Black Swan

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pages: 289 words: 95,046

Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis by Scott Patterson

"World Economic Forum" Davos, 2021 United States Capitol attack, 4chan, Alan Greenspan, Albert Einstein, asset allocation, backtesting, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, bitcoin, Bitcoin "FTX", Black Lives Matter, Black Monday: stock market crash in 1987, Black Swan, Black Swan Protection Protocol, Black-Scholes formula, blockchain, Bob Litterman, Boris Johnson, Brownian motion, butterfly effect, carbon footprint, carbon tax, Carl Icahn, centre right, clean tech, clean water, collapse of Lehman Brothers, Colonization of Mars, commodity super cycle, complexity theory, contact tracing, coronavirus, correlation does not imply causation, COVID-19, Credit Default Swap, cryptocurrency, Daniel Kahneman / Amos Tversky, decarbonisation, disinformation, diversification, Donald Trump, Doomsday Clock, Edward Lloyd's coffeehouse, effective altruism, Elliott wave, Elon Musk, energy transition, Eugene Fama: efficient market hypothesis, Extinction Rebellion, fear index, financial engineering, fixed income, Flash crash, Gail Bradbrook, George Floyd, global pandemic, global supply chain, Gordon Gekko, Greenspan put, Greta Thunberg, hindsight bias, index fund, interest rate derivative, Intergovernmental Panel on Climate Change (IPCC), Jeff Bezos, Jeffrey Epstein, Joan Didion, John von Neumann, junk bonds, Just-in-time delivery, lockdown, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, Mark Spitznagel, Mark Zuckerberg, market fundamentalism, mass immigration, megacity, Mikhail Gorbachev, Mohammed Bouazizi, money market fund, moral hazard, Murray Gell-Mann, Nick Bostrom, off-the-grid, panic early, Pershing Square Capital Management, Peter Singer: altruism, Ponzi scheme, power law, precautionary principle, prediction markets, proprietary trading, public intellectual, QAnon, quantitative easing, quantitative hedge fund, quantitative trading / quantitative finance, Ralph Nader, Ralph Nelson Elliott, random walk, Renaissance Technologies, rewilding, Richard Thaler, risk/return, road to serfdom, Ronald Reagan, Ronald Reagan: Tear down this wall, Rory Sutherland, Rupert Read, Sam Bankman-Fried, Silicon Valley, six sigma, smart contracts, social distancing, sovereign wealth fund, statistical arbitrage, statistical model, stem cell, Stephen Hawking, Steve Jobs, Steven Pinker, Stewart Brand, systematic trading, tail risk, technoutopianism, The Chicago School, The Great Moderation, the scientific method, too big to fail, transaction costs, University of East Anglia, value at risk, Vanguard fund, We are as Gods, Whole Earth Catalog

Sornette finished and took his seat beside Taleb, who was grinning like a Cheshire cat. After mischievously gifting Sornette with a copy of The Black Swan, Taleb put a question to him. “Do you think September 11 was a Black Swan event?” “No,” Sornette replied. “For someone in the building, was it a Black Swan event?” Sornette shrugged. “For the pilot of the plane, was it a Black Swan event? My whole thing is, a Black Swan for the turkey is not a Black Swan for the butcher.” Then Taleb said something he knew would yank Sornette’s chain. Supposedly, he, Taleb, had come up with the Dragon King concept years ago.

There’s a Black Swan wine, a Black Swan publisher, Black Swan yoga, even an exceedingly eccentric comic strip called Black Swan Man that portrays Taleb as a muscle-bound, costumed figure battling the evils of bitcoin and the Federal Reserve and tossing off advice such as “We must always be vigilant against the problem of induction.” Misconceptions about what exactly constitutes a Black Swan endlessly tortured Taleb. People asked: “Was September 11 a Black Swan?” Yes, for the people in the World Trade Center, no for the terrorists. “The Global Financial Crisis?” No, said Taleb. It was entirely predictable (a Gray Swan). Indeed, Taleb and Spitznagel had been forecasting a credit-fueled blowup for years.

Sornette around this time started to become increasingly hostile to Nassim Taleb’s Black Swans. The entire notion behind the Black Swan—that extreme earth-shaking events are impossible to predict—he believed, was radically misguided. It caused people to throw up their hands and stop trying to figure out the future—or understand the past. “The Black Swan concept is dangerous,” Sornette told me. “It puts us back at the time of pre-science where the wrath of nature, the lightning, the storms were the expression of the anger of the gods.” Sornette had long been familiar with Taleb. The Frenchman was a resource for The Black Swan. Indeed, Taleb credits him in the book (“Didier Sornette, always a phone call away, kept e-mailing me papers on various unadvertised, but highly relevant, subjects in statistical physics”).


pages: 651 words: 180,162

Antifragile: Things That Gain From Disorder by Nassim Nicholas Taleb

"World Economic Forum" Davos, Air France Flight 447, Alan Greenspan, Andrei Shleifer, anti-fragile, banking crisis, Benoit Mandelbrot, Berlin Wall, biodiversity loss, Black Swan, business cycle, caloric restriction, caloric restriction, Chuck Templeton: OpenTable:, commoditize, creative destruction, credit crunch, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, discrete time, double entry bookkeeping, Emanuel Derman, epigenetics, fail fast, financial engineering, financial independence, Flash crash, flying shuttle, Gary Taubes, George Santayana, Gini coefficient, Helicobacter pylori, Henri Poincaré, Higgs boson, high net worth, hygiene hypothesis, Ignaz Semmelweis: hand washing, informal economy, invention of the wheel, invisible hand, Isaac Newton, James Hargreaves, Jane Jacobs, Jim Simons, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Kenneth Arrow, knowledge economy, language acquisition, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, Marc Andreessen, Mark Spitznagel, meta-analysis, microbiome, money market fund, moral hazard, mouse model, Myron Scholes, Norbert Wiener, pattern recognition, Paul Samuelson, placebo effect, Ponzi scheme, Post-Keynesian economics, power law, principal–agent problem, purchasing power parity, quantitative trading / quantitative finance, Ralph Nader, random walk, Ray Kurzweil, rent control, Republic of Letters, Ronald Reagan, Rory Sutherland, Rupert Read, selection bias, Silicon Valley, six sigma, spinning jenny, statistical model, Steve Jobs, Steven Pinker, Stewart Brand, stochastic process, stochastic volatility, synthetic biology, tacit knowledge, tail risk, Thales and the olive presses, Thales of Miletus, The Great Moderation, the new new thing, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Malthus, too big to fail, transaction costs, urban planning, Vilfredo Pareto, Yogi Berra, Zipf's Law

Cambridge: Cambridge University Press. Taleb, N. N., and M. Blyth, 2011, “The Black Swan of Cairo.” Foreign Affairs 90(3). Taleb, N. N., and A. Pilpel, 2007, “Epistemology and Risk Management.” Risk and Regulation 13, Summer. Taleb, N. N., and C. Tapiero, 2010, “The Risk Externalities of Too Big to Fail.” Physica A: Statistical Physics and Applications. Taleb, N. N., D. G. Goldstein, and M. Spitznagel, 2009, “The Six Mistakes Executives Make in Risk Management,” Harvard Business Review (October). Taleb, N. N., 2008, “Infinite Variance and the Problems of Practice.” Complexity 14(2). Taleb, N. N., 2009, “Errors, Robustness, and the Fourth Quadrant.”

And the notion that science equals measurement free of error—it is, largely but not in everything—can lead us to all manner of fictions, delusions, and dreams. An excellent understanding of probability linked to skepticism: Franklin (2001). Few other philosophers go back to the real problem of probability. Fourth Quadrant: See the discussion in The Black Swan or paper Taleb (1999). Nuclear, new risk management: Private communication, Atlanta, INPO, Nov. 2011. Anecdotal knowledge and power of evidence: A reader, Karl Schluze, wrote: “An old teacher and colleague told me (between his sips of bourbon) ‘If you cut off the head of a dog and it barks, you don’t have to repeat the experiment.’ ” Easy to get examples: no lawyer would invoke an “N=1” argument in defense of a person, saying “he only killed once”; nobody considers a plane crash as “anecdotal.”

It looks like what we interpret as political systems might come from size. Evidence in Easterly and Kraay (2000). The age of increasing fragility: Zajdenwebber, see the discussion in The Black Swan. Numbers redone recently in The Economist, “Counting the Cost of Calamities,” Jan. 14, 2012. Convexity effect on mean: Jensen (1906), Van Zwet (1966). While Jensen deals with monotone functions, Van Zwet deals with concave-convex and other mixtures—but these remain simple nonlinearities. Taleb and Douady (2012) applies it to all forms of local nonlinearities. Empirical record of bigger: Mergers and hubris hypothesis: in Roll (1986); since then Cartwright and Schoenberg (2006).


pages: 306 words: 82,765

Skin in the Game: Hidden Asymmetries in Daily Life by Nassim Nicholas Taleb

anti-fragile, availability heuristic, behavioural economics, Benoit Mandelbrot, Bernie Madoff, Black Swan, Brownian motion, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, cellular automata, Claude Shannon: information theory, cognitive dissonance, complexity theory, data science, David Graeber, disintermediation, Donald Trump, Edward Thorp, equity premium, fake news, financial independence, information asymmetry, invisible hand, knowledge economy, loss aversion, mandelbrot fractal, Mark Spitznagel, mental accounting, microbiome, mirror neurons, moral hazard, Murray Gell-Mann, offshore financial centre, p-value, Paradox of Choice, Paul Samuelson, Ponzi scheme, power law, precautionary principle, price mechanism, principal–agent problem, public intellectual, Ralph Nader, random walk, rent-seeking, Richard Feynman, Richard Thaler, Ronald Coase, Ronald Reagan, Rory Sutherland, Rupert Read, Silicon Valley, Social Justice Warrior, Steven Pinker, stochastic process, survivorship bias, systematic bias, tail risk, TED Talk, The Nature of the Firm, Tragedy of the Commons, transaction costs, urban planning, Yogi Berra

Palgrave Macmillan. Sandis, Constantine, and Nassim Nicholas Taleb, 2015. “Leadership Ethics and Asymmetry.” In Leadership and Ethics, ed. Boaks and Levine, 233. London: Bloomsbury. Stiglitz, J. E., 1988. “Principal and Agent.” In The New Palgrave Dictionary of Economics, vol. 3. London: Macmillan. Taleb, N. N., 2007. “Black Swans and the Domains of Statistics.” The American Statistician 61(3): 198–200. Taleb, N. N., and P. Cirillo, 2015. “On the Shadow Moments of Apparently Infinite-Mean Phenomena,” arXiv preprint arXiv:1510.06731. Taleb, N. N., and R. Douady, 2015. “On the Super-Additivity and Estimation Biases of Quantile Contributions.”

FOOLED BY RANDOMNESS (2001, 2004), on how we tend to mistake luck for skills, how randomness does not look random, why there is no point talking about performance when it is easier to buy and sell than fry an egg, and the profound difference between dentists and speculators. THE BLACK SWAN (2007, 2010), on how high-impact but rare events dominate history, how we retrospectively give ourselves the illusion of understanding them thanks to narratives, how they are impossible to estimate scientifically, how this makes some areas—but not others—totally unpredictable and unforecastable, how confirmatory methods of knowledge don’t work, and how thanks to Black Swan–blind “faux experts” we are prone to building systems increasingly fragile to extreme events. THE BED OF PROCRUSTES (Philosophical Aphorisms) (2010, 2016) ANTIFRAGILE (2012), on how some things like disorder (hence volatility, time, chaos, variability, and stressors) while others don’t, how we can classify things along the lines fragile-robust-antifragile, how we can identify (anti)fragility based on nonlinear response without having to know much about the history of the process (which solves most of the Black Swan problem), and why you are alive if and only if you love (some) volatility.

For instance, bank blowups came in 2008 because of the accumulation of hidden and asymmetric risks in the system: bankers, master risk transferors, could make steady money from a certain class of concealed explosive risks, use academic risk models that don’t work except on paper (because academics know practically nothing about risk), then invoke uncertainty after a blowup (that same unseen and unforecastable Black Swan and that same very, very stubborn author), and keep past income—what I have called the Bob Rubin trade. The Bob Rubin trade? Robert Rubin, a former Secretary of the United States Treasury, one of those who sign their names on the banknote you just used to pay for coffee, collected more than $120 million in compensation from Citibank in the decade preceding the banking crash of 2008. When the bank, literally insolvent, was rescued by the taxpayer, he didn’t write any check—he invoked uncertainty as an excuse. Heads he wins, tails he shouts “Black Swan.” Nor did Rubin acknowledge that he transferred risk to taxpayers: Spanish grammar specialists, assistant schoolteachers, supervisors in tin can factories, vegetarian nutrition advisors, and clerks for assistant district attorneys were “stopping him out,” that is, taking his risks and paying for his losses.


pages: 317 words: 100,414

Superforecasting: The Art and Science of Prediction by Philip Tetlock, Dan Gardner

Affordable Care Act / Obamacare, Any sufficiently advanced technology is indistinguishable from magic, availability heuristic, behavioural economics, Black Swan, butterfly effect, buy and hold, cloud computing, cognitive load, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, desegregation, drone strike, Edward Lorenz: Chaos theory, forward guidance, Freestyle chess, fundamental attribution error, germ theory of disease, hindsight bias, How many piano tuners are there in Chicago?, index fund, Jane Jacobs, Jeff Bezos, Kenneth Arrow, Laplace demon, longitudinal study, Mikhail Gorbachev, Mohammed Bouazizi, Nash equilibrium, Nate Silver, Nelson Mandela, obamacare, operational security, pattern recognition, performance metric, Pierre-Simon Laplace, place-making, placebo effect, precautionary principle, prediction markets, quantitative easing, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, Robert Shiller, Ronald Reagan, Saturday Night Live, scientific worldview, Silicon Valley, Skype, statistical model, stem cell, Steve Ballmer, Steve Jobs, Steven Pinker, tacit knowledge, tail risk, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Watson beat the top human players on Jeopardy!

If you were asked to envision all the possible swans you might ever encounter, you would probably imagine lots and lots of swans that vary in size and shape, but all would be white, because your experience has taught you all swans are white. But then a ship returns from Australia. On board is a swan—a black swan. You are stunned. The “black swan” is therefore a brilliant metaphor for an event so far outside experience we can’t even imagine it until it happens. But Taleb isn’t interested only in surprise. A black swan must be impactful. Indeed, Taleb insists that black swans, and black swans alone, determine the course of history. “History and societies do not crawl,” he wrote. “They make jumps.”4 The implication for my efforts to improve foresight are devastating: IARPA has commissioned a fool’s errand.

“I said that the tactic was very much under consideration and I suspected that some terrorist groups would use it sooner rather than later.”5 Other events that have been called black swans—such as the outbreak of World War I, which was preceded by more than a decade of fretting about the danger of war among the great powers—also fail the unimaginability test. If black swans must be inconceivable before they happen, a rare species of event suddenly becomes a lot rarer. But Taleb also offers a more modest definition of a black swan as a “highly improbable consequential event.”6 These are not hard to find in history. And as Taleb and I explored in our joint paper, this is where the truth in his critique can be found.

But my Good Judgment Project is premised on misconceptions, panders to desperation, and fosters foolish complacency. I respect Taleb. He and I have even cowritten a paper on a key area where we agree. I think his critique makes deep points that future tournaments will have to struggle to address. But I see another false dichotomy rearing its head: “forecasting is feasible if you follow my formula” versus “forecasting is bunk.” Dispelling the dichotomy requires putting the beguiling black swan metaphor under the analytic microscope. What exactly is a black swan? The stringent definition is something literally inconceivable before it happens. Taleb has implied as much on occasion. If so, many events dubbed black swans are actually gray.


pages: 338 words: 106,936

The Physics of Wall Street: A Brief History of Predicting the Unpredictable by James Owen Weatherall

Alan Greenspan, Albert Einstein, algorithmic trading, Antoine Gombaud: Chevalier de Méré, Apollo 11, Asian financial crisis, bank run, Bear Stearns, beat the dealer, behavioural economics, Benoit Mandelbrot, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, Bonfire of the Vanities, book value, Bretton Woods, Brownian motion, business cycle, butterfly effect, buy and hold, capital asset pricing model, Carmen Reinhart, Claude Shannon: information theory, coastline paradox / Richardson effect, collateralized debt obligation, collective bargaining, currency risk, dark matter, Edward Lorenz: Chaos theory, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, Financial Modelers Manifesto, fixed income, George Akerlof, Gerolamo Cardano, Henri Poincaré, invisible hand, Isaac Newton, iterative process, Jim Simons, John Nash: game theory, junk bonds, Kenneth Rogoff, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, Market Wizards by Jack D. Schwager, martingale, Michael Milken, military-industrial complex, Myron Scholes, Neil Armstrong, new economy, Nixon triggered the end of the Bretton Woods system, Paul Lévy, Paul Samuelson, power law, prediction markets, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk free rate, risk-adjusted returns, Robert Gordon, Robert Shiller, Ronald Coase, Sharpe ratio, short selling, Silicon Valley, South Sea Bubble, statistical arbitrage, statistical model, stochastic process, Stuart Kauffman, The Chicago School, The Myth of the Rational Market, tulip mania, Vilfredo Pareto, volatility smile

A second kind of criticism — one that has already come up in the book — has found its biggest champion in Nassim Taleb. Taleb has written an influential book, The Black Swan, which argues that markets are far too wild to be tamed by physicists. A black swan, you’ll recall, is an event that is so unprecedented it is simply impossible to predict. Black swans, Taleb argues, are what really matter — and yet they are precisely what our best mathematical models are unable to anticipate. This is a particular problem for financial modeling, Taleb says. He argues in his book and in many articles that physics lives in a world he calls “Mediocristan,” whereas finance lives in “Extremistan.”

But if you plot the size of French cities by their population size, as Zipf’s law would have you do, Paris is still much too big. It breaks the mold. Taleb’s argument trades on the fact that black swans can have enormous consequences. Dragon kings are similar in their influence. They are tyrannical when they appear. But unlike black swans, you can hear them coming. Sornette does not argue that all black swans are really dragon kings in disguise, or even that all market crashes are predictable. But he does argue that many things that might seem like black swans really do issue warnings. In many cases, these warnings take the form of log-periodic precursors, oscillations in some form of data that occur only when the system is in the special state where a massive catastrophe can occur.

And indeed, trying to figure out how to predict the kinds of events that might have seemed like black swans from the perspective of (say) Osborne’s random walk model is precisely what led Sornette to start thinking about dragon kings. Surely not every black swan is really a dragon king in disguise. But that shouldn’t stop us from figuring out how to predict and understand as many kinds of would-be black swans as possible. Taleb, though, wants to go further than this. He believes that black swans show that mathematical modeling, in finance and elsewhere, is fundamentally unreliable. Figuring out how to predict dragon kings, or using fat-tailed distributions to address the fact that extreme events occur more often than normal distributions indicate, isn’t enough.


pages: 299 words: 92,782

The Success Equation: Untangling Skill and Luck in Business, Sports, and Investing by Michael J. Mauboussin

Amazon Mechanical Turk, Atul Gawande, Benoit Mandelbrot, Black Swan, Boeing 747, Checklist Manifesto, Clayton Christensen, cognitive bias, commoditize, Daniel Kahneman / Amos Tversky, David Brooks, deliberate practice, disruptive innovation, Emanuel Derman, fundamental attribution error, Gary Kildall, Gini coefficient, hindsight bias, hiring and firing, income inequality, Innovator's Dilemma, John Bogle, Long Term Capital Management, loss aversion, Menlo Park, mental accounting, moral hazard, Network effects, power law, prisoner's dilemma, random walk, Richard Thaler, risk-adjusted returns, shareholder value, Simon Singh, six sigma, Steven Pinker, transaction costs, winner-take-all economy, zero-sum game, Zipf's Law

New York: Harper, 2010. Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. 2nd ed. New York: ThomsonTexere, 2004. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable, Second Edition. New York: Random House, 2010. Taleb, Nassim Nicholas. The Bed of Procrustes: Philosophical and Practical Aphorisms. New York: Random House, 2010. Taleb, Nassim Nicholas. “Antifragility, Robustness, and Fragility Inside the ‘Black Swan’ Domain.” SSRN working paper, February 2011. Taleb, Nassim Nicholas, and Mark Blyth. “The Black Swan of Cairo: How Suppressing Volatility Makes the World Less Predictable and More Dangerous.”

Shaw, “How Large and Long-lasting Are the Persuasive Effects of Televised Campaign Ads? Results from a Randomized Field Experiment,” American Political Science Review 105, no. 1 (February 2011): 135–150. 21. Nassim Nicholas Taleb, The Bed of Procrustes: Philosophical and Practical Aphorisms (New York: Random House, 2010). 22. Nassim Nicholas Taleb, “Antifragility, Robustness, and Fragility Inside the ‘Black Swan’ Domain,” SSRN working paper, February 2011. 23. Nassim Nicholas Taleb and Mark Blyth, “The Black Swan of Cairo: How Suppressing Volatility Makes the World Less Predictable and More Dangerous,” Foreign Affairs 90, no. 3 (May/June 2011): 33–39; Emanuel Derman distinguishes between models and theories, “Models are analogies; they always describe one thing relative to something else.

In his book of aphorisms, The Bed of Procrustes, he writes: “Sports are commoditized and, alas, prostituted randomness.”21 I don't know exactly what that means, but it leads me to believe that watching a ball game is not among Taleb's favorite pastimes. One of my main points is that most people have trouble untangling skill and luck even in cases where it is possible to do so. But it is still important to acknowledge the limits of the methods at our disposal, and Taleb's work effectively illustrates that point. Let's look at the nature of the fourth quadrant in an effort to understand why we get fooled by it and what we can do about that. The fourth quadrant is the world of black swans. Taleb argues that having no theory or model of events in the fourth quadrant is preferable to having a theory or model, because the errors we make are huge and often lead to bad results.


pages: 57 words: 11,522

The Bed of Procrustes: Philosophical and Practical Aphorisms by Nassim Nicholas Taleb

Benoit Mandelbrot, Black Swan, commoditize, knowledge worker, Republic of Letters

ALSO BY NASSIM NICHOLAS TALEB Fooled by Randomness The Black Swan Copyright © 2010 by Nassim Nicholas Taleb All rights reserved. Published in the United States by Random House, an imprint of The Random House Publishing Group, a division of Random House, Inc., New York. RANDOM HOUSE and colophon are registered trademarks of Random House, Inc. Library of Congress Cataloging-in-Publication Data Taleb, Nassim. The bed of Procrustes: philosophical and practical aphorisms / by Nassim Nicholas Taleb. p. cm. eISBN: 978-0-679-64368-5 1. Aphorisms and apothegms. 2. Human behavior— Quotations, maxims, etc.

– The costs of specialization: architects build to impress other architects; models are thin to impress other models; academics write to impress other academics; filmmakers try to impress other filmmakers; painters impress art dealers; but authors who write to impress book editors tend to fail. – It is a waste of emotions to answer critics; better to stay in print long after they are dead. – I can predict when an author is about to plagiarize me, and poorly so when he writes that Taleb “popularized” the theory of Black Swan events.* – Newspaper readers exposed to real prose are like deaf persons at a Puccini opera: they may like a thing or two while wondering, “what’s the point?” – Some books cannot be summarized (real literature, poetry); some can be compressed to about ten pages; the majority to zero pages

* Nor is science capable of dealing effectively with nonlinear and complex matters, those fraught with interdependence (climate, economic life, the human body), in spite of its hyped-up successes in the linear domain (physics and engineering), which give it a prestige that has endangered us. * A Black Swan (capitalized) is an event (historical, economic, technological, personal) that is both unpredicted by some observer and carries massive consequences. In spite of growth in our knowledge, the role of these Black Swans has been growing. * Many philistines reduce my ideas to an opposition to technology when in fact I am opposing the naïve blindness to its side effects—the fragility criterion. I’d rather be unconditional about ethics and conditional about technology than the reverse


pages: 384 words: 93,754

Green Swans: The Coming Boom in Regenerative Capitalism by John Elkington

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, agricultural Revolution, Anthropocene, anti-fragile, Any sufficiently advanced technology is indistinguishable from magic, autonomous vehicles, Berlin Wall, bitcoin, Black Swan, blockchain, Boeing 737 MAX, Boeing 747, Buckminster Fuller, business cycle, Cambridge Analytica, carbon footprint, carbon tax, circular economy, Clayton Christensen, clean water, cloud computing, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, CRISPR, crowdsourcing, David Attenborough, deglobalization, degrowth, discounted cash flows, distributed ledger, do well by doing good, Donald Trump, double entry bookkeeping, drone strike, Elon Musk, en.wikipedia.org, energy transition, Extinction Rebellion, Future Shock, Gail Bradbrook, Geoffrey West, Santa Fe Institute, George Akerlof, global supply chain, Google X / Alphabet X, green new deal, green transition, Greta Thunberg, Hans Rosling, hype cycle, impact investing, intangible asset, Internet of things, invention of the wheel, invisible hand, Iridium satellite, Jeff Bezos, John Elkington, Jony Ive, Joseph Schumpeter, junk bonds, Kevin Kelly, Kickstarter, M-Pesa, Marc Benioff, Mark Zuckerberg, Martin Wolf, microplastics / micro fibres, more computing power than Apollo, move fast and break things, Naomi Klein, Nelson Mandela, new economy, Nikolai Kondratiev, ocean acidification, oil shale / tar sands, oil shock, opioid epidemic / opioid crisis, placebo effect, Planet Labs, planetary scale, plant based meat, plutocrats, Ponzi scheme, radical decentralization, Ralph Nader, reality distortion field, Recombinant DNA, Rubik’s Cube, Salesforce, self-driving car, shareholder value, sharing economy, Sheryl Sandberg, Silicon Valley, smart cities, smart grid, sovereign wealth fund, space junk, Steven Pinker, Stewart Brand, supply-chain management, synthetic biology, systems thinking, The future is already here, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Tim Cook: Apple, urban planning, Whole Earth Catalog

In the work of Nassim Nicholas Taleb, particularly as outlined in his highly influential book The Black Swan, the focus was frequently on transformations that were degenerative. For him, a Black Swan—both words capitalized—is a rare event characterized by its extreme impact and its retrospective (though not prospective) predictability. A typical question after a Black Swan event would be the following: “How did we/they fail to spot that one coming?” Think about the 2007–2008 market crash or the 2011 Fukushima nuclear disaster in Japan. Interestingly, even the blackest of Black Swans will generally have been foreseen by someone, at least in broad terms, as with maverick economist Hyman P.

., https://twitter.com/raydalio/status/1114987900201066496. 8.Irwin Stelzer, “Save Capitalism from Capitalists,” The Sunday Times, April 21, 2019. 9.https://en.wikipedia.org/wiki/Capitalism 10.https://www.theguardian.com/books/2017/sep/28/death-homo-economicus-peter-fleming-review 11.http://theageofconsequences.com 12.Taleb, The Black Swan. 13.https://en.wikipedia.org/wiki/Black_swan_theory 14.Stephen Gibbs, “Economy Shrinks by Half under Maduro,” The Times, May 30, 2019. 15.John Summers, Black Swan Events, Institute of Risk Management NW seminar, January 26, 2012. See also: https://www.theirm.org/media/1120524/Popularmisconceptionsaboutblackswanevents-JohnSummers.pdf. 16.https://www.historynet.com/failed-peace-treaty-versailles-1919.htm 17.One exception was John Maynard Keynes.

They will feed into our thinking about the Green Swan Awards, see https://volans.com/green-swans-2020/, the first two being won by Sir Tim Smit of the Eden Project and Sacha Dench of Conservation Without Borders. Please send any suggestions, ideally with an explanation and links to further details, to me at john@volans.com. Endnotes WELCOME 1.For more on Taleb’s books, including The Black Swan, see his website: http://www.fooledbyrandomness.com. 2.Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable. New York: Penguin Random House, 2007. 3.https://www.ssga.com/blog/2019/01/gray-swans-for-2019.html 4.Camilla Cavendish, Extra Time: 10 Lessons for an Ageing World. New York: HarperCollins Publishers, 2019. 5.https://jembendell.com/about/ 6.Andrew Edgecliffe-Johnson, “Capitalism Keeps CEOs Awake at Night,” Financial Times, April 23, 2019. 7.Ray Dalio, “As most of you know, I’m a capitalist, and even I think capitalism is broken,” @RayDalio, April 7, 2019, 1:26 p.m., https://twitter.com/raydalio/status/1114987900201066496. 8.Irwin Stelzer, “Save Capitalism from Capitalists,” The Sunday Times, April 21, 2019. 9.https://en.wikipedia.org/wiki/Capitalism 10.https://www.theguardian.com/books/2017/sep/28/death-homo-economicus-peter-fleming-review 11.http://theageofconsequences.com 12.Taleb, The Black Swan. 13.https://en.wikipedia.org/wiki/Black_swan_theory 14.Stephen Gibbs, “Economy Shrinks by Half under Maduro,” The Times, May 30, 2019. 15.John Summers, Black Swan Events, Institute of Risk Management NW seminar, January 26, 2012.


pages: 374 words: 114,600

The Quants by Scott Patterson

Alan Greenspan, Albert Einstein, AOL-Time Warner, asset allocation, automated trading system, Bear Stearns, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Bernie Sanders, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, Blythe Masters, Bonfire of the Vanities, book value, Brownian motion, buttonwood tree, buy and hold, buy low sell high, capital asset pricing model, Carl Icahn, centralized clearinghouse, Claude Shannon: information theory, cloud computing, collapse of Lehman Brothers, collateralized debt obligation, commoditize, computerized trading, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Donald Trump, Doomsday Clock, Dr. Strangelove, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, financial engineering, Financial Modelers Manifesto, fixed income, Glass-Steagall Act, global macro, Gordon Gekko, greed is good, Haight Ashbury, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, index fund, invention of the telegraph, invisible hand, Isaac Newton, Jim Simons, job automation, John Meriwether, John Nash: game theory, junk bonds, Kickstarter, law of one price, Long Term Capital Management, Louis Bachelier, low interest rates, mandelbrot fractal, margin call, Mark Spitznagel, merger arbitrage, Michael Milken, military-industrial complex, money market fund, Myron Scholes, NetJets, new economy, offshore financial centre, old-boy network, Paul Lévy, Paul Samuelson, Ponzi scheme, proprietary trading, quantitative hedge fund, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, risk-adjusted returns, Robert Mercer, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Savings and loan crisis, Sergey Aleynikov, short selling, short squeeze, South Sea Bubble, speech recognition, statistical arbitrage, The Chicago School, The Great Moderation, The Predators' Ball, too big to fail, transaction costs, value at risk, volatility smile, yield curve, éminence grise

Prices can gyrate wildly over short periods of time—wildly enough to cause massive, potentially crippling losses to investors who’ve made large, leveraged wagers. As Nassim Nicholas Taleb, a critic of quant models, later argued in several books, investors who believe the market moves according to a random walk are “fooled by randomness” (the title of one of his books). Taleb famously dubbed the wild unexpected swings in markets, and in life itself, “black swans,” evoking the belief long held in the West that all swans are white, a notion exploded when sailors discovered black swans in Australia. Taleb argued that there are far more black swans in the world than many people believe, and that models based on historical trends and expectations of a random walk are bound to lead their users to destruction.

But one evening a colleague: “Going Under, Happily,” by Pete Muller as told to Loch Adamson, New York Times, June 8, 2003. In May 2002, he attended the wedding: The wedding account is based on interviews with Nassim Taleb, John Liew, and Neil Chriss. His peripatetic life had shown him: The brief account of Taleb’s life is based on numerous interviews with Taleb and his longtime trading partner Mark Spitznagel, as well as the articles “Blowing Up: How Nassim Taleb Turned the Inevitability of Disaster into an Investment Strategy,” by Malcolm Gladwell, New Yorker, April 22 and 29, 2002, and “Flight of the Black Swan,” by Stephanie Baker-Said, Bloomberg Markets, May 2008. Once or twice a month: The subjects of this book did not discuss this poker game often.

The Truth was very simple, and remorseless as the driving force of any cutthroat Wall Street banker: Did you make money, or not? Nothing else mattered. Meanwhile, a fund with ties to Nassim Taleb, Universa Investments, was also hitting on all cylinders. Funds run by Universa, managed and owned by Taleb’s longtime collaborator Mark Spitznagel, gained as much as 150 percent in 2008 on its bet that the market is far more volatile than most quant models predict. The fund’s Black Swan Protocol Protection plan purchased far-out-of-the-money put options on stocks and stock indexes, which paid off in spades after Lehman collapsed as the market tanked.


pages: 256 words: 60,620

Think Twice: Harnessing the Power of Counterintuition by Michael J. Mauboussin

affirmative action, Alan Greenspan, asset allocation, Atul Gawande, availability heuristic, Benoit Mandelbrot, Bernie Madoff, Black Swan, butter production in bangladesh, Cass Sunstein, choice architecture, Clayton Christensen, cognitive dissonance, collateralized debt obligation, Daniel Kahneman / Amos Tversky, deliberate practice, disruptive innovation, Edward Thorp, experimental economics, financial engineering, financial innovation, framing effect, fundamental attribution error, Geoffrey West, Santa Fe Institute, George Akerlof, hindsight bias, hiring and firing, information asymmetry, libertarian paternalism, Long Term Capital Management, loose coupling, loss aversion, mandelbrot fractal, Menlo Park, meta-analysis, money market fund, Murray Gell-Mann, Netflix Prize, pattern recognition, Performance of Mutual Funds in the Period, Philip Mirowski, placebo effect, Ponzi scheme, power law, prediction markets, presumed consent, Richard Thaler, Robert Shiller, statistical model, Steven Pinker, systems thinking, the long tail, The Wisdom of Crowds, ultimatum game, vertical integration

City sizes have a much wider range of outcomes than human heights do.8 Nassim Taleb, an author and former derivatives trader, calls the extreme outcomes within power law distributions black swans. He defines a black swan as an outlier event that has a consequential impact and that humans seek to explain after the fact.9 In large part owing to Taleb’s efforts, more people are aware of black swans and distributions that deviate from the bell curve. What most people still don’t appreciate is the mechanism that propagates black swans. Here’s where critical points and phase transitions come in. Positive feedback leads to outcomes that are outliers.

In cases where cause and effect are not clear, learning from history is a challenge. Here are some tips on how to cope with systems that have phase transitions: 1. Study the distribution of outcomes for the system you are dealing with. Thanks to Taleb’s prodding, many people now associate extreme events with black swans. But Taleb makes a careful, if overlooked, distinction: if we understand what the broader distribution looks like, the outcomes—however extreme—are correctly labeled as gray swans, not black swans. He calls them “modelable extreme events.” In fact, scientists have done a lot of work classifying the distributions of various systems, including the stock market, terrorist acts, and power-grid failures.25 So if you have the background and tools to understand these systems, you can get a general view of how the system behaves, even if you have no reliable means of predicting any specific event.

Ford, and Robert R. Hoffman (Menlo Park, CA, and Cambridge, MA: AAAI Press and MIT Press, 1997), 125–146. Taleb, The Black Swan, discusses a similar concept he calls the “ludic fallacy.” 15. Donald MacKenzie, An Engine, Not a Camera: How Financial Models Shape Markets (Cambridge: MIT Press, 2006). 16. Benoit Mandelbrot, “The Variation of Certain Speculative Prices,” in The Random Character of Stock Market Prices, ed. Paul H. Cootner, (Cambridge: MIT Press, 1964), 369–412. This is also a core theme of Taleb, The Black Swan. See also Benoit Mandelbrot and Richard L. Hudson, The (Mis)Behavior of Markets (New York: Basic Books, 2004). 17.


pages: 161 words: 51,919

What's Your Future Worth?: Using Present Value to Make Better Decisions by Peter Neuwirth

backtesting, big-box store, Black Swan, collective bargaining, discounted cash flows, en.wikipedia.org, financial engineering, Long Term Capital Management, Rubik’s Cube, Skype, the scientific method

See en.wikipedia.org/wiki/Bell_System 24. See en.wikipedia.org/wiki/Econometric_model 25. Nassim N. Taleb, Fooled by Randomness, Random House (Trade Paperback Edition), 2005. 26. Ibid. pp. 113–115. 27. Ibid. pp. 116–131. 28. Ibid. pp. 126–127. 29. See en.wikipedia.org/wiki/General_equilibrium_theory 30. See FCC Record, Volume 07, No. 09, p. 2724, April 20–May 1, 1992. 31. Nassim N. Taleb, The Black Swan (Random House [Trade Paperback edition], 2010). 32. From 1/1/1982 to 1/1/2000 the S&P 500 rose from 122.55 to 1469.25, a return of almost 15%/year 33. Taleb, Fooled by Randomness, 113–115. 34. There were countless postmortems after the LTCM collapse.

For one thing, the discounted cash flow method generally focuses on just the “high likelihood” scenarios, while in Present Value thinking we try to imagine all the possibilities, recognizing that low likelihood/high impact possibilities can be very important. Nassim Taleb calls these possibilities “Black Swan” events and suggests that such “impossible to predict” scenarios are the ones that ultimately change our lives in the most important ways.40 While I agree with Taleb that these scenarios are impossible to predict, I don’t think they are impossible to imagine. That is why step 2 is so critical to Present Value thinking, a step that is usually given little attention in discounted cash flow analysis.

., 103 discounted cash flow method, 117–118 inadequate for organizations, 128 discount rate(s), 11 definition of, 51–57 example of, 26 Don’t Work Forever (Vernon), 158 E econometric model, 89–90, 91 education, investing in, 45–49 expanding funnel of doubt, 80–83, 98 F FCC, 84–85, 91 financial crisis of 2008–9, 155 financial engineers, 93 financial planning, 157–160 5-step process, 7–13 in day-to-day decisions, 24–37 discount rate and, 11 evaluating impacts of what might happen, 9 non-attachment to a specific scenario and, 9 only calculation in, 8 fooled by randomness, 83–96 Fooled by Randomness (Taleb), 87–88 foregone investment, 118, 119 Foundation Trilogy (Asimov), 66 Frohlich, Rob, 130–138 future. See also “Black Swan”; Taleb, Nassim Nicholas and Big Data, 66 considering all possible, 5 doesn’t really exist, 2–3 imagining the, 65–76 impossibility of predicting the, 95–96, 118 nature of the, 66–70 non-attachment to any particular, 69 and objectivity evaluating likelihood of scenarios, 69 predicting the, 3 thinking about the, 68–70 uncertainty about the, 39, 67 unlikely scenarios, 125–126 G General Equilibrium Model, 91 H hedge funds, 94 Heinlein, Robert, 65 hot steaks, 78 I induction, principle of, 90.


pages: 111 words: 1

Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets by Nassim Nicholas Taleb

Alan Greenspan, Antoine Gombaud: Chevalier de Méré, availability heuristic, backtesting, behavioural economics, Benoit Mandelbrot, Black Swan, commoditize, complexity theory, corporate governance, corporate raider, currency peg, Daniel Kahneman / Amos Tversky, discounted cash flows, diversified portfolio, endowment effect, equity premium, financial engineering, fixed income, global village, hedonic treadmill, hindsight bias, junk bonds, Kenneth Arrow, Linda problem, Long Term Capital Management, loss aversion, mandelbrot fractal, Mark Spitznagel, Market Wizards by Jack D. Schwager, mental accounting, meta-analysis, Michael Milken, Myron Scholes, PalmPilot, Paradox of Choice, Paul Samuelson, power law, proprietary trading, public intellectual, quantitative trading / quantitative finance, QWERTY keyboard, random walk, Richard Feynman, risk free rate, road to serfdom, Robert Shiller, selection bias, shareholder value, Sharpe ratio, Steven Pinker, stochastic process, survivorship bias, too big to fail, Tragedy of the Commons, Turing test, Yogi Berra

He also taught at the Courant Institute of Mathematical Sciences of New York University. His degrees include an MBA from the Wharton School and a Ph.D. from the University of Paris. In addition to his scientific and literary interests, Taleb’s hobby is to poke fun at those who take themselves and the quality of their knowledge too seriously. His work has been published in twenty-seven languages (even French) and has more than a million readers. He lives mostly in New York. Also by Nassim Nicholas Taleb The Black Swan Footnotes To return to the corresponding text, click on the reference number or "Return to text." Chapter 7 *What I call empiricism does not simply mean “just look at reality”: it implies the rigorous avoidance of hasty generalizations outside what you saw, your “empiri-cism.”

Nowhere is the problem of induction more relevant than in the world of trading—and nowhere has it been as ignored! Cygnus Atratus In his Treatise on Human Nature, the Scots philosopher David Hume posed the issue in the following way (as rephrased in the now famous black swan problem by John Stuart Mill): No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion. Hume had been irked by the fact that science in his day (the eighteenth century) had experienced a swing from scholasticism, entirely based on deductive reasoning (no emphasis on the obsdervation of the real world) to, owing to Francis Bacon, an overreaction into naive and unstructured empiricism.

“I’m As Good As My Last Trade” and Other Heuristics Degree in a Fortune Cookie Two Systems of Reasoning WHY WE DON’T MARRY THE FIRST DATE Our Natural Habitat Fast and Frugal Neurobiologists Too Kafka in a Courtroom An Absurd World Examples of Biases in Understanding Probability We Are Option Blind PROBABILITIES AND THE MEDIA (MORE JOURNALISTS) CNBC at Lunchtime You Should Be Dead by Now The Bloomberg Explanations Filtering Methods We Do Not Understand Confidence Levels An Admission PART III: WAX IN MY EARS • Living with Randomitis I AM NOT SO INTELLIGENT WITTGENSTEIN’S RULER THE ODYSSEAN MUTE COMMAND Twelve GAMBLERS’ TICKS AND PIGEONS IN A BOX TAXI-CAB ENGLISH AND CAUSALITY THE SKINNER PIGEON EXPERIMENT PHILOSTRATUS REDUX Thirteen CARNEADES COMES TO ROME: ON PROBABILITY AND SKEPTICISM CARNEADES COMES TO ROME Probability, the Child of Skepticism MONSIEUR DE NORPOIS’ OPINIONS Path Dependence of Beliefs COMPUTING INSTEAD OF THINKING FROM FUNERAL TO FUNERAL Fourteen BACCHUS ABANDONS ANTONY NOTES ON JACKIE O. ’S FUNERAL RANDOMNESS AND PERSONAL ELEGANCE Epilogue SOLON TOLD YOU SO Beware the London Traffic Jams Postscript THREE AFTERTHOUGHTS IN THE SHOWER FIRST THOUGHT: THE INVERSE SKILLS PROBLEM SECOND THOUGHT: ON SOME ADDITIONAL BENEFITS OF RANDOMNESS Uncertainty and Happiness The Scrambling of Messages THIRD THOUGHT: STANDING ON ONE LEG Acknowledgments for the First Edition A Trip to the Library: Notes and Reading Recommendations Notes References About the Author Also by Nassim Nicholas Taleb Copyright To my mother, Minerva Ghosn Taleb PREFACE TAKING KNOWLEDGE LESS SERIOUSLY This book is the synthesis of, on one hand, the no-nonsense practitioner of uncertainty whospen this professional life trying to resist being fooled by randomness and trick the emotions associated with probabilistic outcomes and, on the other, the aesthetically obsessed, literature-loving human being willing to be fooled by any form of nonsense that is polished, refined, original, and tasteful.


pages: 367 words: 97,136

Beyond Diversification: What Every Investor Needs to Know About Asset Allocation by Sebastien Page

Andrei Shleifer, asset allocation, backtesting, Bernie Madoff, bitcoin, Black Swan, Bob Litterman, book value, business cycle, buy and hold, Cal Newport, capital asset pricing model, commodity super cycle, coronavirus, corporate governance, COVID-19, cryptocurrency, currency risk, discounted cash flows, diversification, diversified portfolio, en.wikipedia.org, equity risk premium, Eugene Fama: efficient market hypothesis, fixed income, future of work, Future Shock, G4S, global macro, implied volatility, index fund, information asymmetry, iterative process, loss aversion, low interest rates, market friction, mental accounting, merger arbitrage, oil shock, passive investing, prediction markets, publication bias, quantitative easing, quantitative trading / quantitative finance, random walk, reserve currency, Richard Feynman, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, robo advisor, seminal paper, shareholder value, Sharpe ratio, sovereign wealth fund, stochastic process, stochastic volatility, stocks for the long run, systematic bias, systematic trading, tail risk, transaction costs, TSMC, value at risk, yield curve, zero-coupon bond, zero-sum game

There are several analytical tools available to asset allocators to model fat tails, such as historical analysis, blended probability distributions, and scenario analysis. Nassim Taleb (2010) argues that we can’t predict higher moments. We don’t know when extreme losses will occur, but we should build resilience to them. Black swans, like the pandemic and oil shock of 2020, are rare, but they do exist. Taleb notes, “The Black Swan idea is not to predict—it is to describe this phenomenon, and how to build systems that can resist Black Swan events.”1 And “Black Swans being unpredictable, we need to adjust to their existence (rather than naïvely try to predict them).”2 There are many examples where we must build resilience to rare but consequential events that we can’t predict, in all areas of life.

Taleb notes, “The Black Swan idea is not to predict—it is to describe this phenomenon, and how to build systems that can resist Black Swan events.”1 And “Black Swans being unpredictable, we need to adjust to their existence (rather than naïvely try to predict them).”2 There are many examples where we must build resilience to rare but consequential events that we can’t predict, in all areas of life. Pick your analogy: skiers wear helmets; cars have air bags; houses are built to withstand hurricanes; boats are built to withstand rogue waves; planes are built to withstand lightning; etc. However, a strict interpretation of Taleb’s black swan theory seems impossible to implement with models and data, because, in his words (Taleb, 2010), a black swan “lies outside the realm of regular expectations, because nothing in the past can convincingly point to its possibility.” If nothing in the past can convincingly point to the possibility of an event, we might as well throw our hands up and not even try to forecast risk.

The Nobel Committee could have tested the Sharpe and Markowitz models—they work like quack remedies sold on the internet—but nobody in Stockholm seems to have thought of it. “Locke’s Madmen, or Bell Curves in the Wrong Places” from The Black Swan: The Impact of the Highly Improbable, with a new section “On Robustness and Fragility” second edition, by Nassim Nicholas Taleb, copyright © 2007, 2010 by Nassim Nicholas Taleb. Used by permission of Random House, an imprint and division of Penguin Random House LLC. All rights reserved. That’s far from Elton and Gruber’s description of the CAPM as “one of the most important discoveries in the field of finance.” Taleb’s concern is that modern portfolio theory and the CAPM were derived under Gaussian assumptions.


pages: 1,239 words: 163,625

The Joys of Compounding: The Passionate Pursuit of Lifelong Learning, Revised and Updated by Gautam Baid

Abraham Maslow, activist fund / activist shareholder / activist investor, Airbnb, Alan Greenspan, Albert Einstein, Alvin Toffler, Andrei Shleifer, asset allocation, Atul Gawande, availability heuristic, backtesting, barriers to entry, beat the dealer, Benoit Mandelbrot, Bernie Madoff, bitcoin, Black Swan, book value, business process, buy and hold, Cal Newport, Cass Sunstein, Checklist Manifesto, Clayton Christensen, cognitive dissonance, collapse of Lehman Brothers, commoditize, corporate governance, correlation does not imply causation, creative destruction, cryptocurrency, Daniel Kahneman / Amos Tversky, deep learning, delayed gratification, deliberate practice, discounted cash flows, disintermediation, disruptive innovation, Dissolution of the Soviet Union, diversification, diversified portfolio, dividend-yielding stocks, do what you love, Dunning–Kruger effect, Edward Thorp, Elon Musk, equity risk premium, Everything should be made as simple as possible, fear index, financial independence, financial innovation, fixed income, follow your passion, framing effect, George Santayana, Hans Rosling, hedonic treadmill, Henry Singleton, hindsight bias, Hyman Minsky, index fund, intangible asset, invention of the wheel, invisible hand, Isaac Newton, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jeff Bezos, John Bogle, Joseph Schumpeter, junk bonds, Kaizen: continuous improvement, Kickstarter, knowledge economy, Lao Tzu, Long Term Capital Management, loss aversion, Louis Pasteur, low interest rates, Mahatma Gandhi, mandelbrot fractal, margin call, Mark Zuckerberg, Market Wizards by Jack D. Schwager, Masayoshi Son, mental accounting, Milgram experiment, moral hazard, Nate Silver, Network effects, Nicholas Carr, offshore financial centre, oil shock, passive income, passive investing, pattern recognition, Peter Thiel, Ponzi scheme, power law, price anchoring, quantitative trading / quantitative finance, Ralph Waldo Emerson, Ray Kurzweil, Reminiscences of a Stock Operator, reserve currency, Richard Feynman, Richard Thaler, risk free rate, risk-adjusted returns, Robert Shiller, Savings and loan crisis, search costs, shareholder value, six sigma, software as a service, software is eating the world, South Sea Bubble, special economic zone, Stanford marshmallow experiment, Steve Jobs, Steven Levy, Steven Pinker, stocks for the long run, subscription business, sunk-cost fallacy, systems thinking, tail risk, Teledyne, the market place, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, time value of money, transaction costs, tulip mania, Upton Sinclair, Walter Mischel, wealth creators, Yogi Berra, zero-sum game

In such a world, events in the distant past continue to echo in the present (path dependence). Or, as Taleb would say, we live primarily in an Extremistan world, one that is full of feedback loops, is filled with interdependence, and thus is black swan–ridden. Taleb’s black swan theory refers to unexpected events of large magnitude and consequences and their dominant role in history. These events are the very reason for Vladimir Lenin’s saying: “There are decades where nothing happens; and there are weeks where decades happen.” Here is my exhaustive list of black swan risks for the coming year: 1. 2. 3. This list will always be empty because you can’t predict a black swan event. A black swan is something that comes as a complete surprise to everyone.

Another hurdle is that, when utilizing Kelly, the long run is based on the number of events, not on a time frame. An investor who bets infrequently will have trouble making enough investments to get the full long-term benefits of applying Kelly. Another key limitation is that people tend to underestimate the role of infrequent, high-impact events, or Taleb’s black swans. The probability and downside magnitude of negative black swans may not be given the necessary consideration when investors look to apply the Kelly criterion, and thus the formula, when applied by the human mind, may tend to overestimate F. And continual overestimation leads to ruin. Anything above the optimal bet size will lead to total loss sooner or later.

., 85 Barron’s, 88, 232–233 Bartlett, Al, 363 base rates, 294 Batnick, Michael, 271 Bayesian methods, 300; biases and, 297; Gardner on, 292–293; Tetlock on, 292–293; translation of language in, 293 Baye’s rule, 292 bear markets, 61; certainty in, 212–213 Becoming Warren Buffett (documentary), 56 beginner’s mind, 290 behavior gap, 331 Benoit, Andy, 68 Berg, Arnold Van Den, 47–48 Berkshire Hathaway, 1, 58, 82, 92, 101, 158, 229; incentive compensation principles at, 147–148; negative press of, 87–88; strengths of, 48 Berlin, Isaiah, 27 Bernstein, Peter, 256; on risk, 255 Berra, Yogi, 147 Beshore, Brent, 174 Bevelin, Peter, 108, 285 Bezos, Jeff, 20, 40, 99 Bhagavad Gita, 63; on investing, 331–332 Bharat Financial Inclusion, 342 biases: from anchoring, 136, 335–338; from association, 133; availability, 14; Bayesian methods and, 297; consistency, 134–135; from deprival syndrome, 135; Fisher on, 337; against high P/E, 213; irrational, 337; from overinfluence, 136; recency, 14, 263; reciprocation tendency, 136; self-serving, 134; status quo, 135; underestimating, 134 big-ticket merger and acquisition, 227 Bill and Melinda Gates Foundation, 64 Bionomics (Rothschild), 286 Bismarck, Otto Von, 349 Black Swan, The (Taleb), 261 black swans, 261–262 bladder theory, 192 Bloomberg, 211 blue-chip stocks, 230–231 Blumkin, Rose, 92 Bogle, John, 229 Bombay Stock Exchange (BSE), 326 bonds: high-risk, 240; junior, 240; low-risk, 240; senior, 240; stocks and, 121–122; total real returns on, 274; Treasury, 255; valuation of, 319–320 boom-and-bust cycles, 238; history of, 282 brands: affordable, 308–309; authenticity of, 223; legitimacy, 222; positional, 222 Brault, Robert, 40 brokers, 348 Brookings Institution, 348 Brooks, John, 264 BSE.


pages: 310 words: 82,592

Never Split the Difference: Negotiating as if Your Life Depended on It by Chris Voss, Tahl Raz

banking crisis, behavioural economics, Black Swan, clean water, cognitive bias, Daniel Kahneman / Amos Tversky, Donald Trump, framing effect, friendly fire, iterative process, loss aversion, market fundamentalism, price anchoring, telemarketer, ultimatum game, uranium enrichment

In seventeenth-century London it was common to refer to impossible things as “Black Swans.” But then the Dutch explorer Willem de Vlamingh went to western Australia in 1697—and saw a black swan. Suddenly the unthinkable and unthought was real. People had always predicted that the next swan they saw would be white, but the discovery of black swans shattered this worldview. Black Swans are just a metaphor, of course. Think of Pearl Harbor, the rise of the Internet, 9/11, and the recent banking crisis. None of the events above was predicted—yet on reflection, the markers were all there. It’s just that people weren’t paying attention. As Taleb uses the term, the Black Swan symbolizes the uselessness of predictions based on previous experience.

Less than a second after Griffin’s silhouette appeared in his scope, the sniper pulled the trigger. Griffin crumpled to the floor, dead. Black Swan theory tells us that things happen that were previously thought to be impossible—or never thought of at all. This is not the same as saying that sometimes things happen against one-in-a-million odds, but rather that things never imagined do come to pass. The idea of the Black Swan was popularized by risk analyst Nassim Nicholas Taleb in his bestselling books Fooled by Randomness (2001)1 and The Black Swan (2007),2 but the term goes back much further. Until the seventeenth century, people could only imagine white swans because all swans ever seen had possessed white feathers.

., 233 Beaudoin, Charlie, 24 Behavioral Change Stairway Model (BCSM), 97 behavioral economics, 11 behavior change BCSM and, 97 health issues and, 97 lessons that lay the foundation for, 112 psychological environment necessary for, 97–98 “that’s right” and, 98, 101–5, 107 “you’re right” as ineffective, 105–7 behind the table or Level II players, 171–72, 186 pronoun usage and, 179, 187 questions to identify, 256 bending reality, 126–35. See also prospect theory key lessons of, 138–39 Bergen, Peter, 232 Black Swan, The (Taleb), 215 Black Swan Group, The, 3, 21, 191, 220 complementary PDF form, bargaining types, 198 website and more information, 258 Black Swans, 19, 21, 213–45 ascertaining counterpart’s unattained goals, 231 asking questions to reveal, 110 “crazy” vs. a clue, 232–33, 245 example, Griffin hostage case, 213–14, 216–17, 235, 244 example, MBA student uncovers seller’s constraints, 238–41 example, Watson standoff, Washington DC, 224–28 getting face time to unearth hidden factors, 236–37 key lessons of, 244–45 knowing a counterpart’s “religion” and, 225, 228–29, 244 as leverage multipliers, 220–24, 244 listening and uncovering, 228, 244–45 mistaking acting on bad information for craziness, 233–34 mistaking constrained for acting crazy, 234–35 mistaking having other interests for acting crazy, 235 observing unguarded moments to unearth hidden factors, 237 Taleb’s use of term, 216 theory of, 215 tips for reading religion correctly, 228 uncovering unknown unknowns, 218–20 what they are, 238 Blum, Gabriella, 2–4, 5 body language.


pages: 327 words: 103,336

Everything Is Obvious: *Once You Know the Answer by Duncan J. Watts

"World Economic Forum" Davos, active measures, affirmative action, Albert Einstein, Amazon Mechanical Turk, AOL-Time Warner, Bear Stearns, behavioural economics, Black Swan, business cycle, butterfly effect, carbon credits, Carmen Reinhart, Cass Sunstein, clockwork universe, cognitive dissonance, coherent worldview, collapse of Lehman Brothers, complexity theory, correlation does not imply causation, crowdsourcing, death of newspapers, discovery of DNA, East Village, easy for humans, difficult for computers, edge city, en.wikipedia.org, Erik Brynjolfsson, framing effect, Future Shock, Geoffrey West, Santa Fe Institute, George Santayana, happiness index / gross national happiness, Herman Kahn, high batting average, hindsight bias, illegal immigration, industrial cluster, interest rate swap, invention of the printing press, invention of the telescope, invisible hand, Isaac Newton, Jane Jacobs, Jeff Bezos, Joseph Schumpeter, Kenneth Rogoff, lake wobegon effect, Laplace demon, Long Term Capital Management, loss aversion, medical malpractice, meta-analysis, Milgram experiment, natural language processing, Netflix Prize, Network effects, oil shock, packet switching, pattern recognition, performance metric, phenotype, Pierre-Simon Laplace, planetary scale, prediction markets, pre–internet, RAND corporation, random walk, RFID, school choice, Silicon Valley, social contagion, social intelligence, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, tacit knowledge, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, too big to fail, Toyota Production System, Tragedy of the Commons, ultimatum game, urban planning, Vincenzo Peruggia: Mona Lisa, Watson beat the top human players on Jeopardy!, X Prize

Once again, we care about things that matter, yet it is precisely these larger, more significant predictions about the future that pose the greatest difficulties. BLACK SWANS AND OTHER “EVENTS” Nowhere is this problem of predicting the things that matter more acute than for what former derivatives trader and gadfly of the financial industry Nassim Taleb calls black swans, meaning events that—like the invention of the printing press, the storming of the Bastille, and the attacks on the World Trade Center—happen rarely but carry great import when they do.15 But what makes an event a black swan? This is where matters get confusing. We tend to speak about events as if they are separate and distinct, and can be assigned a level of importance in the way that we describe natural events such as earthquakes, avalanches, and storms by their magnitude or size.

It’s tempting to think that historical events also follow a heavy-tailed distribution, where Taleb’s black swans lie far out in the tail of the distribution. But as the sociologist William Sewell explains, historical events are not merely “bigger” than others in the sense that some hurricanes are bigger than others. Rather, “events” in the historical sense acquire their significance via the transformations they trigger in wider social arrangements. To illustrate, Sewell revisits the storming of the Bastille on July 14, 1789, an event that certainly seems to satisfy Taleb’s definition of a black swan. Yet as Sewell points out, the event was not just the series of actions that happened in Paris on July 14, but rather encompassed the whole period between July 14 and July 23, during which Louis XVI struggled to control the insurrection in Paris, while the National Assembly at Versailles debated whether to condemn the violence or to embrace it as an expression of the people’s will.

Conversely, the “evidential” view is that a probability should be interpreted only as the odds one ought to accept for a particular gamble, regardless of whether it is repeated or not. 14. See de Mesquita (2009) for details. 15. As Taleb explains, the term “black swan” derives from the European settlement of Australia: Until the settlers witnessed black swans in what is now Western Australia, conventional wisdom held that all swans must be white. 16. For details of the entire sequence of events surrounding the Bastille, see Sewell (1996, pp. 871–78). It is worth noting, moreover, that other historians of the French Revolution draw the boundaries rather differently from Sewell. 17. Taleb makes a similar point—namely that to have predicted the invention of what we now call the Internet, one would have to have known an awful lot about the applications to which the Internet was put after it had been invented.


pages: 807 words: 154,435

Radical Uncertainty: Decision-Making for an Unknowable Future by Mervyn King, John Kay

Airbus A320, Alan Greenspan, Albert Einstein, Albert Michelson, algorithmic trading, anti-fragile, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, autonomous vehicles, availability heuristic, banking crisis, Barry Marshall: ulcers, battle of ideas, Bear Stearns, behavioural economics, Benoit Mandelbrot, bitcoin, Black Swan, Boeing 737 MAX, Bonfire of the Vanities, Brexit referendum, Brownian motion, business cycle, business process, capital asset pricing model, central bank independence, collapse of Lehman Brothers, correlation does not imply causation, credit crunch, cryptocurrency, cuban missile crisis, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, DeepMind, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, Donald Trump, Dutch auction, easy for humans, difficult for computers, eat what you kill, Eddington experiment, Edmond Halley, Edward Lloyd's coffeehouse, Edward Thorp, Elon Musk, Ethereum, Eugene Fama: efficient market hypothesis, experimental economics, experimental subject, fear of failure, feminist movement, financial deregulation, George Akerlof, germ theory of disease, Goodhart's law, Hans Rosling, Helicobacter pylori, high-speed rail, Ignaz Semmelweis: hand washing, income per capita, incomplete markets, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Jeff Bezos, Jim Simons, Johannes Kepler, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Snow's cholera map, John von Neumann, Kenneth Arrow, Kōnosuke Matsushita, Linda problem, Long Term Capital Management, loss aversion, Louis Pasteur, mandelbrot fractal, market bubble, market fundamentalism, military-industrial complex, Money creation, Moneyball by Michael Lewis explains big data, Monty Hall problem, Nash equilibrium, Nate Silver, new economy, Nick Leeson, Northern Rock, nudge theory, oil shock, PalmPilot, Paul Samuelson, peak oil, Peter Thiel, Philip Mirowski, Phillips curve, Pierre-Simon Laplace, popular electronics, power law, price mechanism, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, railway mania, RAND corporation, reality distortion field, rent-seeking, Richard Feynman, Richard Thaler, risk tolerance, risk-adjusted returns, Robert Shiller, Robert Solow, Ronald Coase, sealed-bid auction, shareholder value, Silicon Valley, Simon Kuznets, Socratic dialogue, South Sea Bubble, spectrum auction, Steve Ballmer, Steve Jobs, Steve Wozniak, Suez crisis 1956, Tacoma Narrows Bridge, Thales and the olive presses, Thales of Miletus, The Chicago School, the map is not the territory, The Market for Lemons, The Nature of the Firm, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Thomas Malthus, Toyota Production System, transaction costs, ultimatum game, urban planning, value at risk, world market for maybe five computers, World Values Survey, Yom Kippur War, zero-sum game

., ‘Why Knight Capital Was Saved and Lehman Brothers Failed’, Forbes (20 Aug 2012) < https://www.forbes.com/sites/advisor/2012/08/20/why-knight-capital-was-saved-and-lehman-brothers-failed/ > (accessed 14 Jan 2019) Taleb, N. N., Antifragile: Things that Gain from Disorder (London: Penguin, 2013) Taleb, N. N., The Black Swan: The Impact of the Highly Improbable (London: Penguin, 2008) Taleb, N. N., Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets (London: Penguin, 2007) Taleb, N. N., Skin in the Game: Hidden Asymmetries in Daily Life (London: Allen Lane, 2018) Tetlock, P. E., Expert Political Judgement: How Good Is It? How Can We Know?

When we describe radical uncertainty we are not talking about ‘long tails’ – imaginable and well-defined events whose low probability can be estimated, such as a long losing streak at roulette. And we are not only talking about the ‘black swans’ identified by Nassim Nicholas Taleb – surprising events which no one could have anticipated until they happen, although these ‘black swans’ are examples of radical uncertainty. 19 We are emphasising the vast range of possibilities that lie in between the world of unlikely events which can nevertheless be described with the aid of probability distributions, and the world of the unimaginable.

Ultimately, he found easier and more profitable applications of his skills on Wall Street. 6 Regulators of securities markets restrict the activities of traders with superior information for superficially different but substantively similar reasons. Unknown unknowns At the opposite pole of uncertainty from true randomness are the genuinely unknown unknowns. Taleb’s metaphor of the ‘black swan’ describes the unknown unknowns of business and finance, which are no less important than those of aviation. The origin of the metaphor is that Europeans believed all swans to be white – as all European swans are – until the colonists of Australia observed black swans. A century ago, a telephone that would fit in your pocket, take photographs, calculate the square root of a number, navigate to an unknown destination, and on which you could read any of a million novels, was not improbable; it was just not within the scope of imagination or bounds of possibility.


pages: 242 words: 71,943

Strong Towns: A Bottom-Up Revolution to Rebuild American Prosperity by Charles L. Marohn, Jr.

2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, A Pattern Language, American Society of Civil Engineers: Report Card, anti-fragile, bank run, big-box store, Black Swan, bread and circuses, Bretton Woods, British Empire, business cycle, call centre, cognitive dissonance, complexity theory, corporate governance, Detroit bankruptcy, Donald Trump, en.wikipedia.org, facts on the ground, Ferguson, Missouri, gentrification, global reserve currency, high-speed rail, housing crisis, index fund, it is difficult to get a man to understand something, when his salary depends on his not understanding it, Jane Jacobs, Jeff Bezos, low interest rates, low skilled workers, mass immigration, megaproject, Modern Monetary Theory, mortgage debt, Network effects, new economy, New Urbanism, paradox of thrift, Paul Samuelson, pensions crisis, Ponzi scheme, quantitative easing, reserve currency, restrictive zoning, Savings and loan crisis, the built environment, The Death and Life of Great American Cities, trickle-down economics, Upton Sinclair, urban planning, urban renewal, walkable city, white flight, women in the workforce, yield curve, zero-sum game

Notes 1 https://www.peakprosperity.com/ 2 James Howard Kunstler, The Long Emergency (New York: Grove/Atlantic, 2005). 3 Steve Mouzon, The Original Green: Unlocking the Mystery of True Sustainability (New Urban Guild Foundation, 2010). 4 https://www.strongtowns.org/journal/2014/8/25/stroad-nation.html. 5 Alan Ehrenhalt, The Great Inversion and the Future of the American City (New York: Vintage Books, 2012). 6 https://www.brookings.edu/testimonies/the-changing-geography-of-us- poverty/. 7 Nassim Nicholas Taleb, The Black Swan (New York: Random House, 2007). 8 Nassim Nicholas Taleb, Antifragile (New York: Random House, 2012). 9 https://www.nytimes.com/2011/06/05/opinion/05friedman.html. 7 Productive Places A few blocks from my home there is a restaurant with several historic photos hanging on the wall. I’ve seen them many times but had never stopped to look closely at them, until one day I was waiting for a table and my eyes lingered on a photo of a circus parade passing through a historic downtown.

It’s not survival of the fittest – a phrase often misattributed to Charles Darwin – but rather, survival of the most adaptable. The fittest in one time and place may be at a fatal disadvantage in another. It’s those who can survive in both that have the opportunity to flourish. Author of The Black Swan, Nassim Taleb, in a 2013 speech at Loyola College titled “How to Live in a World We Don’t Understand,” explained how humans have reacted to abundance – to a lack of constraints – by exercising more control over their environment, repeatedly solving the immediate problem at the expense of our overall stability.

After all, this is how Americans have operated for the past three generations (and, arguably, humans prior would have acted if given the same means for transforming their habitat). Wall Street trader turned author and philosopher Nassim Taleb suggests that there are confident ways to live in a world you don’t fully understand. They begin with acknowledging the limits of our capacity to predict the future. From his book The Black Swan: If you know all possible conditions of a physical system you can, in theory, project its behavior into the future. But this only concerns inanimate objects. It is another matter to project a future when humans are involved, if you consider them living beings and endowed with free will.


pages: 576 words: 105,655

Austerity: The History of a Dangerous Idea by Mark Blyth

"there is no alternative" (TINA), accounting loophole / creative accounting, Alan Greenspan, balance sheet recession, bank run, banking crisis, Bear Stearns, Black Swan, book value, Bretton Woods, business cycle, buy and hold, capital controls, Carmen Reinhart, Celtic Tiger, central bank independence, centre right, collateralized debt obligation, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, debt deflation, deindustrialization, disintermediation, diversification, en.wikipedia.org, ending welfare as we know it, Eugene Fama: efficient market hypothesis, eurozone crisis, financial engineering, financial repression, fixed income, floating exchange rates, Fractional reserve banking, full employment, German hyperinflation, Gini coefficient, global reserve currency, Greenspan put, Growth in a Time of Debt, high-speed rail, Hyman Minsky, income inequality, information asymmetry, interest rate swap, invisible hand, Irish property bubble, Joseph Schumpeter, Kenneth Rogoff, liberal capitalism, liquidationism / Banker’s doctrine / the Treasury view, Long Term Capital Management, low interest rates, market bubble, market clearing, Martin Wolf, Minsky moment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, Occupy movement, offshore financial centre, paradox of thrift, Philip Mirowski, Phillips curve, Post-Keynesian economics, price stability, quantitative easing, rent-seeking, reserve currency, road to serfdom, Robert Solow, savings glut, short selling, structural adjustment programs, tail risk, The Great Moderation, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, Tobin tax, too big to fail, Two Sigma, unorthodox policies, value at risk, Washington Consensus, zero-sum game

To return to the height example, just because your model estimates that an eight-foot-tall person does not exist, it doesn’t follow that she doesn’t actually exist and that you will not run into her. In Taleb’s example, all swans were white until Europeans went to Australia and found black swans. Their exhaustive, multiyear, multisite sample of all known swans had convinced Europeans that all swans were white—until they were not. Nothing in their prior sample, no matter how complete it was, could have told them that a black swan was coming. How, then, do you hedge against risks that are not in your sample? How can you know that which is unknowable until it happens?

Use options (the right to buy or sell an asset at a predetermined price) to increase leverage (amplify the bet) while taking a short position as cover. But if this is all it takes to be safe, and to perhaps even make money, why did the banks not see the crisis coming? To answer that question, you need to turn to the trader-turned-philosopher Nassim Nicolas Taleb. Taleb’s Black Swans and Fat-Tailed Worlds A common refrain when the crisis first hit was that no one could have seen it coming. It was the financial equivalent of the meteor that wiped out the dinosaurs. All the diversification and hedging strategies that were supposed to keep banks from blowing up were, as David Viniar, the chief financial officer of Goldman Sachs put it, blindsided by “25 standard deviation moves, several days in a row.”24 This is similar to the “ten sigma event” claim reportedly made by John Meriweather when his hedge fund, Long Term Capital Management (LTCM), blew up in 1998.25 What these sigmas refer to is the number of standard deviations from the mean of a probability distribution at which an outcome will, probabilistically speaking, occur, with each higher sigma (number) being increasingly less likely than the last.

Your VaR number, once calculated, would reflect this. Nassim Taleb never bought into this line of thinking. He had been a critic of VaR models as far back as 1997, arguing that they systematically underestimated the probability of high-impact, low-probability events. He argued that the thin tails of the Gaussian worked for height but not for finance, where the tails were “fat.” The probabilities associated with fat tails do not get exponentially smaller, so outlier events are much more frequent than your model allows you to imagine. This is why ten-sigma events actually happen nine years apart. Taleb’s 2006 book The Black Swan, published before the crisis, turned these criticisms of VaR into a full-blown attack on the way banks and governments think about risk.


pages: 300 words: 77,787

Investing Demystified: How to Invest Without Speculation and Sleepless Nights by Lars Kroijer

Andrei Shleifer, asset allocation, asset-backed security, Bernie Madoff, bitcoin, Black Swan, BRICs, Carmen Reinhart, clean tech, compound rate of return, credit crunch, currency risk, diversification, diversified portfolio, equity premium, equity risk premium, estate planning, fixed income, high net worth, implied volatility, index fund, intangible asset, invisible hand, John Bogle, Kenneth Rogoff, low interest rates, market bubble, money market fund, passive investing, pattern recognition, prediction markets, risk tolerance, risk/return, Robert Shiller, selection bias, sovereign wealth fund, too big to fail, transaction costs, Vanguard fund, yield curve, zero-coupon bond

Make sure it is worth it. 1 www.telegraph.co.uk/finance/personalfinance/pensions/ 9407283/Fees-that-canhalve-the-value-of-your-pension.html 2 For UK specific thoughts on financial planning and pensions I recommend Jonquil Lowe’s Be Your Own Financial Adviser (Pearson Education, 2010). 3 I used a couple including one from University of Pennsylvania: wharton.upenn.edu/mortality/perl/CalcForm chapter 16 * * * Apocalypse investing Not long before the financial crash of 2008 a book called The Black Swan – The Impact of the Highly Improbable (Penguin, 2008) written by Nassim Nicholas Taleb was published. The book caused quite a stir in the financial community. The title of the book refers to the common assumption that swans are white. Swans had always been white and it had almost become part of the definition of being a swan, that it is a beautiful, graceful, white bird. The swan-watching community (if there is such a thing) was aghast and confused when a black swan appeared out of nowhere. All that it took for granted was thrown to the wind if such a fundamental assumption as the swan’s colour could be shattered in an instant.

This should involve very generic things such as ‘how likely are you to lose 25% of your investment?’ with thorough explanations of how this likelihood can change. There should be more in-depth sections with more technical or mathematical calculations for those who want it, along with discussions of the Black Swan theory of Taleb’s books (see Chapter 16). I don’t think there is enough of this kind of information available for investors today. This risk section could be tailored by incorporating information given by the investor. The more information you as the investor are willing to share, the more detailed analysis you would get back.

Index accountants active managers compared with index trackers, 2nd performance over time active personal portfolio management adding up the costs of advisory charges age life stages of financial planning and risk profile AIG allocations see investment allocations alternative investments alternative weightings ‘angel’ investing, 2nd annuities IRR (internal rate of return), 2nd apocalypse investing avoiding fraud and financial disasters and gold as security assets asset classes to avoid concentration risk customisation and noninvestment growth of, and overpayment of fees and institutional investors intangible and liabilities and portfolio theory in the rational portfolio, assets split tangible see also minimal risk assets avoiding fraud banks bailouts cash deposits with and financial disaster and gold as security and property investment Barclays US High Yield index Bernstein, William The Intelligent Asset Allocator bid/offer spread black swan events, 2nd, 3rd Bogle, John bonds bond indices, 2nd dollar domination of ETFs, 2nd and financial planning income from coupon payments indices and the rational portfolio adding other bonds to risk preferences, 2nd rebalancing your portfolio ‘risky’ bonds and liquidity shortterm, 2nd see also corporate bonds; government bonds; minimal risk assets Brazil government bonds broad-based portfolios and liquidity world equities, 2nd, 3rd, 4th, 5th Buffett, Warren, 2nd fee structure capital gains tax (CGT), 2nd, 3rd and gifts car insurance Case-Shiller House Price index, 2nd cash deposits deposit insurance government guarantees risk of CGT see capital gains tax (CGT) civil unrest collectibles commercial property market commodities, 2nd returns form company shares comparison sites, 2nd enhanced independent Contagion (film) corporate bonds adding to minimal risk assets, 2nd, 3rd and financial planning and credit quality ETFs, 2nd and financial planning liquidity of and minimal risk assets and portfolio theory, 2nd and the rational portfolio, 2nd, 3rd adjusting allocations, 2nd risk preferences real return expectations world corporate debt yields, 2nd costs see fees and expenses CRB Commodity index CRB Total Return index, 2nd credit ratings government bonds, 2nd, 3rd, 4th adding to minimal risk assets currency and government bonds, 2nd, 3rd, 4th matching and world equities currency-hedged investment products custody charges customisation Cyprus defined benefits pension schemes defined contribution pension schemes diversification and assets benefits of and corporate bonds, 2nd and equity market risk geographical and government bonds, 2nd and the rational portfolio, 2nd and world equities, 2nd Dow Jones index Industrial Average recovery from losses drop dead allocation early savers edge over the markets see investment edge efficiency frontiers EIS (Enterprise Investment Schemes) Elton, Edwin Modern Portfolio Theory and Investment Analysis emerging market companies listed on Western exchanges Enterprise Investment Schemes (EIS) equities and government and corporate bonds performance and portfolio theory and property investment and the rational portfolio allocations risk preferences, 2nd rebalancing your portfolio risk of diversification and false sense of security recovering from large losses standard deviation, 2nd, 3rd view that markets will always bounce back see also world equities equity risk premium and financial planning ETFs (exchange traded funds), 2nd, 3rd, 4th advantages to owning buying bonds, 2nd, 3rd commodity trading customisation fees and expenses in global property and gold trading implementing and index funds leveraged maturities and minimal risk bonds, 2nd physical or synthetic rebalancing your portfolio and taxes total expense ratio (TER) tracking errors European Union bonds, 2nd expenses see fees and expenses fat tails fees and expenses, 2nd adding up costs alternative investments benefits of paying lower fees and comparison websites financial advisers index trackers compared with active managers and investment edge pension plans and performance impact over time mutual funds, 2nd and the rational investor and the rational portfolio, 2nd rebalancing your portfolio Ferri, Richard All About Asset Allocation financial advisers, 2nd and comparison websites financial crisis 2008–09 and commodities trading and currency matching and government bonds yields and high risk preferences and liquidity and longterm financial planning, 2nd and market risk, 2nd, 3rd, 4th financial planning building your savings and the financial crisis 2008–09, 2nd and investment allocations, 2nd, 3rd and life stages and risk, 2nd risk surveys rules of thumb to consider supercautious savers financial software packages France government bonds fraud, avoiding frequent trading FTSE All-Share index FTSE All-Share Tracker fund FTSE NAREIT Global index, 2nd, 3rd fund pickers future performance mutual funds GDP and corporate bonds and world equity market value, 2nd Germany government bonds gifts and capital gains tax gold, 2nd as security Goldman Sachs government bonds adding to minimal risk assets, 2nd and financial planning and bank deposits banks and government defaults buying in base currency, 2nd credit ratings, 2nd, 3rd, 4th and diversification earnings ETFs, 2nd and the financial crisis (2008) and financial planning inflationprotected liquidity of longerterm maturity minimal risk and world equities, 2nd, 3rd and portfolio theory, 2nd, 3rd and the rational portfolio, 2nd, 3rd adjusting, 2nd, 3rd allocations, 2nd risk preferences real return expectations time horizons yields Greece government debt and bond yields hedge funds, 2nd, 3rd, 4th Japanese government bonds and liquidity high risk preferences home markets overinvestment in Icelandic banks income tax index funds, 2nd and ETFs and government bonds implementing maturities and minimal risk bonds, 2nd total expense ratio (TER) tracking errors index-tracking products, 2nd and active managers adding bonds to a portfolio compared with active managers, 2nd comparison sites, 2nd enhanced independent costs of fund changes and taxes future product development implementing license fees for and liquidity and mutual funds and the rational portfolio, 2nd, 3rd different risk preferences total expense ratio (TER), 2nd versus mutual fund returns over time world equities, 2nd see also ETFs (exchange traded funds); index funds India government bonds inflation earnings from minimal risk bonds inflation-adjusted government bonds inflation-protected bonds returns on world equities information/research costs institutional investors insurance buying deposit insurance schemes intangible assets interest rates cash deposits in banks government bonds, 2nd international investment investment allocations adding other government and corporate bonds and financial planning, 2nd, 3rd flexibility of financial goals life stages rebalancing your portfolio, 2nd investment edge, 2nd absence of, 2nd adding up the costs asset classes to avoid and commodities trading, 2nd and the competition different ways of having and expenses and performance picking your moment and private investments and the rational portfolio reconsidering your edge and world equities ‘invisible hand’ of the market IOUs (promissory notes) IRR (internal rate of return) annuities, 2nd iShares, 2nd Ishikawa, Tets How I Caused the Credit Crunch Japan commodities trading government bonds Nikkei index jewellery leverage ETFs and mortgages portfolios liabilities and the rational portfolio life insurance, 2nd life stages and financial planning liquidity equity portfolio and ‘risky’ bonds and ETFs minimal risk and private investments and the rational portfolio, 2nd, 3rd returns on illiquid investments selling your investment, 2nd localised risks avoiding and noninvestment assets Madoff, Bernie market capitalisation and world equities, 2nd market efficiency and inefficiency Mexico government bonds Microsoft investors, 2nd, 3rd and liquidity, 2nd mid-life savers minimal risk assets, 2nd adding other bonds to corporate bonds, 2nd, 3rd government bonds, 2nd adjusting the risk profile asset classes to avoid buying and diversification and equity markets ETFs and financial planning 50/50 split with world equities, 2nd, 3rd allocations government bonds earnings inflation-protected time horizons of inflationprotected bonds and liquidity as optimal portfolio and portfolio theory, 2nd in the rational portfolio, 2nd, 3rd, 4th, 5th, 6th real return expectations and world equities, 2nd Morgan Stanley mortgages and currency matching and leverage MSCI World Index, 2nd, 3rd, 4th mutual funds fees and performance, 2nd and index trackers national economies and equity market risk OEICs (openended investment companies) oil trading, 2nd optimal portfolio theory minimal risk asset past performance and future performance Paulson, John pension funds, 2nd, 3rd benefits and charges defined benefits schemes underfunded performance and fees index trackers versus active managers versus mutual funds portfolio theory and government bonds optimal and the rational investor price impact private equity capital, 2nd private investments, 2nd and liquidity privatisations and world equities professional investment managers property market investments, 2nd avoiding and financial disasters institutional investors and liquidity and the rational portfolio US subprime housing markets, 2nd, 3rd rational investing, 2nd core of ongoing tasks of rational portfolio adding other bonds to adjusting allocations and equity risk return expectations asset classes to avoid assets and liabilities assets split checklist corporate bonds, 2nd diversification financial benefits of and financial disasters geographical diversification government bonds, 2nd, 3rd, 4th, 5th implementation incorporating other assets and investment edge key components of a and liquidity, 2nd, 3rd and pension plans and portfolio theory and risk preferences risk/return profile, 2nd, 3rd, 4th tailoring to specific needs and circumstances tax adjustments tax benefits of holding and tax efficiency, 2nd, 3rd, 4th world equities, 2nd, 3rd, 4th see also minimal risk assets rebalancing your portfolio ticket size REITs (Real Estate Investment Trusts) residential property market retirees investment allocation retirement annuities and financial planning risk cash deposits credit risk and corporate bonds of equity markets equity risk premium high risk preferences and longterm financial planning, 2nd and the optimised market and the rational portfolio, 2nd, 3rd asset split risk preferences risk expertise websites risk surveys risk/return profile equity markets and financial planning, 2nd, 3rd and long-term financial planning minimal risk assets adding government and corporate bonds to pension plans and portfolio theory and the rational portfolio, 2nd, 3rd, 4th, 5th rebalancing your portfolio world equities riskless investment choice, 2nd S&P 500 index and the CRB Commodity index Index Tracker Portfolio standard deviation stocks volatility savings ‘doing nothing’ with and long-term financial planning life stages SD see standard deviation (SD) selling investments and liquidity software packages Spain government bonds standard deviation (SD) building your savings and equity market risk, 2nd, 3rd synthetic ETFs Taleb, Nassim Nicholas The Black Swan, 2nd tangency points tangible assets tax efficient proxies tax wrappers, 2nd taxes, 2nd advisers or accountants questions to ask benefits of the rational portfolio capital gains tax (CGT), 2nd, 3rd, 4th creating trading lots and financial disaster and pension plans, 2nd rational portfolio adjustment realising losses against tax advice websites tax efficiency and the rational portfolio, 2nd, 3rd, 4th tax schemes tax-sheltered or optimised products transaction tax, 2nd technology-focused funds, 2nd TER (total expense ratio), 2nd This Time is Different: Eight Centuries of Financial Folly (Reinhart and Rogoff) total expense ratio (TER), 2nd transaction taxes, 2nd, 3rd transfer charges turnover costs unit trusts, 2nd United Kingdom bank deposits and credit guarantee equities government bonds credit rating earnings from sterling investors United States corporate bonds, 2nd Dow Jones index, 2nd equity market, 2nd risk, 2nd, 3rd and total expense ratio government bonds credit ratings dollar investors earnings from versus property investment sub-prime housing market, 2nd, 3rd Vanguard, 2nd, 3rd, 4th, 5th, 6th FTSE AllShare index venture capital, 2nd Virgin FTSE All-Share Tracker fund volatility and financial planning predicting future Waal, Edmund de The Hare with Amber Eyes world equities adjusting the rational portfolio alternative weightings defining diversification benefits, 2nd, 3rd ETFs expected returns and financial planning 50/50 split with minimal risk assets, 2nd, 3rd investment allocation and high risk preferences indices liquidity of market value and minimal risk assets, 2nd overweighing ‘home’ equities and portfolio theory and the rational portfolio, 2nd, 3rd, 4th allocations risk preferences real return expectations US market, 2nd ‘Investing Demystified delivers, with great clarity and lucidity, the best possible advice you can get when it comes to personal investments and financial planning.’


pages: 165 words: 50,798

Intertwingled: Information Changes Everything by Peter Morville

A Pattern Language, Airbnb, Albert Einstein, Arthur Eddington, augmented reality, Bernie Madoff, bike sharing, Black Swan, business process, Cass Sunstein, cognitive dissonance, collective bargaining, Computer Lib, disinformation, disruptive innovation, folksonomy, holacracy, index card, information retrieval, Internet of things, Isaac Newton, iterative process, Jane Jacobs, Jeff Hawkins, John Markoff, Kanban, Lean Startup, Lyft, messenger bag, minimum viable product, Mother of all demos, Nelson Mandela, Paul Graham, peer-to-peer, Project Xanadu, quantum entanglement, RFID, Richard Thaler, ride hailing / ride sharing, Schrödinger's Cat, self-driving car, semantic web, sharing economy, Silicon Valley, Silicon Valley startup, single source of truth, source of truth, Steve Jobs, Stewart Brand, systems thinking, Ted Nelson, the Cathedral and the Bazaar, The Death and Life of Great American Cities, the scientific method, The Wisdom of Crowds, theory of mind, uber lyft, urban planning, urban sprawl, Vannevar Bush, vertical integration, zero-sum game

lviii Why Dolphins Make Us Nervous by Robert Krulwich (2013). lix Nonhuman Rights Project, http://www.nonhumanrights.org. lx Your Body Is Younger Than You Think by Nicholas Wade. lxi What is the Function of the Claustrum? by Francis Crick, Christof Koch (2005). lxii A “black swan” is a pivotal event that’s hard to predict or imagine in advance. Nassim Taleb popularized the term in his book, The Black Swan (2007). lxiii Soon Love Soon by Vienna Teng. lxiv Cataloging the World by Alex Wright (2014). lxv As We May Think by Vannevar Bush (1945). lxvi Project Xanadu by Ted Nelson, http://www.xanadu.com. lxvii A Research Center for Augmenting Human Intellect by Doug Englebart (1968).

lxix The Design of Browsing and Berrypicking Techniques by Marcia J. Bates (1989). lxx Information Foraging by Peter Pirolli and Stuart Card (1995). lxxi Service Design by Andy Polaine, Lavrans Lovlie, and Ben Reason (2013), p.86. lxxii On the Drucker Legacy by Robert Klitgaard (2006). lxxiii The Black Swan by Nicholas Nassim Taleb (2007), p.40. lxxiv On Intelligence by Jeff Hawkins (2004), p.87. lxxv The Tell-Tale Brain by V. S. Ramachandran (2011), p.55. lxxvi Hawkins (2004), p.89. lxxvii Teaching Smart People How to Learn by Chris Argyris (1991). lxxviii Models of My Life by Herbert Simon (1991), p.xvii.

And we use tools and language to spread the load across mind-body-environment. Despite these devices, our search for the truth is limited by a very small flashlight. So we must spin our categories like tetrominos. We must turn our ontologies downside-in and upside-out. We must seek monsters and cyborgs in the borderlands, and be mindful to watch for “black swans.”lxii We can’t make change unless we’re playful, since learning means letting go. E.M. Forster wrote “the song of the future must transcend creed” and asked “how can I know what I think till I see what I say?” There’s wisdom in those words, but to stare at the finger is to miss the moon. In the beginning was yathā bhūta, reality as-it-is, unmediated by concepts or classification or culture.


pages: 531 words: 125,069

The Coddling of the American Mind: How Good Intentions and Bad Ideas Are Setting Up a Generation for Failure by Greg Lukianoff, Jonathan Haidt

AltaVista, Bernie Sanders, bitcoin, Black Lives Matter, Black Swan, Cambridge Analytica, cognitive dissonance, correlation does not imply causation, demographic transition, Donald Trump, fake news, Ferguson, Missouri, Filter Bubble, helicopter parent, Herbert Marcuse, hygiene hypothesis, income inequality, Internet Archive, Isaac Newton, low skilled workers, Mahatma Gandhi, mass immigration, mass incarceration, means of production, microaggression, moral panic, Nelson Mandela, Ralph Nader, risk tolerance, Silicon Valley, Snapchat, Social Justice Warrior, Steven Pinker, TED Talk, The Bell Curve by Richard Herrnstein and Charles Murray, traumatic brain injury, Unsafe at Any Speed, Wayback Machine

Antifragility No one has done a better job of explaining the harm of avoiding stressors, risks, and small doses of pain than Nassim Nicholas Taleb, the Lebanese-born statistician, stock trader, and polymath who is now a professor of risk engineering at New York University. In his 2007 best seller, The Black Swan, Taleb argued that most of us think about risk in the wrong way. In complex systems, it is virtually inevitable that unforeseen problems will arise, yet we persist in trying to calculate risk based on past experiences. Life has a way of creating completely unexpected events—events Taleb likens to the appearance of a black swan when, based on your past experience, you assumed that all swans were white. (Taleb was one of the few who predicted the global financial crisis of 2008, based on the financial system’s vulnerability to “black swan” events.)

(Taleb was one of the few who predicted the global financial crisis of 2008, based on the financial system’s vulnerability to “black swan” events.) In his later book Antifragile, Taleb explains how systems and people can survive the inevitable black swans of life and, like the immune system, grow stronger in response. Taleb asks us to distinguish three kinds of things. Some, like china teacups, are fragile: they break easily and cannot heal themselves, so you must handle them gently and keep them away from toddlers. Other things are resilient: they can withstand shocks. Parents usually give their toddlers plastic cups precisely because plastic can survive repeated falls to the floor, although the cups do not benefit from such falls.

., & Esquilin, M. (2007). Racial microaggressions in everyday life: Implications for clinical practice. American Psychologist, 62(4), 271–286. Tajfel, H. (1970). Experiments in intergroup discrimination. Scientific American, 223(5), 96–102. Taleb, N. N. (2007). The black swan: The impact of the highly improbable. New York, NY: Random House. Taleb, N. N. (2012). Antifragile: Things that gain from disorder. New York, NY: Random House. Tetlock, P. E., Kristel, O. V., Elson, B., Green, M., & Lerner, J. (2000). The psychology of the unthinkable: Taboo trade-offs, forbidden base rates, and heretical counterfactuals.


pages: 741 words: 179,454

Extreme Money: Masters of the Universe and the Cult of Risk by Satyajit Das

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", "there is no alternative" (TINA), "World Economic Forum" Davos, affirmative action, Alan Greenspan, Albert Einstein, algorithmic trading, Andy Kessler, AOL-Time Warner, Asian financial crisis, asset allocation, asset-backed security, bank run, banking crisis, banks create money, Basel III, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, bonus culture, book value, Bretton Woods, BRICs, British Empire, business cycle, buy the rumour, sell the news, capital asset pricing model, carbon credits, Carl Icahn, Carmen Reinhart, carried interest, Celtic Tiger, clean water, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, Daniel Kahneman / Amos Tversky, deal flow, debt deflation, Deng Xiaoping, deskilling, discrete time, diversification, diversified portfolio, Doomsday Clock, Dr. Strangelove, Dutch auction, Edward Thorp, Emanuel Derman, en.wikipedia.org, Eugene Fama: efficient market hypothesis, eurozone crisis, Everybody Ought to Be Rich, Fall of the Berlin Wall, financial engineering, financial independence, financial innovation, financial thriller, fixed income, foreign exchange controls, full employment, Glass-Steagall Act, global reserve currency, Goldman Sachs: Vampire Squid, Goodhart's law, Gordon Gekko, greed is good, Greenspan put, happiness index / gross national happiness, haute cuisine, Herman Kahn, high net worth, Hyman Minsky, index fund, information asymmetry, interest rate swap, invention of the wheel, invisible hand, Isaac Newton, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", job automation, Johann Wolfgang von Goethe, John Bogle, John Meriwether, joint-stock company, Jones Act, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kevin Kelly, laissez-faire capitalism, load shedding, locking in a profit, Long Term Capital Management, Louis Bachelier, low interest rates, margin call, market bubble, market fundamentalism, Market Wizards by Jack D. Schwager, Marshall McLuhan, Martin Wolf, mega-rich, merger arbitrage, Michael Milken, Mikhail Gorbachev, Milgram experiment, military-industrial complex, Minsky moment, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, mortgage tax deduction, mutually assured destruction, Myron Scholes, Naomi Klein, National Debt Clock, negative equity, NetJets, Network effects, new economy, Nick Leeson, Nixon shock, Northern Rock, nuclear winter, oil shock, Own Your Own Home, Paul Samuelson, pets.com, Philip Mirowski, Phillips curve, planned obsolescence, plutocrats, Ponzi scheme, price anchoring, price stability, profit maximization, proprietary trading, public intellectual, quantitative easing, quantitative trading / quantitative finance, Ralph Nader, RAND corporation, random walk, Ray Kurzweil, regulatory arbitrage, Reminiscences of a Stock Operator, rent control, rent-seeking, reserve currency, Richard Feynman, Richard Thaler, Right to Buy, risk free rate, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, Rod Stewart played at Stephen Schwarzman birthday party, rolodex, Ronald Reagan, Ronald Reagan: Tear down this wall, Satyajit Das, savings glut, shareholder value, Sharpe ratio, short selling, short squeeze, Silicon Valley, six sigma, Slavoj Žižek, South Sea Bubble, special economic zone, statistical model, Stephen Hawking, Steve Jobs, stock buybacks, survivorship bias, tail risk, Teledyne, The Chicago School, The Great Moderation, the market place, the medium is the message, The Myth of the Rational Market, The Nature of the Firm, the new new thing, The Predators' Ball, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, trickle-down economics, Turing test, two and twenty, Upton Sinclair, value at risk, Yogi Berra, zero-coupon bond, zero-sum game

Fêted as a rock star at Davos, the black swan thesis of Nassim Taleb attracts attention. The crisis may be a black swan (an unknown unknown), white swan (a known unknown) or gray (all of the above) swan. Taleb combatively attacks the charlatans—anyone who does not agree with him. Economists and statisticians do not react well to being labeled pseudo-scientists of financial risk who disguised their incompetence behind maths. In August 2007, the imbeciles, knaves, and fools (Taleb’s descriptions) devoted an entire issue of The American Statistician to the black swan hypothesis. On the Charlie Rose Show, Taleb dismisses all criticism as ad hominen, a logical fallacy that the validity of a premise is linked to the advocating person.

Doom, Nouriel Roubini, together with the former derivative trader, financial philosopher, and best-selling author known variously as Nassim Taleb, Nicholas Nassim Taleb, NNT, or simply the Black Swan (his best-known work). Bill Griffeth, the interviewer, and his co-host Michelle Caruso-Cabrera, started off upbeat: “What would it take to make you bearish on this economy right now?” Dr. Doom summarized the position: “It’s ugly!” Dr. Doom’s prophecy that the current recession was likely to be three times as long and three times as deep as previous recent recessions did not please Griffeth: “But that’s not the end of the world, is it?” The Black Swan was gloomy: “We have the same people in charge, those who did not see the crisis coming.”

The mathematician Benoit Mandelbrot demonstrated that normal distributions do not exist in practice. In Fooled by Randomness and Black Swan, Nicholas Nassim Taleb argued against the application of statistical methods in finance, especially the normal distribution curve to measure risk. Taleb drew on John Stuart Mill, himself rephrasing a problem posed by Scottish philosopher David Hume: “no amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion.” Unpredictable extremes of price movement, known as fat tails, were more common than theory implied.


pages: 444 words: 151,136

Endless Money: The Moral Hazards of Socialism by William Baker, Addison Wiggin

Alan Greenspan, Andy Kessler, asset allocation, backtesting, bank run, banking crisis, Bear Stearns, Berlin Wall, Bernie Madoff, Black Swan, bond market vigilante , book value, Branko Milanovic, bread and circuses, break the buck, Bretton Woods, BRICs, business climate, business cycle, capital asset pricing model, carbon tax, commoditize, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crony capitalism, cuban missile crisis, currency manipulation / currency intervention, debt deflation, Elliott wave, en.wikipedia.org, Fall of the Berlin Wall, feminist movement, fiat currency, fixed income, floating exchange rates, foreign exchange controls, Fractional reserve banking, full employment, German hyperinflation, Great Leap Forward, housing crisis, income inequality, index fund, inflation targeting, Joseph Schumpeter, Kickstarter, laissez-faire capitalism, land bank, land reform, liquidity trap, Long Term Capital Management, lost cosmonauts, low interest rates, McMansion, mega-rich, military-industrial complex, Money creation, money market fund, moral hazard, mortgage tax deduction, naked short selling, negative equity, offshore financial centre, Ponzi scheme, price stability, proprietary trading, pushing on a string, quantitative easing, RAND corporation, rent control, rent stabilization, reserve currency, risk free rate, riskless arbitrage, Ronald Reagan, Savings and loan crisis, school vouchers, seigniorage, short selling, Silicon Valley, six sigma, statistical arbitrage, statistical model, Steve Jobs, stocks for the long run, Tax Reform Act of 1986, The Great Moderation, the scientific method, time value of money, too big to fail, Two Sigma, upwardly mobile, War on Poverty, Yogi Berra, young professional

But there are also unknown unknowns. There are things we do not know we don’t know. Donald Rumsfeld, statement from Defense Department briefing, 200210 In his bestseller, The Black Swan, the financial commentator Nassim Taleb claims that investors and economists err in understanding the direction of markets because they underestimate what they do not know, a concept he names “tunneling.” (Before the sighting of a black swan in Australia, all swans were believed to be white.) Taleb tells the story of visitors to the medievalist and philosopher Umberto Eco’s library of 30,000 books: Most compliment his knowledge by asking in amazement how many has he read; others understand that his wisdom comes from his habit of turning to the large number of unread books at his disposal for reference.

By 1928, Kemmerer had spread the gold-exchange standard across the globe to 50 nations.7 Morgan rose to influence in an era when the accumulation of great wealth began to astound the ordinary man. As Nassim Nicholas Taleb observed in his book, The Black Swan, life is unfair, a theme the economist Sherwin Rosen, author of studies about the economics of superstars, develops as credited by Taleb. Rosen bemoans the high salaries of basketball stars and TV personalities, which he attributes to the “tournament effect,” wherein someone who is marginally better can win the whole pot, leaving others with nothing. Taleb reminds us how this is so: We would rather buy a recording featuring the renowned Vladimir Horowitz for $10.99 than pay $9.99 for one of a struggling pianist.

Harry Marcopolos, The World’s Largest Hedge Fund is a Fraud, November 7, 2005. Copies circulate on various Internet sites, including http://www. berniemadoffsec.com/the-worlds-largest-hedge-fund-is-a-fraud.html. 13. Nassim Nicholas Taleb, The Black Swan:The Impact of the Highly Improbable (New York: Random House, 2007), 229–252. A sprightly discussion of this is in The Black Swan’s Chapter 15: “The Bell Curve, That Great Intellectual Fraud.” Notes 383 14. Zillow, The Majority of U.S. Homeowners Thinks Their Home is Insulated From the Housing Crisis (August 6, 2008), http://zillow.mediaroom.com/index. php?


pages: 453 words: 111,010

Licence to be Bad by Jonathan Aldred

"Friedman doctrine" OR "shareholder theory", Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, availability heuristic, Ayatollah Khomeini, behavioural economics, Benoit Mandelbrot, Berlin Wall, Black Monday: stock market crash in 1987, Black Swan, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Cass Sunstein, Charles Babbage, clean water, cognitive dissonance, corporate governance, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, Donald Trump, Douglas Engelbart, Douglas Engelbart, Dr. Strangelove, Edward Snowden, fake news, Fall of the Berlin Wall, falling living standards, feminist movement, framing effect, Frederick Winslow Taylor, From Mathematics to the Technologies of Life and Death, full employment, Gary Kildall, George Akerlof, glass ceiling, Glass-Steagall Act, Herman Kahn, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, Jeff Bezos, John Nash: game theory, John von Neumann, Linda problem, Long Term Capital Management, Louis Bachelier, mandelbrot fractal, meta-analysis, Mont Pelerin Society, mutually assured destruction, Myron Scholes, Nash equilibrium, Norbert Wiener, nudge unit, obamacare, offshore financial centre, Pareto efficiency, Paul Samuelson, plutocrats, positional goods, power law, precautionary principle, profit maximization, profit motive, race to the bottom, RAND corporation, rent-seeking, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, scientific management, Skinner box, Skype, Social Responsibility of Business Is to Increase Its Profits, spectrum auction, The Nature of the Firm, The Wealth of Nations by Adam Smith, Tragedy of the Commons, transaction costs, trickle-down economics, Vilfredo Pareto, wealth creators, zero-sum game

Standard deviation is a measure of distance from the average, the middle of the bell; 25-standard deviation events are very far away from this, and so should happen less than once in the history of the universe. Events with extreme impacts, which happen completely unexpectedly (although they may seem predictable with hindsight), have been named Black Swans by Nassim Taleb, a Lebanese mathematician and sometime hedge-fund manager. Bell-curve thinking essentially assumes that the possibility of black swans can be ignored, because they will never happen. Goldman Sachs was not alone in using bell-curve thinking. This orthodoxy dominates the financial sector and has repeatedly been approved by regulators as a basis for judging risks.

Strings Attached. Princeton, Princeton University Press. 8. TRUST IN NUMBERS Entertaining and insightful on the ideas behind the global financial crisis: Lanchester, J. (2010). Whoops! London, Penguin. Sprawling but unmissable, and influential, on the flaws in bell-curve thinking: Taleb, N. (2010). The Black Swan. London, Penguin. 9. YOU DESERVE WHAT YOU GET On the rise of the Laffer curve and, more generally, the political/cultural shift towards markets in the US: Rodgers, D. (2011). Age of Fracture. Harvard, Harvard University Press. There are several excellent books on inequality, but few combine accessibility, insight and encyclopaedic knowledge as well as: Atkinson, A. (2015).

M. (1937), ‘The General Theory’, Quarterly Journal of Economics, 51, 213–14. 6 Friedman, M., and Friedman, R. (1998), Two Lucky People (Chicago: University of Chicago Press), 146. 7 For this example and much more detail on the difference between bell-curve and scale-invariant phenomena see N. Taleb (2010), The Black Swan (London: Penguin), chapter 15. 8 BBC News, 15 September 2008: http://news.bbc.co.uk/1/hi/7616996.stm. Quoted in D. Orrell (2012), Economyths (London: Icon), 90. 9 Freedman D., and Stark, P. (2003), ‘What is the Chance of an Earthquake?’, Technical report 611, Department of Statistics, University of California, Berkeley.


Trend Commandments: Trading for Exceptional Returns by Michael W. Covel

Alan Greenspan, Albert Einstein, Alvin Toffler, behavioural economics, Bernie Madoff, Black Swan, business cycle, buy and hold, commodity trading advisor, correlation coefficient, delayed gratification, disinformation, diversified portfolio, en.wikipedia.org, Eugene Fama: efficient market hypothesis, family office, full employment, global macro, Jim Simons, Lao Tzu, Long Term Capital Management, managed futures, market bubble, market microstructure, Market Wizards by Jack D. Schwager, Mikhail Gorbachev, moral hazard, Myron Scholes, Nick Leeson, oil shock, Ponzi scheme, prediction markets, quantitative trading / quantitative finance, random walk, Reminiscences of a Stock Operator, Sharpe ratio, systematic trading, the scientific method, three-martini lunch, transaction costs, tulip mania, upwardly mobile, Y2K, zero-sum game

Market Wizards: Interviews with Top Traders. Columbia: Marketplace Books, 2006. Stridsman, Thomas. Trading Systems That Work: Building and Evaluating Effective Trading Systems. New York: McGraw Hill, 2001. Taleb, Nassim Nicholas. Fooled By Randomness: The Hidden Role of Chance in the Markets and in Life. New York: TEXERE, 2001. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: The Random House Publishing Group, 2007. Taleb, Nassim. The Bed of Procrustes: Philosophical and Practical Aphorisms. New York: Random House Publishing Group, 2010. Tharp, Van. Trade Your Way to Financial Freedom. New York: McGraw Hill, Inc., 2007.

That’s a major winner right there.3 My political science background allowed me to see that; others should be able to see it too. However, many look at events through the wrong lens. Deep down the money elite know that standard finance theory has no explanation for the winners of low-probability, high-impact events.4 The bottom line is that big, unexpected events make trend traders rich. They exploit Black Swan events (see Nassim Taleb’s book of the same name for more). 92 Tre n d C o m m a n d m e n t s What do I mean? When a major event occurs, such as the Russian debt default of August 1998, the terrorist attacks of September 11, 2001, or the 2002 and 2008 equity market crashes, events accelerate existing trends to even greater magnitudes.5 Unexpected events will never stop.

moments, 143-144 alpha in trend following, 137 Altis Partners, 5, 19 Apple Computer, 87 approval ratings, based on economy, 181-182 Aspect Capital, 5 average true range, defined, 13 averaging losses, avoiding, 79 benchmark comparisons, 105-106 Bernanke, Ben, 175-176 bet sizing, 61-62 beta, defined, 12 black box, trend following compared to, 187 Black Swan (Taleb), 91 Blankfein, Lloyd, 175 blind risk, 56 BlueCrest, 5 Borish, Peter, 143 B Bratt, Elmer Clark, 230 Bacon, Louis, 5, 15 bubbles Barclays CTA Index, 15 irrational behavior in, 25-26 Barings Bank collapse, 4 predicting, 153 Bartiromo, Maria, 174, 177 Buffett, Warren, 157-158, 189 batting statistics example, 138-139 Burnett, Erin, 42 Becker, Gary, 25 Bush, George W., 182 behaviors, leading to market losses, 117-120 Bush, George H.


pages: 227 words: 62,177

Numbers Rule Your World: The Hidden Influence of Probability and Statistics on Everything You Do by Kaiser Fung

Alan Greenspan, American Society of Civil Engineers: Report Card, Andrew Wiles, behavioural economics, Bernie Madoff, Black Swan, business cycle, call centre, correlation does not imply causation, cross-subsidies, Daniel Kahneman / Amos Tversky, edge city, Emanuel Derman, facts on the ground, financial engineering, fixed income, Gary Taubes, John Snow's cholera map, low interest rates, moral hazard, p-value, pattern recognition, profit motive, Report Card for America’s Infrastructure, statistical model, the scientific method, traveling salesman

This classic theory works well for automotive insurance but applies poorly to catastrophe insurance, as Tampa businessman Bill Poe painfully discovered. For auto insurers, the level of total claims is relatively stable from year to year, even though individual claims are dispersed over time. By contrast, catastrophe insurance is a “negative black swan” business, to follow Nassim Taleb’s terminology. In Taleb’s view, business managers can be lulled into ignoring certain extremely unlikely events (“black swans”) just because of the remote chance of occurrence, even though the rare events have the ability to destroy their businesses. Hurricane insurers hum along merrily, racking up healthy profits, until the big one ravages the Atlantic coast, something that has little chance of happening but wreaks extreme damage when it does happen.

By contrast, I bring out the key concepts underlying those techniques, such as variability, correlation, and stratification. With most books focused on exciting new theories, the work of applied scientists has suffered from general neglect. Freakonomics is a notable exception, covering the applied research of the economics professor Steven Levitt. Two books in the finance area also fit the bill: in The Black Swan, Nassim Taleb harangues theoreticians of financial mathematics (and other related fields) on their failure in statistical thinking, while in My Life as a Quant, Emanuel Derman offers many valuable lessons for financial engineers, the most important of which is that modelers in the social sciences—unlike physicists—should not seek the truth.

A mega-hurricane could cause $100 billion in losses—fifty to a hundred times higher than the damage from the normal storm. The classic theory of insurance, which invokes the bell curve, breaks down at this point because of extreme variability and severe spatial concentration of this risk. When the black swan appears, a large portion of customers makes claims simultaneously, overwhelming insurers. These firms might still be solvent on average—meaning that over the long run, their premiums would cover all claims—but the moment cash balances turn negative, they implode. Indeed, catastrophe insurers who fail to plan for the variability of claims invariably find themselves watching in horror as one ill wind razes their entire surplus.


Bulletproof Problem Solving by Charles Conn, Robert McLean

active transport: walking or cycling, Airbnb, Amazon Mechanical Turk, asset allocation, availability heuristic, Bayesian statistics, behavioural economics, Big Tech, Black Swan, blockchain, book value, business logic, business process, call centre, carbon footprint, cloud computing, correlation does not imply causation, Credit Default Swap, crowdsourcing, David Brooks, deep learning, Donald Trump, driverless car, drop ship, Elon Musk, endowment effect, fail fast, fake news, future of work, Garrett Hardin, Hyperloop, Innovator's Dilemma, inventory management, iterative process, loss aversion, megaproject, meta-analysis, Nate Silver, nudge unit, Occam's razor, pattern recognition, pets.com, prediction markets, principal–agent problem, RAND corporation, randomized controlled trial, risk tolerance, Silicon Valley, SimCity, smart contracts, stem cell, sunk-cost fallacy, the rule of 72, the scientific method, The Signal and the Noise by Nate Silver, time value of money, Tragedy of the Commons, transfer pricing, Vilfredo Pareto, walkable city, WikiLeaks

Which ones should you ramp up with resources and slow down or terminate based on your assessment? How else might you cleave the nursing supply problem? Would you cleave the airport capacity problem in a more compelling way than outlined in Chapter 1? Notes 1  Margaret Webb Pressler, “The Fall of the House of Hechinger,” Washington Post, July 21, 1997. 2  See Nassim N. Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007), for a deeply insightful discussion of probability and decision‐making errors. 3  Remedy DefinitionsContextualize/Placard: Leaves artifact in place, but tells the story of the actor's role in offensive acts. Balancing: Brings into the physical or digital space the voices/images of others, including those wronged, may include balancing restorative justice actions.

Tetlock and Dan Gardner, Superforecasting: The Art and Science of Prediction (Crown Publishing, 2015). 6  Caroline Webb, How to Have a Good Day (Random House, 2016), 167. 7  Caroline Webb, How to Have a Good Day (Random House, 2016), 170–172. 8  Philip E. Tetlock and Dan Gardner, Superforecasting: The Art and Science of Prediction (Crown Publishing, 2015). 9  Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (Random House, 2007). 10  Daniel Kahnemann, Dan Lovallo, and Olivier Sibony, “Before You Make That Big Decision,” Harvard Business Review, June 2011. Chapter Five Conduct Analyses How you go about gathering facts and conducting analysis to test your hypotheses often makes the difference between good and bad problem solving, even when the earlier steps have been followed carefully.

How would you take the root cause case of homeless women to the next stage of inquiry? What are the second‐ and third‐order questions to be asked? What analysis would you want to see undertaken before you felt comfortable with policies to address the issue? Notes 1  Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (Penguin, 2007). 2  Gerd Gigerenzer, Peter M. Todd, and the ABC Research Group, Simple Heuristics That Make Us Smart (Oxford University Press, 2000). 3  Report prepared for the United Kingdom's Department of International Development by The Nature Conservancy, WWF, and the University of Manchester, “Improving Hydropower Outcomes through System Scale Planning, An Example from Myanmar,” 2016. 4  Warren Buffett, “My Philanthropic Pledge,” Fortune, June 16, 2010. 5  Our friend Barry Nalebuff of Yale points out that the actual rule is 69.3, but is usually rounded up to 72 because it is easier to do the division in your head. 6  CB Insights, May 25, 2015, www.cbinsights.com. 7  Nate Silver, The Signal and the Noise (Penguin, 2012). 8  Dan Lovallo, Carmina Clarke, and Colin Camerer, “Robust Analogizing and the Outside View: Two Empirical Tests of Case Based Decision Making,” Strategic Management Journal 33, no. 5 (2012): 496–512. 9  “‘Chainsaw Al’ Axed,” CNN Money, June 15, 1998. 10  This problem was suggested by Barry Nalebuff of Yale University. 11  Nicklas Garemo, Stefan Matzinger, and Robert Palter, “Megaprojects: The Good, the Bad, and the Better,” McKinsey Quarterly, July 2015 (quoting Bent Flyvberg, Oxford Saïd Business School). 12  Daniel Kahneman, Dan Lovallo, and Olivier Sibony, “Before You Make that Big Decision,” Harvard Business Review, June 2011. 13  Gerd Gigerenzer, Peter M.


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Safe Haven: Investing for Financial Storms by Mark Spitznagel

Albert Einstein, Antoine Gombaud: Chevalier de Méré, asset allocation, behavioural economics, bitcoin, Black Swan, blockchain, book value, Brownian motion, Buckminster Fuller, cognitive dissonance, commodity trading advisor, cryptocurrency, Daniel Kahneman / Amos Tversky, data science, delayed gratification, diversification, diversified portfolio, Edward Thorp, fiat currency, financial engineering, Fractional reserve banking, global macro, Henri Poincaré, hindsight bias, Long Term Capital Management, Mark Spitznagel, Paul Samuelson, phenotype, probability theory / Blaise Pascal / Pierre de Fermat, quantitative trading / quantitative finance, random walk, rent-seeking, Richard Feynman, risk free rate, risk-adjusted returns, Schrödinger's Cat, Sharpe ratio, spice trade, Steve Jobs, tail risk, the scientific method, transaction costs, value at risk, yield curve, zero-sum game

My suggestion to follow the Greek Orthodox fast, where one is vegan two‐thirds of the year (and aggressively carnivore on the other third, mostly Sundays and holidays), failed to convince. It seemed too much of a compromise. He finds ways to furtively inflict his musical tastes on his coworkers (Mahler, mainly, with performances by von Karajan) and in the early days, as in a ritual, the conversations used to start and end with Karl Popper and central (Black Swan) asymmetries in the scientific method. There is this insistence that we are not in the business of trading, but partaking of an intellectual enterprise, that is, both applying proper inference and probability theory to the business world and, without any modesty, improving these fields according to feedback from markets.

As introduced (and formulated) in Safe Haven, risk mitigation needs to be “cost‐effective” (i.e., it should raise your wealth), and to do that it needs to mitigate the risks that matter, not the risks that don't. It was the birth of tail risk hedging as an investable asset class. Tail risk hedging removed the effect of the nasty Black Swan on portfolios; cost‐effective tail risk hedging obliterated all the other forms of risk mitigation. Accordingly, the idea grew on people and a new category was born. This led to a legion of imitators—those very same mutua muli persons who had previously been fooled by modern finance tools, finding a new thing to sell.

Of course, we may have mitigated the risk of a remote, extreme loss that never happened. And yet, such a remote loss could happen suddenly at any time, and our risk mitigation could thus raise our CAGR (relative to our position had we not used that mitigation). This is the problem of induction, where the arrival of just one black swan falsifies any claim that all swans are white. But when I say that cost‐effective risk mitigation raises a portfolio's CAGR over time, this also means over a sufficiently broad range of observable outcomes, which largely resolves these epistemological problems. (We will address this with what is known as a bootstrap in later chapters.)


pages: 250 words: 79,360

Escape From Model Land: How Mathematical Models Can Lead Us Astray and What We Can Do About It by Erica Thompson

Alan Greenspan, Bayesian statistics, behavioural economics, Big Tech, Black Swan, butterfly effect, carbon tax, coronavirus, correlation does not imply causation, COVID-19, data is the new oil, data science, decarbonisation, DeepMind, Donald Trump, Drosophila, Emanuel Derman, Financial Modelers Manifesto, fudge factor, germ theory of disease, global pandemic, hindcast, I will remember that I didn’t make the world, and it doesn’t satisfy my equations, implied volatility, Intergovernmental Panel on Climate Change (IPCC), John von Neumann, junk bonds, Kim Stanley Robinson, lockdown, Long Term Capital Management, moral hazard, mouse model, Myron Scholes, Nate Silver, Neal Stephenson, negative emissions, paperclip maximiser, precautionary principle, RAND corporation, random walk, risk tolerance, selection bias, self-driving car, social distancing, Stanford marshmallow experiment, statistical model, systematic bias, tacit knowledge, tail risk, TED Talk, The Great Moderation, The Great Resignation, the scientific method, too big to fail, trolley problem, value at risk, volatility smile, Y2K

In doing so, we have to recognise that absolute risk is inherently incalculable. Nassim Taleb gives the delightful example of a casino that can statistically calculate its business risk with high levels of confidence, but this risk is dwarfed by the combination of a tiger mauling a star performer, a contractor attempting to dynamite the casino, an employee failing to file documentation leading to a large fine, and a ransom payment being made for the casino owner’s kidnapped daughter. These unmodelled risks, labelled Black Swans by Taleb, are simply not predictable – although we can be pretty sure that something could occur.

.: Why Confusing Illusion with Reality Can Lead to Disaster, on Wall Street and in Life, Free Press, 2012 Frydman, Roman, and Michael Goldberg, Beyond Mechanical Markets, Princeton University Press, 2011 Haldane, Andrew, ‘The Dog and the Frisbee’, speech at Jackson Hole, Wyoming, 31 August 2012 Lowenstein, Roger, When Genius Failed: The Rise and Fall of Long Term Capital Management, Fourth Estate, 2002 MacKenzie, Donald, An Engine, Not a Camera: How Financial Models Shape Markets, MIT Press (Inside Technology Series), 2008 March, James, Lee Sproull and Michal Tamuz, ‘Learning from Samples of One or Fewer’, Organization Science, 2(1), 1991 Rebonato, Riccardo, Volatility and Correlation, John Wiley, 1999 Stiglitz, Joseph, ‘Where Modern Macroeconomics Went Wrong’, Oxford Review of Economic Policy, 34, 2018 Taleb, Nassim, The Black Swan: The Impact of the Highly Improbable, Random House, 2007 Wilmott, Paul, and David Orrell, The Money Formula: Dodgy Finance, Pseudo Science, and How Mathematicians Took Over the Markets, Wiley, 2017 ——, and Emanuel Derman, ‘The Financial Modelers’ Manifesto’, https://wilmott.com/financialmodelers-manifesto/, 2009 Chapter 8: The Atmosphere is Complicated Allen, Myles, Mustafa Babiker, Yang Chen, et al., ‘IPCC SR15: Summary for Policymakers’, in IPCC Special Report: Global Warming of 1.5C, Intergovernmental Panel on Climate Change, 2018 Anderson, Kevin, ‘Duality in Climate Science’, Nature Geoscience, 8(12), 2015 Beck, Silke, and Martin Mahony, ‘The Politics of Anticipation: The IPCC and the Negative Emissions Technologies Experience’, Global Sustainability, 1, 2018 Burke, Marshall, Solomon Hsiang and Edward Miguel, ‘Global Non-Linear Effect of Temperature on Economic Production’, Nature, 527(7577), 2015 Edwards, Paul, A Vast Machine: Computer Models, Climate Data, and the Politics of Global Warming, MIT Press, 2010 Hänsel, Martin C., Moritz A.

And yet they are not completely inaccessible: we can list these uncertainties, study them, quantitatively or qualitatively evaluate the likelihood of their occurrence, even take real-world steps to prevent them. Yes, there could be truly unexpected events – Black Swans – by which we might be blindsided. But the majority of surprising events are not really Black Swans. Some people saw the 2008 financial crisis coming. Pandemics have been at the top of national risk registers for decades. Climate tipping points are absolutely on the radar of mainstream scientific research. It’s not that we think these kinds of events can’t happen, it’s that we haven’t developed an effective way of dealing with or formalising our understanding that they could happen.


pages: 345 words: 75,660

Prediction Machines: The Simple Economics of Artificial Intelligence by Ajay Agrawal, Joshua Gans, Avi Goldfarb

Abraham Wald, Ada Lovelace, AI winter, Air France Flight 447, Airbus A320, algorithmic bias, AlphaGo, Amazon Picking Challenge, artificial general intelligence, autonomous vehicles, backpropagation, basic income, Bayesian statistics, Black Swan, blockchain, call centre, Capital in the Twenty-First Century by Thomas Piketty, Captain Sullenberger Hudson, carbon tax, Charles Babbage, classic study, collateralized debt obligation, computer age, creative destruction, Daniel Kahneman / Amos Tversky, data acquisition, data is the new oil, data science, deep learning, DeepMind, deskilling, disruptive innovation, driverless car, Elon Musk, en.wikipedia.org, Erik Brynjolfsson, everywhere but in the productivity statistics, financial engineering, fulfillment center, general purpose technology, Geoffrey Hinton, Google Glasses, high net worth, ImageNet competition, income inequality, information retrieval, inventory management, invisible hand, Jeff Hawkins, job automation, John Markoff, Joseph Schumpeter, Kevin Kelly, Lyft, Minecraft, Mitch Kapor, Moneyball by Michael Lewis explains big data, Nate Silver, new economy, Nick Bostrom, On the Economy of Machinery and Manufactures, OpenAI, paperclip maximiser, pattern recognition, performance metric, profit maximization, QWERTY keyboard, race to the bottom, randomized controlled trial, Ray Kurzweil, ride hailing / ride sharing, Robert Solow, Salesforce, Second Machine Age, self-driving car, shareholder value, Silicon Valley, statistical model, Stephen Hawking, Steve Jobs, Steve Jurvetson, Steven Levy, strong AI, The Future of Employment, the long tail, The Signal and the Noise by Nate Silver, Tim Cook: Apple, trolley problem, Turing test, Uber and Lyft, uber lyft, US Airways Flight 1549, Vernor Vinge, vertical integration, warehouse automation, warehouse robotics, Watson beat the top human players on Jeopardy!, William Langewiesche, Y Combinator, zero-sum game

If something has never happened before, a machine cannot predict it (at least without a human’s careful judgment to provide a useful analogy that allows the machine to predict using information about something else). Nassim Nicholas Taleb emphasizes unknown unknowns in his book The Black Swan.13 He highlights that we cannot predict truly new events from past data. The book’s title refers to the Europeans’ discovery of a new type of swan in Australia. To eighteenth-century Europeans, swans were white. Upon arrival in Australia, they saw something totally new and unpredictable: black swans. They had never seen black swans and therefore had no information that could predict the existence of such a swan.14 Taleb argues that the appearances of other unknown unknowns have important consequences—unlike the appearance of black swans, which had little meaningful impact on the direction of European or Australian society.

Even as machines get better at such situations, the laws of probability mean that in small samples, there will always be some uncertainty. Thus, when data is sparse, machine predictions will be imprecise in a known way. The machine can provide a sense of how imprecise its predictions are. As we discuss in chapter 8, this creates a human role for judging how to act on imprecise predictions. 13. Nassim Nicholas Taleb, The Black Swan (New York: Random House, 2007). 14. In Isaac Asimov’s Foundation series, prediction becomes powerful enough that it could foresee the destruction of the Galactic Empire and the various growing pains of the society that is the focus of the story. Important to the plot line, however, is that these predictions could not foresee the rise of “the mutant.”

See also autonomous vehicles autonomous vehicles, 8, 14–15 decision making by, 111–112 knowledge loss and, 78 legal requirements on, 116 loss of human driving skill and, 193 mail delivery, 103 in mining, 112–114 passenger interests and, 95 preferences and, 88–90 rail systems, 104 reward function engineering in, 92 school bus drivers and, 149–150 tolerance for error in, 185–187 value capture and, 164–165 Autopilot, 8 Babbage, Charles, 12, 65 back propagation, 38 Baidu, 164, 217, 219 bail-granting decisions, 56–58 bank tellers, 171–173 Bayesian estimation, 13 Beane, Billy, 56, 161–162 Beijing Automotive Group, 164 beta testing, 184, 191 Bhalla, Ajay, 25 biases, 19 feedback data and, 204–205 human predictions and, 55–58 in job ads, 195–198 against machine recommendations, 117 regression models and, 34 variance and, 34–35 binding affinity, 135–138 Bing, 50, 204, 216 biopsies, 108–109, 148 BlackBerry, 129 The Black Swan (Taleb), 60–61 Blake, Thomas, 199 blockchain, 220 Bostrom, Nick, 221, 222 boundary shifting, 157–158, 167–178 data ownership and, 174–176 what to leave in/out and, 168–170 breast cancer, 65 Bresnahan, Tim, 12 Bricklin, Dan, 141, 163, 164 A Brief History of Time (Hawking), 210–211 Brynjolfsson, Erik, 91 business models, 156–157 Amazon, 16–17 Camelyon Grand Challenge, 65 capital, 170–171, 213 Capital in the Twenty-First Century (Piketty), 213 capsule networks, 13 Cardiio, 44 Cardiogram, 44–45, 46, 47–49 causality, 63–64 reverse, 62 CDL.


pages: 270 words: 79,180

The Middleman Economy: How Brokers, Agents, Dealers, and Everyday Matchmakers Create Value and Profit by Marina Krakovsky

Affordable Care Act / Obamacare, Airbnb, Al Roth, Ben Horowitz, Benchmark Capital, Black Swan, buy low sell high, Chuck Templeton: OpenTable:, Credit Default Swap, cross-subsidies, crowdsourcing, deal flow, disintermediation, diversified portfolio, experimental economics, George Akerlof, Goldman Sachs: Vampire Squid, income inequality, index fund, information asymmetry, Jean Tirole, Joan Didion, John Zimmer (Lyft cofounder), Kenneth Arrow, Lean Startup, Lyft, Marc Andreessen, Mark Zuckerberg, market microstructure, Martin Wolf, McMansion, Menlo Park, Metcalfe’s law, moral hazard, multi-sided market, Network effects, patent troll, Paul Graham, Peter Thiel, pez dispenser, power law, real-name policy, ride hailing / ride sharing, Robert Metcalfe, Sand Hill Road, search costs, seminal paper, sharing economy, Silicon Valley, social graph, supply-chain management, TaskRabbit, the long tail, The Market for Lemons, the strength of weak ties, too big to fail, trade route, transaction costs, two-sided market, Uber for X, uber lyft, ultimatum game, Y Combinator

Even a monumental failure has a limit to its losses, whether it be $500,000 or $5 million, whereas a spectacular success knows no bounds: the top companies come to be valued at $500 million or more at exit. This is why the risk analyst Nassim Nicholas Taleb, best known as the author of The Black Swan, considers venture capital to be what he calls “antifragile,” something that actually gains from randomness.32 To achieve antifragility, Taleb writes, the potential cost of errors needs to remain small and the potential gain needs to be large. “It is the asymmetry between upside and downside that allows antifragile tinkering to benefit from disorder and uncertainty.”33 When your downside is limited and your upside is potentially infinite, you should embrace risk taking.

That rule fits venture capital perfectly because returns in venture capital follow a power-law distribution, a pattern many of us are familiar with as the 80/20 rule,34 although many power-law distributions are even more extreme. For example, according to a study released today, the 80 wealthiest individuals in the world collectively own $1.9 trillion—a total about equal to the “wealth” of all the people in the poorer half of the world.35 In The Black Swan, Taleb coined a memorable word to refer to such highly skewed distributions: they occur in “Extremistan,” where a single event or data point has a disproportionate impact on the total.36 Venture capital lives in Extremistan in that only about 15 start-ups out of several thousand vying for VC funding each year are responsible for the vast majority of profits: just one of those megahits—the next Google or Facebook or Twitter—will make you a monumental winner even if all your other investments lose money.

Newman, “Power Laws, Pareto Distributions and Zipf’s Law,” Contemporary Physics 46 (2005): 323–51. 35.Patricia Cohen, “Richest 1% Likely to Control Half of Global by Wealth by 2016, Study Finds,” New York Times, January 19, 2015. 36.Taleb wrote that “In Extremistan, inequalities are such that one single observation can disproportionately impact the aggregate, or the total.” See Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007), 33. 37.Peter Thiel, Zero to One: Notes on Startups, or How to Build the Future (New York: Crown Business, 2014), 86. 38.Julianne Pepitone and Stacy Cowley, “Facebook’s First Big Investor, Peter Thiel, Cashes Out,” CNNMoney, August 20, 2012. 39.In the introduction to their book of interviews with 35 top VCs and angel investors (including Maples), Tarang Shah and Sheetal Shah observe that entrepreneurs who had founded successful companies “had a very strong intuition and access to asymmetric information” that enabled them to tap emerging opportunities.


pages: 491 words: 131,769

Crisis Economics: A Crash Course in the Future of Finance by Nouriel Roubini, Stephen Mihm

Alan Greenspan, Asian financial crisis, asset-backed security, balance sheet recession, bank run, banking crisis, barriers to entry, Bear Stearns, behavioural economics, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, bond market vigilante , bonus culture, Bretton Woods, BRICs, British Empire, business cycle, call centre, capital controls, Carmen Reinhart, central bank independence, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, dark matter, David Ricardo: comparative advantage, debt deflation, Eugene Fama: efficient market hypothesis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial engineering, financial innovation, Financial Instability Hypothesis, financial intermediation, full employment, George Akerlof, Glass-Steagall Act, global pandemic, global reserve currency, Gordon Gekko, Greenspan put, Growth in a Time of Debt, housing crisis, Hyman Minsky, information asymmetry, interest rate swap, invisible hand, Joseph Schumpeter, junk bonds, Kenneth Rogoff, laissez-faire capitalism, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, Louis Bachelier, low interest rates, margin call, market bubble, market fundamentalism, Martin Wolf, means of production, Minsky moment, money market fund, moral hazard, mortgage debt, mortgage tax deduction, new economy, Northern Rock, offshore financial centre, oil shock, Paradox of Choice, paradox of thrift, Paul Samuelson, Ponzi scheme, price stability, principal–agent problem, private sector deleveraging, proprietary trading, pushing on a string, quantitative easing, quantitative trading / quantitative finance, race to the bottom, random walk, regulatory arbitrage, reserve currency, risk tolerance, Robert Shiller, Satyajit Das, Savings and loan crisis, savings glut, short selling, South Sea Bubble, sovereign wealth fund, special drawing rights, subprime mortgage crisis, Suez crisis 1956, The Great Moderation, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, too big to fail, tulip mania, Tyler Cowen, unorthodox policies, value at risk, We are all Keynesians now, Works Progress Administration, yield curve, Yom Kippur War

As it became apparent that the crisis was real, many commentators tried to make sense of the disaster. Plenty of people invoked Nassim Nicholas Taleb’s concept of the “black swan” to explain it. Taleb, whose book of that title came out on the eve of the crisis, defined a “black swan event” as a game-changing occurrence that is both extraordinarily rare and well-nigh impossible to predict. By that definition, the financial crisis was a freak event, albeit an incredibly important and transformational one. No one could possibly have seen it coming. In a perverse way, that idea is comforting. If financial crises are black swans, comparable to plane crashes—horrific but highly improbable and impossible to predict—there’s no point in worrying about them.

., remarks to the Washington Post 200 Lunch, Washington, D.C., May 16, 2008, online at http://www.ustreas.gov/press/releases/hp981.htm. 16 “Sure . . . there are trouble spots . . .”: Donald Luskin, “Quit Doling Out That Bad-Economy Line,” Washington Post, September 14, 2008. 16 “black swan”: Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 18 households used their homes as collateral: Karl E. Case, John M. Quigley, and Robert J. Shiller, “Comparing Wealth Effects: The Stock Market versus the Housing Market,” Advances in Macroeconomics 5 (2005): 1-34. 18 home equity withdrawals: See Gene Sperling, “Housing Bust Meets the Equity Blues,” Bloomberg.com, April 19, 2007, online at http://www.bloomberg.com/apps/news?

Freefall: America, Free Markets, and the Sinking of the World Economy. New York: W.W. Norton, 2010. Sylla, Richard. “Monetary Innovation and Crises in American Economic History.” In Paul Wachtel, ed., Crises in the Economic and Financial Structure. Lexington, Mass.: D.C. Heath, 1982. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Temin, Peter. Did Monetary Forces Cause the Great Depression? New York: W. W. Norton, 1976. Tett, Gillian. Fool’s Gold: How the Bold Dream of a Small Tribe at J. P. Morgan Was Corrupted by Wall Street Greed and Unleashed a Catastrophe.


pages: 447 words: 104,258

Mathematics of the Financial Markets: Financial Instruments and Derivatives Modelling, Valuation and Risk Issues by Alain Ruttiens

algorithmic trading, asset allocation, asset-backed security, backtesting, banking crisis, Black Swan, Black-Scholes formula, Bob Litterman, book value, Brownian motion, capital asset pricing model, collateralized debt obligation, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, delta neutral, discounted cash flows, discrete time, diversification, financial engineering, fixed income, implied volatility, interest rate derivative, interest rate swap, low interest rates, managed futures, margin call, market microstructure, martingale, p-value, passive investing, proprietary trading, quantitative trading / quantitative finance, random walk, risk free rate, risk/return, Satyajit Das, seminal paper, Sharpe ratio, short selling, statistical model, stochastic process, stochastic volatility, time value of money, transaction costs, value at risk, volatility smile, Wiener process, yield curve, zero-coupon bond

LVII, no. 5, 2002, pp. 2075–2112. 13 See Y. AÏT-SAHALIA, P.A. MYKLAND, “The effects of random and discrete sampling when estimating continuous-time diffusions”, Econometrica, vol. 71, no. 2, 2003, pp. 483–549. 14 For more about these issues, see E. DERMAN, N. TALEB, “The illusion of dynamic replication”, Quantitative Finance, vol. 5, no. 4, 2005, pp. 323–326. 15 Nassim N. TALEB, The Black Swan, 2nd ed., Random House, 2010, 480 p. 16 See M. HENRARD, Swaptions: 1 price, 10 deltas, and … 6 gammas, Wilmott Magazine, April 2011, pp. 48–57. 17 Robert A. JARROW, Risk management models: construction, testing, usage, Johnson School Research Paper Series no. 38, 2010, March 15, 2011. 18 See Alain RUTTIENS, Pour contribuer à réduire le risque de pertes dans les activités de marché: la gestion d'actifs et le risque de position, AGEFI Luxembourg, October 2008 (in French). 19 Thomas S.

With respect to risk management, the expected credit loss amount should have to be lower than the profits of the bank or fund activities, 15 while the Credit VaR amount should not exceed the net asset value of the bank (or economic capital) or fund. A higher loss than the Credit VaR level may be viewed as likely to threaten the survival of the bank or fund, hence the tentatives to test such possibility by stress tests, although difficult to design properly (cf. the Nassim Taleb's “black swan”). Example. A fund has $100m of various exposures. Adequate Monte Carlo simulations allow to estimate that, over 1 year, the frequency of losses with c = 99% is 15%. For a global recovery rate (cf. Chapter 13, Section 13.1.4) of the exposure estimated at 40%, the 1-year Credit VaR is Given the complexity of the task of modeling credit risk (cf.

Zone “II”: there is some higher, unexpected, loss level corresponding to the maximum financial capacity of the firm, before going bankrupt. Zone III: to care for the highly improbable occurrence of losses above this maximum level, one has not found anything but “stress tests”. The problem – explored by Nassim Taleb in his famous book “The Black Swan”15 – is that it is almost impossible to guess what should have to be tested. Indeed, an abnormally huge loss cannot be caused but by a rare, unexpected event, that could have been hardly anticipated (if it was the case, it could even have resulted in a smaller loss) and tested beforehand.


pages: 478 words: 126,416

Other People's Money: Masters of the Universe or Servants of the People? by John Kay

Affordable Care Act / Obamacare, Alan Greenspan, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, behavioural economics, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Monday: stock market crash in 1987, Black Swan, Bonfire of the Vanities, bonus culture, book value, Bretton Woods, buy and hold, call centre, capital asset pricing model, Capital in the Twenty-First Century by Thomas Piketty, cognitive dissonance, Cornelius Vanderbilt, corporate governance, Credit Default Swap, cross-subsidies, currency risk, dematerialisation, disinformation, disruptive innovation, diversification, diversified portfolio, Edward Lloyd's coffeehouse, Elon Musk, Eugene Fama: efficient market hypothesis, eurozone crisis, financial engineering, financial innovation, financial intermediation, financial thriller, fixed income, Flash crash, forward guidance, Fractional reserve banking, full employment, George Akerlof, German hyperinflation, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Greenspan put, Growth in a Time of Debt, Ida Tarbell, income inequality, index fund, inflation targeting, information asymmetry, intangible asset, interest rate derivative, interest rate swap, invention of the wheel, Irish property bubble, Isaac Newton, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", Jim Simons, John Meriwether, junk bonds, light touch regulation, London Whale, Long Term Capital Management, loose coupling, low cost airline, M-Pesa, market design, Mary Meeker, megaproject, Michael Milken, millennium bug, mittelstand, Money creation, money market fund, moral hazard, mortgage debt, Myron Scholes, NetJets, new economy, Nick Leeson, Northern Rock, obamacare, Occupy movement, offshore financial centre, oil shock, passive investing, Paul Samuelson, Paul Volcker talking about ATMs, peer-to-peer lending, performance metric, Peter Thiel, Piper Alpha, Ponzi scheme, price mechanism, proprietary trading, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, railway mania, Ralph Waldo Emerson, random walk, reality distortion field, regulatory arbitrage, Renaissance Technologies, rent control, risk free rate, risk tolerance, road to serfdom, Robert Shiller, Ronald Reagan, Schrödinger's Cat, seminal paper, shareholder value, Silicon Valley, Simon Kuznets, South Sea Bubble, sovereign wealth fund, Spread Networks laid a new fibre optics cable between New York and Chicago, Steve Jobs, Steve Wozniak, The Great Moderation, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tobin tax, too big to fail, transaction costs, tulip mania, Upton Sinclair, Vanguard fund, vertical integration, Washington Consensus, We are the 99%, Yom Kippur War

., 2005, The Wisdom of Crowds: Why the Many Are Smarter Than the Few, London, Abacus. Taibbi, M., 2009, ‘The Great American Bubble Machine’, Rolling Stone, 9 July. Tainter, J., 1988, The Collapse of Complex Societies, Cambridge, Cambridge University Press. Taleb, N.N., 2001, Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life, London and New York, Texere. Taleb, N.N., 2007, The Black Swan: The Impact of the Highly Improbable, London, Penguin. Taleb, N.N., 2012, Antifragile: Things That Gain from Disorder, New York, Random House. Tarbell, I.M., 1904, The History of the Standard Oil Company, New York, McClure, Phillips & Co. Taylor, M., 2014, ‘Banks Have Failed to Exorcise Their Technical Gremlins’, Financial Times, 30 January.

., 2014, ‘The Case for Index-Fund Investing’, Vanguard Research, April, https://advisors.vanguard.com/VGApp/iip/site/advisor/researchcommentary/article/IWE_InvComCase4Index. 20. Kahneman himself is not guilty of this: Kahneman, D., 2011, Thinking Fast and Slow, New York, Farrar, Straus and Giroux. 21. Rubin, R., 2004, In an Uncertain World, New York, Random House. 22. The unknown unknown was famously described by Donald Rumsfeld; see Taleb, N.N., 2007, The Black Swan: The Impact of the Highly Improbable, London, Penguin. 23. Greenspan, A., 2008, Statement to the House, Committee on Oversight and Government Reform, Hearing, 23 October (Serial 110–209). 24. Ibid. 25. Tett, G., 2013, ‘An Interview with Alan Greenspan’, FT Magazine, 25 October. 26.

Transcript of investor conference call, 9 August 2007, reported on Bloomberg.com, 25 November 2008. 13. Congressional Oversight Panel, June Oversight Report: The AIG Rescue, Its Impact on Markets, and the Government’s Exit Strategy, 10 June 2010. 14. Shaxson, N., 2011, Treasure Islands, New York, St Martin’s Press. 15. Taleb, N.N., 2007, The Black Swan: The Impact of the Highly Improbable, London, Penguin, p. 43. 16. Edwards, J.S.S., Kay, J.A., and Mayer, C.P., 1987, The Economic Analysis of Accounting Profitability, Oxford, Oxford University Press. 17. McLean, B., and Elkind, P., 2003, The Smartest Guys in the Room: The Amazing Rise and Scandalous Fall of Enron, New York, Penguin, p. 41. 18.


pages: 381 words: 101,559

Currency Wars: The Making of the Next Gobal Crisis by James Rickards

"World Economic Forum" Davos, Alan Greenspan, Asian financial crisis, bank run, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Big bang: deregulation of the City of London, Black Swan, borderless world, Bretton Woods, BRICs, British Empire, business climate, buy and hold, capital controls, Carmen Reinhart, Cass Sunstein, collateralized debt obligation, complexity theory, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-border payments, currency manipulation / currency intervention, currency peg, currency risk, Daniel Kahneman / Amos Tversky, deal flow, Deng Xiaoping, diversification, diversified portfolio, Dr. Strangelove, Fall of the Berlin Wall, family office, financial innovation, floating exchange rates, full employment, game design, German hyperinflation, Gini coefficient, global rebalancing, global reserve currency, Great Leap Forward, guns versus butter model, high net worth, income inequality, interest rate derivative, it's over 9,000, John Meriwether, Kenneth Rogoff, laissez-faire capitalism, liquidity trap, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, Mexican peso crisis / tequila crisis, Money creation, money market fund, money: store of value / unit of account / medium of exchange, Myron Scholes, Network effects, New Journalism, Nixon shock, Nixon triggered the end of the Bretton Woods system, offshore financial centre, oil shock, one-China policy, open economy, paradox of thrift, Paul Samuelson, power law, price mechanism, price stability, private sector deleveraging, proprietary trading, quantitative easing, race to the bottom, RAND corporation, rent-seeking, reserve currency, Ronald Reagan, short squeeze, sovereign wealth fund, special drawing rights, special economic zone, subprime mortgage crisis, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, time value of money, too big to fail, value at risk, vertical integration, War on Poverty, Washington Consensus, zero-sum game

Importantly, phase transitions can produce catastrophic effects from small causes—a single snowflake can cause a village to be destroyed by an avalanche. This is one secret behind so-called black swans. Nassim Nicholas Taleb popularized the term “black swan” in his book of the same name. In that book, Taleb rightly demolished the normal distribution—the bell curve—as a way of understanding risk. The problem is that he demolished one paradigm but did not produce another to replace it. Taleb expressed some disdain for mathematical modeling in general, preferring to take on the mantle of a philosopher. He dubbed all improbably catastrophic events “black swans,” as if to say, “Stuff happens,” and he left it at that. The term is widely used by analysts and policy makers who understand the “Stuff happens” part but don’t understand the critical state dynamics and complexity behind it.

Christ, “A Short-Run Aggregate-Demand Model of the Interdependence and Effects of Monetary and Fiscal Policies with Keynesian and Classical Interest Elasticities,” The American Economic Review 57, no. 2, May 1967. 192 The role of VaR in causing the Panic of 2008 is immense . . . The House of Representatives held one hearing on this topic, at which sworn testimony was provided by Black Swan author Nassim Nicholas Taleb, bank analyst Christopher Whalen and myself, among others. This hearing was held by the Subcommittee on Investigations and Oversight of the Committee on Science, Space and Technology on September 10, 2009. The ostensible reason for using the Science Committee was that VaR is a quantitative and therefore scientific discipline; however, I was informed that this was actually done at the request of Financial Services Committee chairman Barney Frank in order to establish a record on VaR while avoiding the lobbyists who typically influence witness selection and questions in the Financial Services Committee.

New Haven: Yale University Press, 2006. Stewart, Bruce H., and J. M. Thompson. Nonlinear Dynamics and Chaos, 2nd ed. Chichester, UK: Wiley, 2002. Surowiecki, James. The Wisdom of Crowds. New York: Doubleday, 2004. Tainter, Joseph A. The Collapse of Complex Societies. Cambridge: Cambridge University Press, 1988. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Tarnoff, Ben. Moneymakers: The Wicked Lives and Surprising Adventures of Three Notorious Counterfeiters. New York: Penguin Press, 2011. Taylor, John B. Getting Off Track: How Government Actions and Interventions Caused, Prolonged, and Worsened the Financial Crisis.


pages: 246 words: 74,341

Financial Fiasco: How America's Infatuation With Homeownership and Easy Money Created the Economic Crisis by Johan Norberg

accounting loophole / creative accounting, Alan Greenspan, bank run, banking crisis, Bear Stearns, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, business cycle, capital controls, central bank independence, collateralized debt obligation, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, David Brooks, diversification, financial deregulation, financial innovation, Greenspan put, helicopter parent, Home mortgage interest deduction, housing crisis, Howard Zinn, Hyman Minsky, Isaac Newton, Joseph Schumpeter, Long Term Capital Management, low interest rates, market bubble, Martin Wolf, Mexican peso crisis / tequila crisis, millennium bug, money market fund, moral hazard, mortgage tax deduction, Naomi Klein, National Debt Clock, new economy, Northern Rock, Own Your Own Home, precautionary principle, price stability, Ronald Reagan, savings glut, short selling, Silicon Valley, South Sea Bubble, The Wealth of Nations by Adam Smith, too big to fail

For every $100 they had guaranteed or lent through securities, they had only $1.20 of equity.4S In August 2008, Fannie and Freddie owned junk loans and securities based on junk loans worth over $1 trillion-more than one-fifth of their entire mortgage portfolio.49 In the words of Nassim Nicholas Taleb, author of the book The Black Swan, about how people underestimate lowprobability risks, they were "sitting on a barrel of dynamite." Their army of analysts, however, claimed that the risks were small. They had sophisticated models to manage risks. That is, all risks but onea fall in home prices.50 As Freddie Mac's former CEO Richard Syron looked back on what went wrong, he blamed the bad mortgages on politicians' pushing through an expansion of homeownership even to households that could not afford to own a home.

Leonnig, "How HUD Mortgage Policy Fed the Crisis." 46. Wallison and Calomiris, "The Last Trillion-Dollar Commitment." 47. Shenn, "Fannie, Freddie Subprire Spree." 48. Lockhart, "Reforming the Regulation of the Government Sponsored Enterprises." 49. Wallison and Calomiris, "The Last Trillion-Dollar Commitment." 50. Taleb, The Black Swan, pp. 225-26. 51. Duhigg, "Pressured to Take More Risk." Chapter 3 1. Dougherty, "German Bank Becomes First EU Victim"; The Economist, "Sold Down the River Rhine." 2. Muolo and Padilla, Chain of Blame, pp. 209-10. 3. Grant, Mr. Market Miscalculates, pp. 181-82. 4. Pollock, "The Human Foundations of Financial Risk." 5.

Sarkozy, "International Financial Crisis"; International Herald Tribune, "Germany: US Slipping as Financial Superpower"; Prashad, "Wealth's Apostles." 7. de Rugy and Warren, "Regulatory Agency Spending Reaches New Height," pp. 5-6. 8. de Rugy, "Bush's Regulatory Kiss-Off." 9. Smith, Wealth of Nations, V.i.e.18. 10. Jolly, "Ex-Trader Tells How He Lost So Much for One Bank." 11. Younglai, "SEC's Cox Regrets Short-Selling Ban." 12. Heckscher, Gammal och ny ekonomisk liberalism, pp. 96-97 (quotation translated). 13. Taleb, The Black Swan; Buffett on the Charlie Rose Shozo, WNET, October 1, 2008. 14. Lessig, "Why the Banks All Fell Down." 15. Dowd, "Moral Hazard and the Financial Crisis." 16. The Economist, "Negative Outlook." 17. Hayek, Denationalisation of Money. See also Rothbard, What Has Government Done to Our Money?


pages: 376 words: 109,092

Paper Promises by Philip Coggan

accounting loophole / creative accounting, activist fund / activist shareholder / activist investor, Alan Greenspan, balance sheet recession, bank run, banking crisis, barriers to entry, Bear Stearns, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, bond market vigilante , Bretton Woods, British Empire, business cycle, call centre, capital controls, Carmen Reinhart, carried interest, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, currency risk, debt deflation, delayed gratification, diversified portfolio, eurozone crisis, Fall of the Berlin Wall, falling living standards, fear of failure, financial innovation, financial repression, fixed income, floating exchange rates, full employment, German hyperinflation, global reserve currency, Goodhart's law, Greenspan put, hiring and firing, Hyman Minsky, income inequality, inflation targeting, Isaac Newton, John Meriwether, joint-stock company, junk bonds, Kenneth Rogoff, Kickstarter, labour market flexibility, Les Trente Glorieuses, light touch regulation, Long Term Capital Management, low interest rates, manufacturing employment, market bubble, market clearing, Martin Wolf, Minsky moment, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, Myron Scholes, negative equity, Nick Leeson, Northern Rock, oil shale / tar sands, paradox of thrift, peak oil, pension reform, plutocrats, Ponzi scheme, price stability, principal–agent problem, purchasing power parity, quantitative easing, QWERTY keyboard, railway mania, regulatory arbitrage, reserve currency, Robert Gordon, Robert Shiller, Ronald Reagan, savings glut, short selling, South Sea Bubble, sovereign wealth fund, special drawing rights, Suez crisis 1956, The Chicago School, The Great Moderation, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Wealth of Nations by Adam Smith, time value of money, too big to fail, trade route, tulip mania, value at risk, Washington Consensus, women in the workforce, zero-sum game

Another issue was that the figures in the VAR models also tended to be heavily influenced by recent observations. So a long period of low volatility tended to reduce the potential loss generated by the model, thereby persuading banks to take more risk (just as Hyman Minsky predicted). As Taleb points out, this creates a very dangerous mindset. His ‘black swan’ example dates back to the philosopher David Hume; just because you see a thousand white swans does not mean there cannot be a black swan (as there are in Australia). But another example of his reasoning is even more illuminating. Turkeys are fed by the farmer for 364 days, and must presume the farmer to be a benign caregiver; they have no way of anticipating that, on the 365th day, the same farmer will slaughter them for our Thanksgiving or Christmas meal.

Its mandate was set by treaty. 21 Michiyo Nakamoto and David Wighton, ‘Citigroup Chief Stays Bullish on Buy-outs’, Financial Times, 9 July 2007. 22 Quoted in Nick Leeson, Rogue Trader, London, 1996. 23 Pablo Triana, Lecturing Birds on Flying: Can Mathematical Theories Destroy The Financial Markets?, New York, 2009. 24 Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, London, 2008. 25 Peter Thal Larsen, ‘Goldman Pays the Price for Being Big’, Financial Times, 13 August 2008. 26 Andrew Haldane, ‘Why Banks Failed the Stress Test’, 9 – 10 February 2009. 27 Interview with the author, 25 October 2010. 9. THE CRISIS BEGINS 1 Tim Congdon, The Debt Threat, Oxford, 1989. 2 Peter Warburton, Debt and Delusion, London, 1999. 3 ‘Debt and Deleveraging: The Global Credit Bubble and its Economic Consequences’, McKinsey Global Institute, January 2010. 4 Scott Schuh, Oz Shy and Joanna Stavins, ‘Who Gains and Who Loses from Credit Card Payments?

Skidelsky, Robert, John Maynard Keynes: Fighting for Freedom 1937 – 1946, London, 2001. —Keynes: The Return of the Master, London, 2009. Sorkin, Andrew Ross, Too Big to Fail: Inside the Battle to Save Wall Street, London, 2009. Stiglitz, Joseph, Freefall: Free Markets and the Sinking of the Global Economy , rev. edn, London, 2010. Taleb, Nassim Nicholas, The Black Swan: The Impact of the Highly Improbable , London, 2008. Warburton, Peter, Debt and Delusion: Central Bank Follies that Threaten Economic Disaster, London, 1999. Willetts, David, The Pinch: How the Baby Boomers Took Their Children’s Future – and Why They Should Give It Back, London, 2010.


pages: 370 words: 107,983

Rage Inside the Machine: The Prejudice of Algorithms, and How to Stop the Internet Making Bigots of Us All by Robert Elliott Smith

"World Economic Forum" Davos, Ada Lovelace, adjacent possible, affirmative action, AI winter, Alfred Russel Wallace, algorithmic bias, algorithmic management, AlphaGo, Amazon Mechanical Turk, animal electricity, autonomous vehicles, behavioural economics, Black Swan, Brexit referendum, British Empire, Cambridge Analytica, cellular automata, Charles Babbage, citizen journalism, Claude Shannon: information theory, combinatorial explosion, Computing Machinery and Intelligence, corporate personhood, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, data science, deep learning, DeepMind, desegregation, discovery of DNA, disinformation, Douglas Hofstadter, Elon Musk, fake news, Fellow of the Royal Society, feminist movement, Filter Bubble, Flash crash, Geoffrey Hinton, Gerolamo Cardano, gig economy, Gödel, Escher, Bach, invention of the wheel, invisible hand, Jacquard loom, Jacques de Vaucanson, John Harrison: Longitude, John von Neumann, Kenneth Arrow, Linda problem, low skilled workers, Mark Zuckerberg, mass immigration, meta-analysis, mutually assured destruction, natural language processing, new economy, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, On the Economy of Machinery and Manufactures, p-value, pattern recognition, Paul Samuelson, performance metric, Pierre-Simon Laplace, post-truth, precariat, profit maximization, profit motive, Silicon Valley, social intelligence, statistical model, Stephen Hawking, stochastic process, Stuart Kauffman, telemarketer, The Bell Curve by Richard Herrnstein and Charles Murray, The Future of Employment, the scientific method, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Malthus, traveling salesman, Turing machine, Turing test, twin studies, Vilfredo Pareto, Von Neumann architecture, warehouse robotics, women in the workforce, Yochai Benkler

Errors that fall into the latter camp are what are sometimes call black swans, thanks to Nassim Nicholas Taleb’s popular 2007 book The Black Swan: The Impact of the Highly Improbable.7 Taleb illustrated his titular concept with the one-rule model that simply says, ‘All swans are white’. This model is entirely right and useful, up to the point where one sees even a single black swan. At that point, the model’s value completely vanishes, because one has to reconsider the entire model (that is to say, the one parsimonious rule). A black swan is the revelatory sort of event that Box was talking about, one that prompts a total re-evaluation of swans – if there are black swans might there be swans of different hues, and what else don’t we know about swans now that we’ve discovered there are black swans?

IEEE Annals of the History of Computing, 25:4, https://ieeexplore.ieee.org/document/1253886 6Molly McLay, 2006, From Wollstonecraft to Mill: Varied Positions and Influences of the European and American Women’s Rights Movements. Constructing the Past, 7(1), Article 13, http://digitalcommons.iwu.edu/constructing/vol7/iss1/13 7N.N. Taleb, 2007, The Black Swan: The Impact of the Highly Improbable, New York: Random House. 8Betty Alexandra Toole, 1992, Ada, the Enchantress of Numbers: A Selection from the Letters of Lord Byron’s Daughter and Her Description of the First Computer. Mill Valley, CA: Strawberry Press. 9Saini, A., 2017, Inferior: How Science Got Women Wrong and the New Research that’s Rewriting the Story.

A black swan is the revelatory sort of event that Box was talking about, one that prompts a total re-evaluation of swans – if there are black swans might there be swans of different hues, and what else don’t we know about swans now that we’ve discovered there are black swans? This leads to a shift in the movable window, leading us towards the gathering of more data, followed by new cycles of induction and deduction, to form more useful models. Unfortunately, steering the window of social models has resisted recognition of black swans, even when they’ve crashed right into the most important developments in the history of science and technology. In 1814, Byron married the wealthy heiress Anne Isabella Milbanke, nicknamed Lady Annabelle.


pages: 537 words: 144,318

The Invisible Hands: Top Hedge Fund Traders on Bubbles, Crashes, and Real Money by Steven Drobny

Albert Einstein, AOL-Time Warner, Asian financial crisis, asset allocation, asset-backed security, backtesting, banking crisis, Bear Stearns, Bernie Madoff, Black Swan, bond market vigilante , book value, Bretton Woods, BRICs, British Empire, business cycle, business process, buy and hold, capital asset pricing model, capital controls, central bank independence, collateralized debt obligation, commoditize, commodity super cycle, commodity trading advisor, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency peg, debt deflation, diversification, diversified portfolio, equity premium, equity risk premium, family office, fiat currency, fixed income, follow your passion, full employment, George Santayana, global macro, Greenspan put, Hyman Minsky, implied volatility, index fund, inflation targeting, interest rate swap, inventory management, inverted yield curve, invisible hand, junk bonds, Kickstarter, London Interbank Offered Rate, Long Term Capital Management, low interest rates, market bubble, market fundamentalism, market microstructure, Minsky moment, moral hazard, Myron Scholes, North Sea oil, open economy, peak oil, pension reform, Ponzi scheme, prediction markets, price discovery process, price stability, private sector deleveraging, profit motive, proprietary trading, purchasing power parity, quantitative easing, random walk, Reminiscences of a Stock Operator, reserve currency, risk free rate, risk tolerance, risk-adjusted returns, risk/return, savings glut, selection bias, Sharpe ratio, short selling, SoftBank, sovereign wealth fund, special drawing rights, statistical arbitrage, stochastic volatility, stocks for the long run, stocks for the long term, survivorship bias, tail risk, The Great Moderation, Thomas Bayes, time value of money, too big to fail, Tragedy of the Commons, transaction costs, two and twenty, unbiased observer, value at risk, Vanguard fund, yield curve, zero-sum game

Most of these lessons are as old as the hills, which is why I really cannot understand all this talk about black swans. When the same thing happens over and over again, how can you be surprised? “Black swan” may have become the most confusing phrase in markets. Nassim Taleb’s recent use of the term is commonly understood to denote an unlikely and unforeseeable event, but this is not the main story of 2008. I saw a crisis as highly likely given people’s beliefs and behaviors. Many people seem to use the “black swan” idea to reassure themselves when some bad things happened that they did not expect. They use it to claim that it was not their fault, which I do not think was Taleb’s meaning. Too often, people use it to avoid taking responsibility for their actions by claiming the events—and their losses—in 2008 were unforeseeable, whereas in fact their hypothesis of how markets worked was just disproved.

Too often, people use it to avoid taking responsibility for their actions by claiming the events—and their losses—in 2008 were unforeseeable, whereas in fact their hypothesis of how markets worked was just disproved. The other hypotheses always existed. The metaphor of the black swan is of course an old one and was used by Karl Popper in the 1930s to illustrate the fallacy of induction. It is an example of something that can falsify a hypothesis. If you have a hypothesis that all swans are white, a single black swan falsifies that hypothesis. In this usage, the existence of a black swan is of course neither unforeseeable nor even a low probability event, since hypotheses are falsified all the time. It is as though the recent “black swan” is not taken as a falsification but instead as confirmation that swans are generally white and so we should carry on as before, which is a perverse interpretation of either Popper or Taleb.

.,” Swampland: A Blog about Politics, September 15, 2009, http://swampland.blogs.time.com/2009/09/15/warren-buffett-could-have-saved-lehma/. How do you make sure that you are around to keep playing in your hedge fund? We tend to be long volatility and look for trades that make money in difficult markets, during down swings in risky assets and in times of increased volatility. We like to be long the tails, the black swans. In general, however, we run a fairly low-risk fund. We try to avoid being hurt by catastrophic scenarios because the survivors are usually granted a license to print money for a while. Do you spend more time thinking about how it could all go wrong or how you are going to make money? We spend more time on how to make money.


pages: 502 words: 107,657

Predictive Analytics: The Power to Predict Who Will Click, Buy, Lie, or Die by Eric Siegel

Alan Greenspan, Albert Einstein, algorithmic trading, Amazon Mechanical Turk, Apollo 11, Apple's 1984 Super Bowl advert, backtesting, Black Swan, book scanning, bounce rate, business intelligence, business process, butter production in bangladesh, call centre, Charles Lindbergh, commoditize, computer age, conceptual framework, correlation does not imply causation, crowdsourcing, dark matter, data is the new oil, data science, driverless car, en.wikipedia.org, Erik Brynjolfsson, Everything should be made as simple as possible, experimental subject, Google Glasses, happiness index / gross national happiness, information security, job satisfaction, Johann Wolfgang von Goethe, lifelogging, machine readable, Machine translation of "The spirit is willing, but the flesh is weak." to Russian and back, mass immigration, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, Norbert Wiener, personalized medicine, placebo effect, prediction markets, Ray Kurzweil, recommendation engine, risk-adjusted returns, Ronald Coase, Search for Extraterrestrial Intelligence, self-driving car, sentiment analysis, Shai Danziger, software as a service, SpaceShipOne, speech recognition, statistical model, Steven Levy, supply chain finance, text mining, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Davenport, Turing test, Watson beat the top human players on Jeopardy!, X Prize, Yogi Berra, zero-sum game

I also often refer in my own writing to a third type of analytics—“prescriptive”—that tells its users what to do through controlled experiments or optimization. Those quantitative methods are much less popular, however, than predictive analytics. This book and the ideas behind it are a good counterpoint to the work of Nassim Nicholas Taleb. His books, including The Black Swan, suggest that many efforts at prediction are doomed to fail because of randomness and the inherent unpredictability of complex events. Taleb is no doubt correct that some events are black swans that are beyond prediction, but the fact is that most human behavior is quite regular and predictable. The many examples that Siegel provides of successful prediction remind us that most swans are white.

Leinweber attracted the attention he sought, but his lesson didn’t seem to sink in. “I got calls for years asking me what the current butter business in Bangladesh was looking like and I kept saying, ‘Ya know, it was a joke, it was a joke!’ It’s scary how few people actually get that.” As Black Swan author Nassim Taleb put it in his suitably titled book, Fooled by Randomness, “Nowhere is the problem of induction more relevant than in the world of trading—and nowhere has it been as ignored!” Thus the occasional overzealous yet earnest public claim of economic prediction based on factors like women’s hemlines, men’s necktie width, Super Bowl results, and Christmas day snowfall in Boston.

See also test data Baesens, Ben bagging (bootstrap aggregating) Bangladesh Barbie dolls Bayes, Thomas (Bayes Network) Beane, Billy Beano Beaux, Alex behavioral predictors Bella Pictures BellKor BellKor Netflix Prize teams Ben Gurion University (Israel) Bernstein, Peter Berra, Yogi Big Bang Theory, The Big Bang theory Big Brother BigChaos team “big data” movement billing errors, predicting black box trading Black Swan, The (Taleb) blogs and blogging anxiety, predicting from entries collective intelligence and data glut and content in LiveJournal mood prediction research via nature of Blue Cross Blue Shield of Tennessee BMW BNSF Railway board games, predictive play of Bohr, Niels book titles, testing Bowie, David brain activity, predicting Brandeis, Louis Brasil Telecom (Oi) breast cancer, predicting Brecht, Bertolt Breiman, Leo Brigham Young University British Broadcasting Corporation (BBC) Brobst, Stephen Brooks, Mel Brynjolfsson, Eric buildings, predicting fault in Bullard, Ben burglaries, predicting business rules, decision trees and buying behavior, predicting C Cage, Nicolas Canadian Automobile Association Canadian Tire car crashes and harm, predicting CareerBuilder Carlin, George Carlson, Gretchen Carnegie Mellon University CART decision trees Castagno, Davide causality cell phone industry consumer behavior and dropped calls, predicting GPS data and location predicting Telenor (Norway) CellTel (African telecom) Central Tables.


pages: 348 words: 83,490

More Than You Know: Finding Financial Wisdom in Unconventional Places (Updated and Expanded) by Michael J. Mauboussin

Alan Greenspan, Albert Einstein, Andrei Shleifer, Atul Gawande, availability heuristic, beat the dealer, behavioural economics, Benoit Mandelbrot, Black Swan, Brownian motion, butter production in bangladesh, buy and hold, capital asset pricing model, Clayton Christensen, clockwork universe, complexity theory, corporate governance, creative destruction, Daniel Kahneman / Amos Tversky, deliberate practice, demographic transition, discounted cash flows, disruptive innovation, diversification, diversified portfolio, dogs of the Dow, Drosophila, Edward Thorp, en.wikipedia.org, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, fixed income, framing effect, functional fixedness, hindsight bias, hiring and firing, Howard Rheingold, index fund, information asymmetry, intangible asset, invisible hand, Isaac Newton, Jeff Bezos, John Bogle, Kenneth Arrow, Laplace demon, Long Term Capital Management, loss aversion, mandelbrot fractal, margin call, market bubble, Menlo Park, mental accounting, Milgram experiment, Murray Gell-Mann, Nash equilibrium, new economy, Paul Samuelson, Performance of Mutual Funds in the Period, Pierre-Simon Laplace, power law, quantitative trading / quantitative finance, random walk, Reminiscences of a Stock Operator, Richard Florida, Richard Thaler, Robert Shiller, shareholder value, statistical model, Steven Pinker, stocks for the long run, Stuart Kauffman, survivorship bias, systems thinking, The Wisdom of Crowds, transaction costs, traveling salesman, value at risk, wealth creators, women in the workforce, zero-sum game

Daniel Kahneman, Paul Slovic, and Amos Tversky (Cambridge: Cambridge University Press, 1982), 306-34. 8 Peter Schwartz, Inevitable Surprises: Thinking Ahead in a Time of Turbulence (New York: Gotham Books, 2003). 9 Roger Lowenstein, When Genius Failed: The Rise and Fall of Long-Term Capital Management (New York: Random House, 2000); Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 10 Daniel Kahneman and Amos Tversky, “Prospect Theory: An Analysis of Decision Under Risk,” Econometrica 47 (1979): 263-91. 11 Nassim Nicholas Taleb, Fooled By Randomness: The Hidden Role of Chance in Markets and in Life (New York: Texere, 2001), 89-90. Taleb takes to task the well-known investor Jim Rogers for arguing against investing in options because of the frequency of loss. Says Taleb, “Mr. Jim Rogers seems to have gone very far in life for someone who does not distinguish between probability and expectation.” 12 See chapter 3. 13 Russo and Schoemaker, Winning Decisions, 123-24. 14 Rubin, commencement address, University of Pennsylvania, 1999. 2.

New Yorker, March 28, 2003. http://www.newyorker.com/archive/2003/03/24/030324ta_talk_surowiecki. ——. The Wisdom of Crowds: Why the Many Are Smarter Than the Few and How Collective Wisdom Shapes Business, Economies, Societies and Nations. New York: Random House, 2004. Taleb, Nassim Nicholas. Fooled By Randomness: The Hidden Role of Chance in Markets and in Life. New York: Texere, 2001. ——. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Tallis, Frank. Hidden Minds: A History of the Unconscious. New York: Arcade Publishing, 2002. Taylor, Richard P. “Order in Pollock’s Chaos.” Scientific American (December 2002). http://materialscience.uoregon.edu/taylor/art/scientificamerican.pdf.

Bulls, Bears, and Odds In his provocative book Fooled by Randomness, Nassim Taleb relates an anecdote that beautifully drives home the expected value message.3 In a meeting with his fellow traders, a colleague asked Taleb about his view of the market. He responded that he thought there was a high probability that the market would go up slightly over the next week. Pressed further, he assigned a 70 percent probability to the up move. Someone in the meeting then noted that Taleb was short a large quantity of S&P 500 futures—a bet that the market would go down—seemingly in contrast to his “bullish” outlook. Taleb then explained his position in expected-value terms.


pages: 460 words: 131,579

Masters of Management: How the Business Gurus and Their Ideas Have Changed the World—for Better and for Worse by Adrian Wooldridge

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, affirmative action, Alan Greenspan, barriers to entry, behavioural economics, Black Swan, blood diamond, borderless world, business climate, business cycle, business intelligence, business process, carbon footprint, Cass Sunstein, Clayton Christensen, clean tech, cloud computing, collaborative consumption, collapse of Lehman Brothers, collateralized debt obligation, commoditize, company town, corporate governance, corporate social responsibility, creative destruction, credit crunch, crowdsourcing, David Brooks, David Ricardo: comparative advantage, disintermediation, disruptive innovation, do well by doing good, don't be evil, Donald Trump, Edward Glaeser, Exxon Valdez, financial deregulation, Ford Model T, Frederick Winslow Taylor, future of work, George Gilder, global supply chain, Golden arches theory, hobby farmer, industrial cluster, intangible asset, It's morning again in America, job satisfaction, job-hopping, joint-stock company, Joseph Schumpeter, junk bonds, Just-in-time delivery, Kickstarter, knowledge economy, knowledge worker, lake wobegon effect, Long Term Capital Management, low skilled workers, Mark Zuckerberg, McMansion, means of production, Menlo Park, meritocracy, Michael Milken, military-industrial complex, mobile money, Naomi Klein, Netflix Prize, Network effects, new economy, Nick Leeson, Norman Macrae, open immigration, patent troll, Ponzi scheme, popular capitalism, post-industrial society, profit motive, purchasing power parity, radical decentralization, Ralph Nader, recommendation engine, Richard Florida, Richard Thaler, risk tolerance, Ronald Reagan, science of happiness, scientific management, shareholder value, Silicon Valley, Silicon Valley startup, Skype, Social Responsibility of Business Is to Increase Its Profits, Steve Jobs, Steven Levy, supply-chain management, tacit knowledge, technoutopianism, the long tail, The Soul of a New Machine, The Wealth of Nations by Adam Smith, Thomas Davenport, Tony Hsieh, too big to fail, vertical integration, wealth creators, women in the workforce, young professional, Zipcar

But once he had made enough money to be “free from authority,” as he put it, he turned to academia—he is now a professor at both the Polytechnic Institute of New York University and Oxford University—and to the wider world of punditry. The Black Swan was a quirkily learned polemic against humanity’s hubris about its ability to predict the future. Taleb argued that our minds are wired to deceive us. We like to think that we can predict and control the world. But most of the greatest events, from scientific breakthroughs to global upheavals, are black swans. This tendency is particularly dangerous when it is allied to arrogant bankers and a globalized financial system. Before the global meltdown, the lords of finance liked to boast that the combination of global integration and the development of sophisticated financial models had dramatically reduced volatility.

Before the global meltdown, the lords of finance liked to boast that the combination of global integration and the development of sophisticated financial models had dramatically reduced volatility. Nonsense, said Taleb: while volatility might have declined in the short term, giving the appearance of stability, the world was on the verge of a “Black Swan” of devastating proportions. No sooner had the book hit the bookstores than the black swan flapped its wings. The Internet and the capital markets have both reinforced the third revolutionary force: globalization. Globalization is speeding ahead at a faster pace than at any time since the late nineteenth century.

In 2007–08, problems with arcane securities traded by often obscure financial institutions shook “real” companies to their foundations and threw millions of people out of work. The most famous analyst of the growing uncertainty is Nassim Taleb, whose impeccably timed The Black Swan: The Impact of the Highly Improbable (2007) has become a global best-seller, translated into thirty-one languages, turning its author into the prophet-cum-rock star of the global economic meltdown.8 The product of a prominent and polyglot Lebanese family, Taleb began his career in finance, as a Wall Street trader, including a spell at Lehman Brothers, and as a hedge fund manager. But once he had made enough money to be “free from authority,” as he put it, he turned to academia—he is now a professor at both the Polytechnic Institute of New York University and Oxford University—and to the wider world of punditry.


pages: 147 words: 39,910

The Great Mental Models: General Thinking Concepts by Shane Parrish

Albert Einstein, anti-fragile, Atul Gawande, Barry Marshall: ulcers, bitcoin, Black Swan, colonial rule, correlation coefficient, correlation does not imply causation, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, delayed gratification, feminist movement, Garrett Hardin, if you see hoof prints, think horses—not zebras, index fund, Isaac Newton, Jane Jacobs, John Bogle, Linda problem, mandelbrot fractal, Pepsi Challenge, Philippa Foot, Pierre-Simon Laplace, Ponzi scheme, Richard Feynman, statistical model, stem cell, The Death and Life of Great American Cities, the map is not the territory, the scientific method, Thomas Bayes, Torches of Freedom, Tragedy of the Commons, trolley problem

Something we thought could only happen every 1,000 years might be likely to happen in any given year! This is using false prior information and results in us underestimating the probability of the future distribution being different. _ Taleb, Nassim. The Black Swan: The Impact of the Highly Improbable, 2nd edition. New York: Random House, 2010. Anti-fragility How do we benefit from the uncertainty of a world we don’t understand, one dominated by “fat tails”? The answer to this was provided by Nassim Taleb in a book curiously titled Antifragile. Here is the core of the idea. We can think about three categories of objects: Ones that are harmed by volatility and unpredictability, ones that are neutral to volatility and unpredictability, and finally, ones that benefit from it.

They consistently overestimate their confidence in their probabilistic estimates. (For reference, the general stock market has returned no more than 7% to 8% per annum in the United States over a long period, before fees.) Orders of Magnitude Nassim Taleb puts his finger in the right place when he points out our naive use of probabilities. In The Black Swan, he argues that any small error in measuring the risk of an extreme event can mean we’re not just slightly off, but way off—off by orders of magnitude, in fact. In other words, not just 10% wrong but ten times wrong, or 100 times wrong, or 1,000 times wrong.

This book, and the volumes which will follow, are the books I wish had existed years ago when I started learning about mental models. These are my homage to the idea that we can benefit from understanding how the world works and applying that understanding to keep us out of trouble. The ideas in these volumes are not my own, nor do I deserve any credit for them. They come from the likes of Charlie Munger, Nassim Taleb, Charles Darwin, Peter Kaufman, Peter Bevelin, Richard Feynman, Albert Einstein, and so many others. As the Roman poet Publius Terentius wrote: “Nothing has yet been said that’s not been said before.” I’ve only curated, edited, and shaped the work of others before me. The timeless, broad ideas in these volumes are for my children and their children and their children’s children.


pages: 342 words: 94,762

Wait: The Art and Science of Delay by Frank Partnoy

algorithmic trading, Atul Gawande, behavioural economics, Bernie Madoff, Black Swan, blood diamond, Cass Sunstein, Checklist Manifesto, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, computerized trading, corporate governance, cotton gin, Daniel Kahneman / Amos Tversky, delayed gratification, Flash crash, Frederick Winslow Taylor, George Akerlof, Google Earth, Hernando de Soto, High speed trading, impulse control, income inequality, information asymmetry, Isaac Newton, Long Term Capital Management, Menlo Park, mental accounting, meta-analysis, MITM: man-in-the-middle, Nick Leeson, paper trading, Paul Graham, payday loans, Pershing Square Capital Management, Ralph Nader, Richard Thaler, risk tolerance, Robert Shiller, Ronald Reagan, Saturday Night Live, scientific management, six sigma, social discount rate, Spread Networks laid a new fibre optics cable between New York and Chicago, Stanford marshmallow experiment, statistical model, Steve Jobs, systems thinking, The Market for Lemons, the scientific method, The Wealth of Nations by Adam Smith, upwardly mobile, Walter Mischel, work culture

Eldar Shafir and Richard Thaler, “Invest Now, Drink Later, Spend Never: On the Mental Accounting of Delayed Consumption,” Journal of Economic Psychology 27(5, 2006): 694–712. 3. Nassim Taleb in particular has demonstrated that human beings make all sorts of cognitive mistakes in assessing risk. See Nassim Nicholas Taleb, Fooled by Randomness: The Hidden Role of Chance in Life and Markets (Random House, 2008), and Taleb, The Black Swan. 4. Men appear to be more overconfident than women about their trading: one study shows that men trade 45 percent more than women, which costs them almost a full percentage point in terms of their net annual returns.

The contingency we have not considered seriously looks strange; what looks strange is thought impossible; what is improbable need not be considered seriously.”20 These unconsidered contingencies are what Donald Rumsfeld, the former secretary of defense, referred to as “unknown unknowns.” They are what the economist Frank Knight labeled unquantifiable “uncertainty” (as opposed to risk, which can be measured). Or what Nassim Taleb called “black swans.” Or what the German military theorist Carl von Clausewitz wrote was the inevitability of surprise. Or what Charles Perrow labeled unanticipated “normal accidents.” They are what Socrates meant when he said, “I neither know nor think that I know.”21 For centuries, these leading thinkers and other people we have met in this book have told us not to jump to firm conclusions about the unknown.

But that was just the most recent iteration: the collapse of Enron, the implosion of the hedge fund Long-Term Capital Management, the billions of dollars lost by rogue traders Kweku Adoboli, Jerome Kerviel, Nick Leeson, and others—all of these fiascos have, at their heart, a mistaken reliance on complex math. Nassim N. Taleb has written widely and wisely about the deception in financial models, most notably in his book The Black Swan: The Impact of the Highly Improbable (Random House, 2007). In retrospect, many economic models look absurd. For my college honors thesis, I wrote computer code, using something called “simplicial algorithms,” that was supposed to accurately depict Mexico’s economy.


pages: 312 words: 91,835

Global Inequality: A New Approach for the Age of Globalization by Branko Milanovic

Asian financial crisis, assortative mating, Berlin Wall, bitcoin, Black Swan, Branko Milanovic, Capital in the Twenty-First Century by Thomas Piketty, centre right, colonial exploitation, colonial rule, David Ricardo: comparative advantage, deglobalization, demographic transition, Deng Xiaoping, discovery of the americas, European colonialism, Fall of the Berlin Wall, Francis Fukuyama: the end of history, full employment, Gini coefficient, Gunnar Myrdal, income inequality, income per capita, invisible hand, labor-force participation, liberal capitalism, low skilled workers, Martin Wolf, means of production, military-industrial complex, mittelstand, moral hazard, Nash equilibrium, offshore financial centre, oil shock, open borders, open immigration, Paul Samuelson, place-making, plutocrats, post scarcity, post-industrial society, profit motive, purchasing power parity, Ralph Nader, Robert Solow, Second Machine Age, seigniorage, Silicon Valley, Simon Kuznets, special economic zone, stakhanovite, trade route, transfer pricing, very high income, Vilfredo Pareto, Washington Consensus, women in the workforce

And even in the 1 case out of 100 where we happen to be right, the value of that guess will be considered to result more from pure chance than from any genuine ability to extract from the past and predict the future. These singular events will remain totally outside our predictive ability, just like the appearance of black swans, as popularized in Nassim Taleb’s recent book The Black Swan (2007). And since we cannot believe that they will cease to occur in the future, it simply means that all our predictions will largely be faulty. Although we cannot predict any particular event that might occur in the next century, we can consider some possible scenarios that could change the economic composition of entire continents or even the world: Nuclear war between the United States and Russia or China that could lead to massive destruction and long-lasting radioactive contamination.

As in tennis, a tiny difference in skill level is sufficient to make one person number one in the world, earning millions, and another person number 150, covering the costs out of his own (or more likely his parents’) pocket in order to participate in tournaments. A useful way to visualize the winner-take-all rule is to think of the scalability of different jobs. As Nassim Taleb writes in Black Swan, scalable jobs are those where a person’s same unit of labor can be sold many times over.5 A typical example is that of a top pianist who in the past could sell her ability only to those who would come to listen to her. Then, with the invention of the record player, she could sell it to all who would buy the recordings; today, via the Internet, YouTube, and webcasting, she can sell it to practically the entire globe.

As I discussed in Chapter 2, we see here again that the effects of technological change and globalization cannot be readily separated: the two, while conceptually distinct, go together. Perhaps the most important change will continue to be the increasing number of activities that are scalable. In Black Swan, Taleb gives the examples of a sex-worker and a cook as people whose activities are not scalable. But this is no longer necessarily the case. Entire industries have grown up on the Internet with people advertising their own nudity or teaching cooking, and doing this for thousands of fee-paying viewers simultaneously.6 The point is: technology has tremendously expanded the ability of sex workers, cooks, personal trainers, teachers, and many others to sell their services: a rival good has become nonrival.


Global Catastrophic Risks by Nick Bostrom, Milan M. Cirkovic

affirmative action, agricultural Revolution, Albert Einstein, American Society of Civil Engineers: Report Card, anthropic principle, artificial general intelligence, Asilomar, availability heuristic, backpropagation, behavioural economics, Bill Joy: nanobots, Black Swan, carbon tax, carbon-based life, Charles Babbage, classic study, cognitive bias, complexity theory, computer age, coronavirus, corporate governance, cosmic microwave background, cosmological constant, cosmological principle, cuban missile crisis, dark matter, death of newspapers, demographic transition, Deng Xiaoping, distributed generation, Doomsday Clock, Drosophila, endogenous growth, Ernest Rutherford, failed state, false flag, feminist movement, framing effect, friendly AI, Georg Cantor, global pandemic, global village, Great Leap Forward, Gödel, Escher, Bach, Hans Moravec, heat death of the universe, hindsight bias, information security, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, Kevin Kelly, Kuiper Belt, Large Hadron Collider, launch on warning, Law of Accelerating Returns, life extension, means of production, meta-analysis, Mikhail Gorbachev, millennium bug, mutually assured destruction, Nick Bostrom, nuclear winter, ocean acidification, off-the-grid, Oklahoma City bombing, P = NP, peak oil, phenotype, planetary scale, Ponzi scheme, power law, precautionary principle, prediction markets, RAND corporation, Ray Kurzweil, Recombinant DNA, reversible computing, Richard Feynman, Ronald Reagan, scientific worldview, Singularitarianism, social intelligence, South China Sea, strong AI, superintelligent machines, supervolcano, synthetic biology, technological singularity, technoutopianism, The Coming Technological Singularity, the long tail, The Turner Diaries, Tunguska event, twin studies, Tyler Cowen, uranium enrichment, Vernor Vinge, War on Poverty, Westphalian system, Y2K

But preventing the Challenger disaster would have required, not attending to the problem with the 0-rings, but attending to every warning sign which seemed as severe as the 0-ring problem, without benefit of hindsight. 5 .4 Black Swans Taleb (2005) suggests that hindsight bias and availability bias bear primary responsibility for our failure to guard against what he calls Black Swans. Black Swans are an especially difficult version of the problem of the fat tails: sometimes most of the variance in a process comes from exceptionally rare, exceptionally huge events. Consider a financial instrument that earns $10 with 98% probability, but loses $1000 with 2% probability; it is a poor net risk, but it looks like a steady winner. Taleb (2001) gives the example of a trader whose strategy worked for 6 years without a single bad quarter, yielding close to $80 million - then lost $300 million in a single catastrophe.

The hindsight bias rendered the event too predictable in retrospect, permitting the angry victims to find it the result of 'negligence' such as intelligence agencies' failure to distinguish warnings of AI Qaeda activity amid a thousand other warnings. We learned not to allow hijacked planes to overfly our cities. We did not learn the lesson: 'Black Swans do occur; do what you can to prepare for the unanticipated.' Taleb (2005) writes: It is difficult to motivate people in the prevention of Black Swans . . . Prevention is not easily perceived, measured, or rewarded; it is generally a silent and thankless activity. Just consider that a costly measure is taken to stave off such an event. One can easily compute the costs while the results are hard to determine.

N . 216 Bin Laden, 0. 417-18 biodiversity ix biodiversity cycles 256 biodiversity preservation 20 biological weapons 453-4 difference from other weapons of mass destruction 454-5 use of nanoscale technology 484 Biological Weapons: Limiting the Threat, Lederberg, J. 475 biosecurity threats ix, 22-4 biosphere, destruction of 34, 35 biotechnology 450-2 dual-use challenges 455-8 Luddite apocalypticism 81-2 micro- and molecular biology 458-60 rapidity of progress 454-5 risk management 460, 474-5 DNA synthesis technology 463-4, 465 international regulations 464 multi-stakeholder partnerships 462-3 533 novel pathogens 464-5 oversight of research 460-2 'soft' oversight of research 462 use of nanoscale technology 484 bioterrorism 82, 407, 451-2, 456-7 catastrophic attacks 466-8 infectious disease surveillance 469-70 prevention, inverse cost-benefit analysis 188-9 BioWatch 469 Bird, K. and Sherwin, M . J . 403 Black, F . 301 The Black Book of Communism: Crimes, Terror, Repression, Courtois, S . et a!. 518 Black Death 290, 294, 295 black holes 41 risk from particle accelerators 348-50 The Black Swan: The Impact ofthe Highly Improbable, Taleb, N. 162 Black Swans 94-5, 180 Blair, B. 383-4 blast, nuclear explosions 386 block-assembly operation, nanofactories 497 Blood Music, G. Bear 358 Bomb Scare: The History and Future of Nuclear Weapons, Cirincione, ) . 401 bonobos, evolution 56 Bostrom, N. 103, 121, 1 30, 1 36, 138-9, 318, 512 Anthropic Bias: Observation Selection Effects 141 bottom up climate models 266 botulinum toxin 456 Bovine Spongiform Encephalitis (BSE) 303 brain acceleration of 331 evolution 56-7 gene regulation 58 brain function, gene changes 58, 61 brain scans, value in totalitarianism 5 1 1 brain size, increase 365 Brave New World, Huxley, A. 512 'breakout', technological 360 Brenner, L.A. et a!.


pages: 379 words: 99,340

The Revolt of the Public and the Crisis of Authority in the New Millennium by Martin Gurri

Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, anti-communist, Arthur Eddington, Ayatollah Khomeini, bitcoin, Black Monday: stock market crash in 1987, Black Swan, Burning Man, business cycle, citizen journalism, Climategate, Climatic Research Unit, collective bargaining, creative destruction, crowdsourcing, currency manipulation / currency intervention, dark matter, David Graeber, death of newspapers, disinformation, Eddington experiment, en.wikipedia.org, Erik Brynjolfsson, facts on the ground, Francis Fukuyama: the end of history, Frederick Winslow Taylor, full employment, Great Leap Forward, housing crisis, income inequality, Intergovernmental Panel on Climate Change (IPCC), invention of writing, job-hopping, military-industrial complex, Mohammed Bouazizi, Nate Silver, Occupy movement, Port of Oakland, Republic of Letters, Ronald Reagan, scientific management, Skype, Steve Jobs, the scientific method, The Signal and the Noise by Nate Silver, too big to fail, traveling salesman, University of East Anglia, urban renewal, War on Poverty, We are the 99%, WikiLeaks, Yochai Benkler, young professional

Too Big To Fail: The Inside Story of How Wall Street and Washington Fought To Save the Financial System – And Themselves. Penguin Books, 2009. Sreberny, Annabelle, and Khiabany, Gholam. Blogistan: The Internet and Politics in Iran. I.B. Tauris, 2011. Taleb, Nassim Nicholas. Antifragile: Things That Gain From Disorder. Random House, 2012. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. Random House, 2007. Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. Random House Trade Paperbacks, 2004. Taylor, Frederick Winslow. Principles of Scientific Management. A public domain book, 1911.

[235] Bureau of Labor Statistic’s “How the Government Measures Unmployment,” http://www.bls.gov/cps/cps_htgm.htm. [236] Charles Dickens, Bleak House, Chapter 5: “Telescopic Philanthropy,” http://www.worldwideschool.org/library/books/lit/charlesdickens/BleakHouse/chap4.html. [237] N. N. Taleb, The Black Swan: The Impact of the Highly Improbable (Random House, 2007), 34-35. [238] The most lucid and readable book on networks and small worlds, in my judgment, is still Albert-Laszlo Barabasi’s Linked: How Everything Is Connected to Everything Else and What It Means for Business, Science, and Everyday Life (2002)

Only those blinded by archaic categories will fail to see that that public, once synonymous with “the audience,” is no longer silent, no longer passive – that it has leaped onstage and become a leading actor in the world-historical drama. Yet any feature I might depict in my portrait of the public can be falsified by some example, and any attempt I might make to simplify or personalize the subject will result in caricature and error. The most promising way forward, it seems to me, is to follow N. N. Taleb’s “subtractive knowledge” method of analyzing complex questions. Rather than assert what the public is, I explain what the public is not. This resembles the sculptor’s approach of chipping away at the stone until a likeness emerged, or the bond trader’s formula of identifying safe investments by subtracting risk.[29] Since the public is an unstable and undetermined entity – a complex system – this negative mode of characterizing its behavior is least likely to fall into the fallacy of personification, of inventing some new Marxian-style “class” with a single consciousness and will.


pages: 483 words: 141,836

Red-Blooded Risk: The Secret History of Wall Street by Aaron Brown, Eric Kim

Abraham Wald, activist fund / activist shareholder / activist investor, Albert Einstein, algorithmic trading, Asian financial crisis, Atul Gawande, backtesting, Basel III, Bayesian statistics, Bear Stearns, beat the dealer, Benoit Mandelbrot, Bernie Madoff, Black Swan, book value, business cycle, capital asset pricing model, carbon tax, central bank independence, Checklist Manifesto, corporate governance, creative destruction, credit crunch, Credit Default Swap, currency risk, disintermediation, distributed generation, diversification, diversified portfolio, Edward Thorp, Emanuel Derman, Eugene Fama: efficient market hypothesis, experimental subject, fail fast, fear index, financial engineering, financial innovation, global macro, illegal immigration, implied volatility, independent contractor, index fund, John Bogle, junk bonds, Long Term Capital Management, loss aversion, low interest rates, managed futures, margin call, market clearing, market fundamentalism, market microstructure, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, natural language processing, open economy, Pierre-Simon Laplace, power law, pre–internet, proprietary trading, quantitative trading / quantitative finance, random walk, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, road to serfdom, Robert Shiller, shareholder value, Sharpe ratio, special drawing rights, statistical arbitrage, stochastic volatility, stock buybacks, stocks for the long run, tail risk, The Myth of the Rational Market, Thomas Bayes, too big to fail, transaction costs, value at risk, yield curve

This may seem like an obvious insight, and perhaps it is. But many people disagree. A common approach by quantitative professionals is to deal only with the first kind of analysis, based on the assumption that events you know nothing about shouldn’t affect your decisions. At the other extreme, Nassim Taleb in Fooled by Randomness and The Black Swan has argued that only the second kind of analysis matters; the first is fraudulent, because long-term outcomes are dominated by unexpected, high-impact events. A more popular but less intellectual version of Nassim’s argument is to make choices according to whim or tradition or gut instinct because careful analysis and planning seem to fail so often.

By that logic I had to regretfully omit my other books (but they’re great). In addition, I have picked mostly recent books and relatively obscure books. The classics everyone likes are easy to find. I start with the books that take on the subject of Red-Blooded Risk most directly. Nassim Taleb is best known for his Black Swan, but his earlier book, Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets, tackles many of the same issues as my book, with somewhat different results. We more or less agree on the problem, but go in opposite directions to find solutions. A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber comes at things from a third direction.

See also Probability betting/probability and foundation of frequentism and in history/law “prior beliefs” and risk defining capital technology startups and Beat the Dealer (Thorp) Beat the Market (Thorp and Kassouf) Behavioral Game Theory (Camerer) Bennet, Rick Bernoulli, Jakob Berns, Gregory Bernstein, Peter Betting: Kelly bets probability and public sports Beyond Counting (Grosjean) Beyond Individual Choice (Bacharach) Big Short, The (Lewis) Black, Alethea Black, Fischer Black-Scholes-Merton model Black Swan, The (Taleb) Black Wednesday Bloom, Murray Teigh Bogle, John Bond ratings Bookstaber, Richard Born Losers (Sandage) Bounds of Reason, The (Gintis) Brenner, Reuven and Gabrielle Bringing Down the House (Mezrich) British Treasury Broke, (Adams) Bronze Age Bronze Age Economics (Earle) Bubble investors Bulls, Bears, and Brains (Leitzes) Burton, Robert Alan Business Cycles and Equilibrium (Black) Busting Vegas (Mezrich) Calvet, Laurent E.


pages: 654 words: 191,864

Thinking, Fast and Slow by Daniel Kahneman

Albert Einstein, Atul Gawande, availability heuristic, Bayesian statistics, behavioural economics, Black Swan, book value, Cass Sunstein, Checklist Manifesto, choice architecture, classic study, cognitive bias, cognitive load, complexity theory, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, delayed gratification, demand response, endowment effect, experimental economics, experimental subject, Exxon Valdez, feminist movement, framing effect, hedonic treadmill, hindsight bias, index card, information asymmetry, job satisfaction, John Bogle, John von Neumann, Kenneth Arrow, libertarian paternalism, Linda problem, loss aversion, medical residency, mental accounting, meta-analysis, nudge unit, pattern recognition, Paul Samuelson, peak-end rule, precautionary principle, pre–internet, price anchoring, quantitative trading / quantitative finance, random walk, Richard Thaler, risk tolerance, Robert Metcalfe, Ronald Reagan, Shai Danziger, sunk-cost fallacy, Supply of New York City Cabdrivers, systematic bias, TED Talk, The Chicago School, The Wisdom of Crowds, Thomas Bayes, transaction costs, union organizing, Walter Mischel, Yom Kippur War

“I read one review of that brand and it was excellent. Still, that could have been a fluke. Let’s consider only the brands that have a large number of reviews and pick the one that looks best.” Part 3 Overconfidence The Illusion of Understanding The trader-philosopher-statistician Nassim Taleb could also be considered a psychologist. In The Black Swan, Taleb introduced the notion of a narrative fallacy to describe how flawed stories of the past shape our views of the world and our expectations for the future. Narrative fallacies arise inevitably from our continuous attempt to make sense of the world. The explanatory stories that people find compelling are simple; are concrete rather than abstract; assign a larger role to talent, stupidity, and intentions than to luck; and focus on a few striking events that happened rather than on the countless events that failed to happen.

The difficulties of statistical thinking contribute to the main theme of Part 3, which describes a puzzling limitation of our mind: our excessive confidence in what we believe we know, and our apparent inability to acknowledge the full extent of our ignorance and the uncertainty of the world we live in. We are prone to overestimate how much we understand about the world and to underestimate the role of chance in events. Overconfidence is fed by the illusory certainty of hindsight. My views on this topic have been influenced by Nassim Taleb, the author of The Black Swan. I hope for watercooler conversations that intelligently explore the lessons that can be learned from the past while resisting the lure of hindsight and the illusion of certainty. The focus of part 4 is a conversation with the discipline of economics on the nature of decision making and on the assumption that economic agents are rational.

A coherent story was instantly constructed as you read; you immediately knew the cause of Fred’s anger. Finding such causal connections is part of understanding a story and is an automatic operation of System 1. System 2, your conscious self, was offered the causal interpretation and accepted it. A story in Nassim Taleb’s The Black Swan illustrates this automatic search for causality. He reports that bond prices initially rose on the day of Saddam Hussein’s capture in his hiding place in Iraq. Investors were apparently seeking safer assets that morning, and the Bloomberg News service flashed this headline: U.S. TREASURIES RISE; HUSSEIN CAPTURE MAY NOT CURB TERRORISM.


Succeeding With AI: How to Make AI Work for Your Business by Veljko Krunic

AI winter, Albert Einstein, algorithmic trading, AlphaGo, Amazon Web Services, anti-fragile, anti-pattern, artificial general intelligence, autonomous vehicles, Bayesian statistics, bioinformatics, Black Swan, Boeing 737 MAX, business process, cloud computing, commoditize, computer vision, correlation coefficient, data is the new oil, data science, deep learning, DeepMind, en.wikipedia.org, fail fast, Gini coefficient, high net worth, information retrieval, Internet of things, iterative process, job automation, Lean Startup, license plate recognition, minimum viable product, natural language processing, recommendation engine, self-driving car, sentiment analysis, Silicon Valley, six sigma, smart cities, speech recognition, statistical model, strong AI, tail risk, The Design of Experiments, the scientific method, web application, zero-sum game

Complementarity, F-score, and NLP evaluation. Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC’16), Portorož, Slovenia. 2016:261–266. Taleb NN, Douady R. Mathematical definition, mapping, and detection of (anti)fragility. arXiv. 2012 Aug;arXiv:1208.1189 [q-fin.RM]. Taleb NN, Canetti E, Kinda T, Loukoianova E, Schmieder C. A new heuristic measure of fragility and tail risks: Application to stress testing. IMF Working Papers. 2012 Aug;12. Taleb NN. The black swan: the impact of the highly improbable. 2nd ed. New York: Random House Trade Paperbacks; 2010. Johnson K. Nvidia trains world’s largest Transformer-based language model.

You might even miss that the improvement in that stage of your ML pipeline would provide a considerable return. Such low-probability, high-impact events are commonly referred to in business circles as black swans [127].1 So nonlinearity matters when the significant payoff is missed. Figure 7.6 shows a situation in which local sensitivity analysis misses the convexity. 1 In Europe, it was believed for a long time that all swans were white, until someone traveled far enough to see a black swan. A single black swan, while rare, had a large impact on dispelling this theory. 177 Advanced methods for sensitivity analysis Business Metrics Actual response is convex Assumed response of linear sensitivity analysis Improvement in a single stage of ML pipeline (technical metric) Point x at which the local sensitivity analysis is performed Figure 7.5 Convexity in the ML pipeline’s response.

At a price of the increased complexity of the analysis, global sensitivity analysis could detect the presence of nonlinearity of response. whether the response is linear or if there are indications of convexity/concavity. Details of this technique are explained by Taleb et al. [126]. Figure 7.7 shows the application of that heuristic. Coincidentally, any global sensitivity analysis could apply the same technique (described in the Taleb et al. paper [126]) to detect the nonlinear response. How much do the possible errors in the linear sensitivity analysis matter for your ML pipeline, and does the fact that linear sensitivity analysis could miss convexity mean that you should always perform global sensitivity analysis?


Super Thinking: The Big Book of Mental Models by Gabriel Weinberg, Lauren McCann

Abraham Maslow, Abraham Wald, affirmative action, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, anti-pattern, Anton Chekhov, Apollo 13, Apple Newton, autonomous vehicles, bank run, barriers to entry, Bayesian statistics, Bernie Madoff, Bernie Sanders, Black Swan, Broken windows theory, business process, butterfly effect, Cal Newport, Clayton Christensen, cognitive dissonance, commoditize, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, dark pattern, David Attenborough, delayed gratification, deliberate practice, discounted cash flows, disruptive innovation, Donald Trump, Douglas Hofstadter, Dunning–Kruger effect, Edward Lorenz: Chaos theory, Edward Snowden, effective altruism, Elon Musk, en.wikipedia.org, experimental subject, fake news, fear of failure, feminist movement, Filter Bubble, framing effect, friendly fire, fundamental attribution error, Goodhart's law, Gödel, Escher, Bach, heat death of the universe, hindsight bias, housing crisis, if you see hoof prints, think horses—not zebras, Ignaz Semmelweis: hand washing, illegal immigration, imposter syndrome, incognito mode, income inequality, information asymmetry, Isaac Newton, Jeff Bezos, John Nash: game theory, karōshi / gwarosa / guolaosi, lateral thinking, loss aversion, Louis Pasteur, LuLaRoe, Lyft, mail merge, Mark Zuckerberg, meta-analysis, Metcalfe’s law, Milgram experiment, minimum viable product, moral hazard, mutually assured destruction, Nash equilibrium, Network effects, nocebo, nuclear winter, offshore financial centre, p-value, Paradox of Choice, Parkinson's law, Paul Graham, peak oil, Peter Thiel, phenotype, Pierre-Simon Laplace, placebo effect, Potemkin village, power law, precautionary principle, prediction markets, premature optimization, price anchoring, principal–agent problem, publication bias, recommendation engine, remote working, replication crisis, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, ride hailing / ride sharing, Robert Metcalfe, Ronald Coase, Ronald Reagan, Salesforce, school choice, Schrödinger's Cat, selection bias, Shai Danziger, side project, Silicon Valley, Silicon Valley startup, speech recognition, statistical model, Steve Jobs, Steve Wozniak, Steven Pinker, Streisand effect, sunk-cost fallacy, survivorship bias, systems thinking, The future is already here, The last Blockbuster video rental store is in Bend, Oregon, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Tragedy of the Commons, transaction costs, uber lyft, ultimatum game, uranium enrichment, urban planning, vertical integration, Vilfredo Pareto, warehouse robotics, WarGames: Global Thermonuclear War, When a measure becomes a target, wikimedia commons

This revision would account for the fact that the scenario might represent a black swan event, and that you might therefore be wrong about its probability. One reason that the probability of black swan events may be miscalculated relates to the normal distribution (see Chapter 5), which is the bell-curve-shaped probability distribution that explains the frequency of many natural phenomena (e.g., people’s heights). In a normal distribution, rare events occur on the tails of the distribution (e.g., really tall or short people), far from the middle of the bell curve. Black swan events, though, often come from fat-tailed distributions, which literally have fatter tails, meaning that events way out from the middle have a much higher probability when compared with a normal distribution.

In other words, if there is a chance of financial ruin, you might want to avoid that plan even though on average it would lead to a better financial outcome. One thing to watch out for in this type of analysis is the possibility of black swan events, which are extreme, consequential events (that end in things like financial ruin), but which have significantly higher probabilities than you might initially expect. The name is derived from the false belief, held for many centuries in Europe and other places, that black swans did not exist, when in fact they were (and still are) common birds in Australia. As applied to decision tree analysis, a conservative approach would be to increase your probability estimates of low-probability but highly impactful scenarios like the bankruptcy one.

That person embodies the Shirky principle. You do not want to be that person. Inertia in beliefs and behaviors allows entrenched ideas and organizations to persist for long periods of time. The Lindy effect is the name of this phenomenon. It was popularized by Nassim Taleb in his book Antifragile, which we mentioned in Chapter 1. Taleb explains: If a book has been in print for forty years, I can expect it to be in print for another forty years. But, and that is the main difference, if it survives another decade, then it will be expected to be in print another fifty years. This, simply, as a rule, tells you why things that have been around for a long time are not “aging” like persons, but “aging” in reverse.


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Little Bets: How Breakthrough Ideas Emerge From Small Discoveries by Peter Sims

Alan Greenspan, Amazon Web Services, Black Swan, Clayton Christensen, complexity theory, David Heinemeier Hansson, deliberate practice, discovery of penicillin, endowment effect, fail fast, fear of failure, Frank Gehry, Guggenheim Bilbao, Jeff Bezos, knowledge economy, lateral thinking, Lean Startup, longitudinal study, loss aversion, meta-analysis, PageRank, Richard Florida, Richard Thaler, Ruby on Rails, Salesforce, scientific management, Silicon Valley, statistical model, Steve Ballmer, Steve Jobs, Steve Wozniak, systems thinking, TED Talk, theory of mind, Toyota Production System, urban planning, Wall-E

MIT’s Peter Senge has been a primary contributor to the thinking behind what it takes to build sustainable and learning organizational cultures. This is Senge’s cornerstone book. Taleb, Nassim Nicholas. The Black Swan. New York: Random House, 2007. Academic, researcher, and investor Nassim Taleb’s book is an important reminder of the impact of unlikely events. It’s a thought-provoking intellectual adventure. One of the points that Taleb highlights is that, when operating within a high degree of uncertainty, one should experiment including to find what Taleb calls inadvertent discoveries. Countless innovations have happened this way, including Alexander Fleming’s discovery of penicillin, which he found in a mold that had contaminated another experiment.

., Handbook of Creativity, 168 Stokes, Patricia, Creativity from Constraint, 170–71 Storyboards, 59–62, 70, 145 Strategy and innovation, further readings and resources on, 173–76 Stress Factory, New Brunswick, New Jersey, 1 Subtle controls, 85–86 Summit Partners, 111 SUN Microsystems, 10, 36 Superelaborate storyboards, 43 Surprises, 11 Sutherland, Jeff, 84, 85 Sutton, Robert, 42 Tait, Karen, 157–58 Tait, Richard, 155–58 Takeuchi, Hirotaka, 85–86 Tal Afar, Iraq, 92–94, 103, 150, 159 Taleb, Nassim Nicholas, The Black Swan, 175 Taliban, 25 Technology, 17, 20, 21, 22, 29–32, 83–91, 107–108, 112, 132, 137, 142–46, 153. See also Computers; specific technologies TEDTalks, 165 Thoen, Chris, 62, 63, 135 Thomke, Stefan, Experimentation Matters, 175 3M, 135–36, 138, 140 Tin Toy (film), 145, 146 Today Show (TV show), 125 Toyota, 44 Toyota, Yasuhisa, 81, 82 Toy Story (film), 30, 32, 146 Toy Story 2 (film), 44–45 Toy Story 3 (film), 70 Tushman (Michael L.) and O’Reilly (Charles), Winning Through Innovation, 175–76 Twitter feeds, suggested, 176–78 Tyco, 109 Uncertainty, 16–17 University of Chicago, 7 Up, 71, 105–106 US News & World Report, 78 Valley Forge Military Academy, 91 Vanier, Andre, 89–91 Vanity Fair, 118 Viacom, 146 Vietnam War, 24–25 VMWare, 107 Von Clausewitz, Carl, On War, 176 Von Hippel, Eric, 131–40, 199 The Sources of Innovation, 168 Von Hippel Strategy, 133–40 Walking around, management by, 120–21 Walkman, 108 WALL-E (film), 52, 59 Wallis, Michael, 106 Wall Street, 6 Washington, D.C., 124, 125, 126 Waterfall method, 86–88 Waterman, Bob, In Search of Excellence, 120 Weick, Karl, 141–42, 147, 148, 149–50 West, Kanye, 134 West Point, 22, 24, 91 Wilde, Oscar, 78 Will.i.am, 134 Wired magazine, 108 Wiseman, Richard, 121–24, 129, 152 The Luck Factor, 121 World War II, 25 Worm’s eye view, 104–105 Wozniak, Steve, 108 Wright, Will, 115 Xerox PARC, 12, 108 Yahoo!


pages: 250 words: 64,011

Everydata: The Misinformation Hidden in the Little Data You Consume Every Day by John H. Johnson

Affordable Care Act / Obamacare, autism spectrum disorder, Black Swan, business intelligence, Carmen Reinhart, cognitive bias, correlation does not imply causation, Daniel Kahneman / Amos Tversky, data science, Donald Trump, en.wikipedia.org, Kenneth Rogoff, labor-force participation, lake wobegon effect, Long Term Capital Management, Mercator projection, Mercator projection distort size, especially Greenland and Africa, meta-analysis, Nate Silver, obamacare, p-value, PageRank, pattern recognition, publication bias, QR code, randomized controlled trial, risk-adjusted returns, Ronald Reagan, selection bias, statistical model, The Signal and the Noise by Nate Silver, Thomas Bayes, Tim Cook: Apple, wikimedia commons, Yogi Berra

As the Wall Street Journal noted in an article about coincidences in lottery drawings, “with millions of people choosing numbers in hundreds of lotteries around the world each week, coincidences are bound to happen.”43 Consider the black swan. A few hundred years ago, people assumed that the existence of a black swan was impossible, simply because they hadn’t seen any evidence of one before. But not seeing a black swan doesn’t mean it doesn’t exist, just that we haven’t seen it—yet. Today, a “black swan” event is something that is highly improbable, yet has a massive impact when it occurs; the term was popularized by Nassim Nicholas Taleb, who has written extensively about the topic of uncertainty. Just because it hasn’t happened yet doesn’t mean it can’t—or won’t—happen. Black swans exist.44 ARE YOU SURE?

James Fallows, “When a 1-in-a-Billion Chance of Accident May Not Seem ‘Safe Enough,’”Atlantic website, March 28, 2014, http://www.theatlantic.com/technology/archive/2014/03/when-a-1-in-a-billion-chance-of-accident-may-not-seem-safe-enough/359780/. 43. Carl Bialik, “Odds Are, Stunning Coincidences Can Be Expected,” Wall Street Journal website, updated September 24, 2009, http://www.wsj.com/articles/SB125366023562432131, accessed August 2, 2015. 44. Taleb cites the rise of the Internet and the events of September 11, 2001, as examples of events with black swan characteristics in his book The Black Swan: The Impact of the Highly Improbable, 2nd ed., with a new section: “On Robustness and Fragility” (Incerto), Random House (2010). 45. Brad M. Barber and Terrance Odean, “Trading Is Hazardous to Your Wealth: The Common Stock Investment Performance of Individual Investors,” Journal of Finance LV (April 2, 2000), http://citeseerx.ist.psu.edu/viewdoc/download?

., the total number of votes in a state are aggregated to determine who receives that state’s Electoral College votes) Average—A type of summary statistic (usually the mean, mode, or median) that describes the data in a single metric Big data—Data that’s too big for people to process without the use of sophisticated machinery or computing capacity, given its enormous volume Bivariate relationship—A fancy way of saying that there is a relationship between two (“bi”) variables (“variate”) (e.g., the price of your house is related to the number of bathrooms it has) Black swan event—Something that is highly improbable, yet has a massive impact when it occurs Causation—A relationship where it is determined that one factor causes another factor Cherry-picking—Choosing anecdotal examples from the data to make your point, while ignoring other data points that may contradict it Confidence interval—A way to measure the level of statistical certainty about results; typically expressed as a range of values, the confidence interval tells you the range of values within which you’re likely to see the estimate (assuming, of course, you have a random—and representative—sample) Confidence level—The term we use to determine how confident we are that we’re measuring the data correctly Confirmation bias—The tendency to interpret data in a way that reinforces your preconceptions Correlation—A type of statistical relationship between two variables, usually defined as positive (moving in the same direction) or negative (moving in opposite directions) Data—Information or facts Dependence—When one variable is said to be directly determined by another Deterministic forecast—A forecast for which you determine a precise outcome (e.g., it will rain tomorrow at 9 a.m. at my house) Economic impact—How much something is going to cost in terms of time, money, health, or other resources Estimate—A statistic capturing an inference about a population from a sample of data Everydata—The term we use to describe everyday data External validity—The extent to which the results from your sample can be extended to draw meaningful conclusions about the full population False positive—A situation in which the statistical forecast predicts an untrue outcome (e.g., your credit card company calls you suspecting a recent purchase you actually made was fraudulent) Forecast—A statement about the future; while forecast and prediction may have different meanings to specific groups of people (see chapter 8), we generally use them synonymously unless noted otherwise Forecast bias—The term used to describe when a prediction is consistently high (a positive forecast bias) or low (a negative bias) Inference—The process of making statistical conclusions about the data Magnitude—Essentially, the size of the effect Margin of error—A way to measure statistical uncertainty Mean—What most people think of when you say “average” (to get the mean, you add up all the values, then divide by the number of data points) Median—The middle value in a data set that has been rank ordered Misrepresentation—When data is portrayed in an inaccurate or misleading manner Mode—The data point (or points) most frequently found in your data Observation—Looking at one unit, such as a person, a price, or a day Odds—In statistics, the odds of something happening is the ratio of the probability of an outcome to the probability that it doesn’t occur (e.g., a horse’s statistical odds of winning a race might be ⅓, which means it is probable that the horse will win one out of every three races; in betting jargon, the odds are typically the reverse, so this same horse would have 2–1 odds against, which means it has a ⅔ chance of losing) Omitted variable—A variable that plays a role in a relationship, but may be overlooked or otherwise not included; omitted variables are one of the primary reasons why correlation doesn’t equal causation Outlier—A particular observation that doesn’t fit; it may be much higher (or lower) than all the other data, or perhaps it just doesn’t fall into the pattern of everything else that you’re seeing P-hacking—Named after p-values, p-hacking is a term for the practice of repeatedly analyzing data, trying to find ways to make nonsignificant results significant P-value—A way to measure statistical significance; the lower your p-value is, the less likely it is that the results you’re seeing are due to chance Population—The entire set of data or observations that you want to study and draw inferences about; statisticians rarely have the ability to look at the entire population in a study, although it could be possible with a small, well-defined group (e.g., the voting habits of all 100 U.S. senators) Prediction—See forecast Prediction error—A way to measure uncertainty in the future, essentially by comparing the predicted results to the actual outcomes, once they occur Prediction interval—The range in which we expect to see the next data point Probabilistic forecast—A forecast where you determine the probability of an outcome (e.g., there is a 30 percent chance of thunderstorms tomorrow) Probability—The likelihood (typically expressed as a percentage, fraction, or decimal) that an outcome will occur Proxy—A factor that you believe is closely related (but not identical) to another difficult-to-measure factor (e.g., IQ is a proxy for innate ability) Random—When an observed pattern is due to chance, rather than some observable process or event Risk—A term that can mean different things to different people; in general, risk takes into account not only the probability of an event, but also the consequences Sample—Part of the full population (e.g., the set of Challenger launches with O-ring failures) Sample selection—A potential statistical problem that arises when the way a sample has been chosen is directly related to the outcomes one is studying; also, sometimes used to describe the process of determining a sample from a population Sampling error—The uncertainty of not knowing if a sample represents the true value in the population or not Selection bias—A potential concern when a sample is comprised of those who chose to participate, a factor which may bias the results Spurious correlation—A statistical relationship between two factors that has no practical or economic meaning, or one that is driven by an omitted variable (e.g., the relationship between murder rates and ice cream consumption) Statistic—A numeric measure that describes an aspect of the data (e.g., a mean, a median, a mode) Statistical impact—Having a statistically significant effect of some undetermined size Statistical significance—A probability-based method to determine whether an observed effect is truly present in the data, or just due to random chance Summary statistic—Metric that provides information about one or more aspects of the data; averages and aggregated data are two examples of summary statistics Weighted average—An average calculated by assigning each value a weight (based on the value’s relative importance) NOTES Preface 1.


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The Education of a Value Investor: My Transformative Quest for Wealth, Wisdom, and Enlightenment by Guy Spier

Albert Einstein, Atul Gawande, Bear Stearns, Benoit Mandelbrot, big-box store, Black Swan, book value, Checklist Manifesto, classic study, Clayton Christensen, Daniel Kahneman / Amos Tversky, Exxon Valdez, Gordon Gekko, housing crisis, information asymmetry, Isaac Newton, Kenneth Arrow, Long Term Capital Management, Mahatma Gandhi, mandelbrot fractal, mirror neurons, Nelson Mandela, NetJets, pattern recognition, pre–internet, random walk, Reminiscences of a Stock Operator, risk free rate, Ronald Reagan, South Sea Bubble, Steve Jobs, Stuart Kauffman, TED Talk, two and twenty, winner-take-all economy, young professional, zero-sum game

But I suspect that it’s harder for people like me who flocked to New York from elsewhere and therefore lack the local roots that give emotional stability to people raised there. For outsiders, it’s too easy to get unbalanced by the unbridled appetites—including greed and envy—that financial centers like New York and London can inflame. To borrow a memorable term from Nassim Nicholas Taleb’s book The Black Swan: The Impact of the Highly Improbable, these big cities are “Extremistan.” As we know from various studies, the disparity between our own wealth and our neighbors’ wealth can play a significant role in determining our happiness. If so, then reading about a New York–based multibillionaire like the Blackstone Group’s Stephen Schwarzman may well trigger a destabilizing reaction in my irrational brain.

See also letters to shareholders Aquamarine Chemicals, 42–3 Aquamarine Fund assets reach $50 million, 49–50 and Bear Stearns, 86–7 creation and naming of, 43 cumulative return, 2 and fee structures, 46–7 and financial crisis of 2008–2009, 86–99 investment of net worth in, 46 and Lehman Brothers, 87–8 Ariely, Dan, 102 attention deficit disorder (ADD), 48, 107–8, 155 authenticity, 33, 42, 63, 66–7, 76, 81, 84, 132 Bak, Per, 105 Bank of America, 126–7 Bear Stearns, 86–7 behavioral finance, 60, 102–9, 115, 117–18, 125, 135–8, 140–1, 143, 147–50, 154, 191 behaviorism, 28 Benello, Allen, 112, 144 Berkshire Hathaway, 46, 59, 82, 142, 192 annual meetings, 41, 61, 71–2, 178 annual reports, 38–9, 63, 142 and Buffett’s salary, 73, 116 as a company rather than a fund, 94–5 decentralized structure of, 81 holdings, 40–1, 78, 125, 137, 153 and the tech bubble, 71 textile operations, 17–18 See also Buffett, Warren Bernanke, Ben, 87 Bettger, Frank, 6 Bill and Melinda Gates Foundation, 78, 185 Black Swan: The Impact of the Highly Improbable, The (Taleb), 109 Blodget, Henry, 17 Bloomberg terminal/monitor, 2, 52, 87, 116–19, 135–6, 146 Blumkin, Rose, 41–2, 177 Bogdanor, Vernon, 25 Bond Markets, Analysis and Strategies (Fabozzi), 18–19 Bosanek, Debbie, 82, 176, 181 Boulder Brands, 167–70 Brandt, Jonathan, 144, 178 Braxton Associates, 28–9 bridge, 122, 124–8, 130 Brookfield Office Properties, 97–8 Buffett, Howard, 116 Buffett, Susan, 75, 79, 174–5 Buffett, Warren, 37, 53, 55, 90 annual Berkshire salary, 73, 116 and bridge, 124 on debt, 93 father of, 116 on fear, 85 and fee structures, 46–7, 67, 74 and financial crisis of 2008–2009, 90 on first rule of investing, 52 generosity of, 115, 175–6, 178–9, 185 guest talk at HBS, 28–30, 42 and the “inner/outer scorecard,” 26, 65, 80–1 integrity of, 36 and investment decisions, 17–18, 24, 53, 90, 127, 136–7, 148, 165 on learning from mistakes, 2 Letters to Shareholders, 39, 63, 93 as life-long learner, 29–30 on love, 175 Lowenstein’s biography of, 19, 30, 63, 116, 142 lunch with, 1–2, 22, 69–84, 98 and management, 110–11, 163 mistakes of, 17–18, 153 office of, 35, 95, 111–17, 143 playfulness of, 116, 121–2, 131 preface to The Intelligent Investor, 19, 30 on reputation, 18 as role model, 39–40, 46, 63, 71, 83, 96, 113, 115–16, 122, 176 Schroeder’s biography of, 83, 142 “The Superinvestors of Graham-and-Doddsville,” 37, 82 “Too Hard” box of, 116, 170, 180 and wealth, 78, 82, 188 See also Berkshire Hathaway Buffett: The Making of an American Capitalist (Lowenstein), 19, 30, 63, 116, 142 Buffett-Pabrai Way of doing business, 171–85 Burlington Coat Factory, 36 Burlington Northern Santa Fe, 137 Burns, C.

For example, the proximity of so much extreme wealth might make it more tempting for me to swing for the fences with my investments instead of focusing calmly on making a decent compounded return without undue risk. For me at least, it seemed wiser to live in a place where the differences are less extreme. Given my particular set of flaws and vulnerabilities, I figured that I would stand a better chance of operating somewhat rationally in the kind of place that Taleb describes as “Mediocristan,” where life is more mundane. So I started actively to consider alternatives to Manhattan. For a while, I thought seriously of moving to Omaha, given how well it had worked for Warren. I also considered Irvine, California, where Mohnish lives. I contemplated other American cities like Boston, Grand Rapids, and Boulder.


pages: 396 words: 117,149

The Master Algorithm: How the Quest for the Ultimate Learning Machine Will Remake Our World by Pedro Domingos

Albert Einstein, Amazon Mechanical Turk, Arthur Eddington, backpropagation, basic income, Bayesian statistics, Benoit Mandelbrot, bioinformatics, Black Swan, Brownian motion, cellular automata, Charles Babbage, Claude Shannon: information theory, combinatorial explosion, computer vision, constrained optimization, correlation does not imply causation, creative destruction, crowdsourcing, Danny Hillis, data is not the new oil, data is the new oil, data science, deep learning, DeepMind, double helix, Douglas Hofstadter, driverless car, Erik Brynjolfsson, experimental subject, Filter Bubble, future of work, Geoffrey Hinton, global village, Google Glasses, Gödel, Escher, Bach, Hans Moravec, incognito mode, information retrieval, Jeff Hawkins, job automation, John Markoff, John Snow's cholera map, John von Neumann, Joseph Schumpeter, Kevin Kelly, large language model, lone genius, machine translation, mandelbrot fractal, Mark Zuckerberg, Moneyball by Michael Lewis explains big data, Narrative Science, Nate Silver, natural language processing, Netflix Prize, Network effects, Nick Bostrom, NP-complete, off grid, P = NP, PageRank, pattern recognition, phenotype, planetary scale, power law, pre–internet, random walk, Ray Kurzweil, recommendation engine, Richard Feynman, scientific worldview, Second Machine Age, self-driving car, Silicon Valley, social intelligence, speech recognition, Stanford marshmallow experiment, statistical model, Stephen Hawking, Steven Levy, Steven Pinker, superintelligent machines, the long tail, the scientific method, The Signal and the Noise by Nate Silver, theory of mind, Thomas Bayes, transaction costs, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, white flight, yottabyte, zero-sum game

Outside of AI and cognitive science, the most common objections to machine learning are variants of this claim. Nassim Taleb hammered on it forcefully in his book The Black Swan. Some events are simply not predictable. If you’ve only ever seen white swans, you think the probability of ever seeing a black one is zero. The financial meltdown of 2008 was a “black swan.” It’s true that some things are predictable and some aren’t, and the first duty of the machine learner is to distinguish between them. But the goal of the Master Algorithm is to learn everything that can be known, and that’s a vastly wider domain than Taleb and others imagine. The housing bust was far from a black swan; on the contrary, it was widely predicted.

., 138–139 Baldwin effect, 139, 140, 304 Bandit problems, 129–130 Barto, Andy, 221 Bayes, Thomas, 144–145 Bayesian learning, 166–170, 174–175 Bayesian methods, cell model and, 114 Bayesian model averaging, 166–167 Bayesian models, tweaking probabilities, 170–173 Bayesian networks, 24, 156–161, 305–306 Alchemy and, 250 gene regulation and, 159 inference problem and, 161–166 Master Algorithm and, 240, 245 relational learning and, 231 Bayesians, 51, 52–53, 54, 143–175 Alchemy and, 253 further reading, 304–305 hidden Markov model, 154–155 If . . . then . . . rules and, 155–156 inference problem, 161–166 learning and, 166–170 logic and probability and, 173–175 Markov chain, 153–155 Markov networks, 170–173 Master Algorithm and, 240–241, 242 medical diagnosis and, 149–150 models and, 149–153 nature and, 141 probabilistic inference and, 52, 53 See also Bayesian networks Bayes’ theorem, 31–32, 52–53, 143–149, 253 Beam search, 135 “Beer and diapers” rule, 69–70 Belief, probability and, 149 Belief propagation, 161–164, 242, 253 Bell Labs, 190 Bellman, Richard, 188, 220 Bellman’s equation, 220 Berkeley, George, 58 Berlin, Isaiah, 41 Bias, 78–79 Bias-free learning, futility of, 64 Bias-variance decomposition, 301 The Bible Code (Drosnin), 72 Big data, 21 A/B testing and, 227 algorithms and, 7 clustering and, 206–207 relational learning and, 232–233 science, machine learning, and, 14–16 scientific truth and, 40 Big-data systems, 258 Bing, 12 Biology, learning algorithms and, 15 Black swans, 38–39, 158, 232 The Black Swan (Taleb), 38 Blessing of nonuniformity, 189 Board games, reinforcement learning and, 219 Bohr, Niels, 178, 199 Boltzmann distribution, 103–104 Boltzmann machines, 103–104, 117, 250 Boole, George, 104, 175 Boolean circuits, 123, 136 Boolean variable, 149 Boosting, 238 Borges, Jorge Luis, 71 Box, George, 151 Brahe, Tycho, 14, 131 Brahe phase of science, 39–40 Brain learning algorithms and, 26–28 mapping, 118 number of connections in, 94–95 reverse engineering the, 52, 302 S curves and, 105 simulating with computer, 95 spin glasses and, 102–103 BRAIN initiative, 118 Breiman, Leo, 238 Brin, Sergey, 55, 227, 274 Bryson, Arthur, 113 Bucket brigade algorithm, 127 Building blocks, 128–129, 134 Buntine, Wray, 80 Burglar alarms, Bayesian networks and, 157–158 Burks, Arthur, 123 Burns, Bob, 206 Business, machine learning and, 10–13 C. elegans, 118 Cajal, Santiago Ramón y, 93–94 Caltech, 170 CancerCommons.org, 261 Cancer cure algorithm for, 53–54 Bayesian learning and, 174 inverse deduction and, 83–85 Markov logic network and, 249 program for (CanceRx), 259–261, 310 Cancer diagnosis, 141 Cancer drugs predicting efficacy of, 83–84 relational learning and models for, 233 selection of, 41–42 CanceRx, 259–261, 310 Capital One, 272 Carbonell, Jaime, 69 Carnap, Rudolf, 175 Cars driverless, 113, 166, 172, 306 learning to drive, 113 Case-based reasoning, 198, 307 Catch Me If You Can (film), 177 Cause and effect, Bayes’ theorem and, 145–149 Cell model of, 114–115 relational learning and workings of, 233 Cell assembly, 94 Cell phone, hidden Markov models and, 155 Centaurs, 277 Central Dogma, 83 Cerebellum, 27, 118 Chance, Bayes and, 145 Chaos, study of, 30 Checkers-playing program, 219 Cholera outbreak, London’s, 182–183 Chomsky, Noam, 36–38 Chrome, 266 Chunking, 223–227, 254, 309 Circuit design, genetic programming and, 135–136 Classes, 86–87, 209, 257 Classifiers, 86–87, 127 Master Algorithm and, 240 Naïve Bayes, 151–153 nearest-neighbor algorithm and, 183 Clinton, Bill, 18 Clustering, 205–210, 254, 257 hierarchical, 210 Cluster prototypes, 207–208 Clusters, 205–210 “Cocktail party” problem, 215 Cognition, theory of, 226 Coin toss, 63, 130, 167–168 Collaborative filtering systems, 183–184, 306–307 Columbus test, 113 Combinatorial explosion, 73–74 Commoner, Barry, 158 Commonsense reasoning, 35, 118–119, 145, 276–277, 300 Complexity monster, 5–6, 7, 43, 246 Compositionality, 119 Computational biologists, use of hidden Markov models, 155 Computers decision making and, 282–286 evolution of, 286–289 human interaction with, 264–267 as learners, 45 logic and, 2 S curves and, 105 as sign of Master Algorithm, 34 simulating brain using, 95 as unifier, 236 writing own programs, 6 Computer science, Master Algorithm and, 32–34 Computer vision, Markov networks and, 172 Concepts, 67 conjunctive, 66–68 set of rules and, 68–69 sets of, 86–87 Conceptual model, 44, 152 Conditional independence, 157–158 Conditional probabilities, 245 Conditional random fields, 172, 306 Conference on Neural Information Processing Systems (NIPS), 170, 172 Conjunctive concepts, 65–68, 74 Connectionists/connectionism, 51, 52, 54, 93–119 Alchemy and, 252 autoencoder and, 116–118 backpropagation and, 52, 107–111 Boltzmann machine and, 103–104 cell model, 114–115 connectomics, 118–119 deep learning and, 115 further reading, 302–303 Master Algorithm and, 240–241 nature and, 137–142 neural networks and, 112–114 perceptron, 96–101, 107–108 S curves and, 104–107 spin glasses and, 102–103 symbolist learning vs., 91, 94–95 Connectomics, 118–119 Consciousness, 96 Consilience (Wilson), 31 Constrained optimization, 193–195, 241, 242 Constraints, support vector machines and, 193–195 Convolutional neural networks, 117–119, 303 Cope, David, 199, 307 Cornell University, Creative Machines Lab, 121–122 Cortex, 118, 138 unity of, 26–28, 299–300 Counterexamples, 67 Cover, Tom, 185 Crawlers, 8–9 Creative Machines Lab, 121–122 Credit-assignment problem, 102, 104, 107, 127 Crick, Francis, 122, 236 Crossover, 124–125, 134–136, 241, 243 Curse of dimensionality, 186–190, 196, 201, 307 Cyber Command, 19 Cyberwar, 19–21, 279–282, 299, 310 Cyc project, 35, 300 DARPA, 21, 37, 113, 121, 255 Darwin, Charles, 28, 30, 131, 235 algorithm, 122–128 analogy and, 178 Hume and, 58 on lack of mathematical ability, 127 on selective breeding, 123–124 variation and, 124 Data accuracy of held-out, 75–76 Bayes’ theorem and, 31–32 control of, 45 first principal component of the, 214 human intuition and, 39 learning from finite, 24–25 Master Algorithm and, 25–26 patterns in, 70–75 sciences and complex, 14 as strategic asset for business, 13 theory and, 46 See also Big data; Overfitting; Personal data Database engine, 49–50 Databases, 8, 9 Data mining, 8, 73, 232–233, 298, 306.

So, provided the conditional independencies hold, no information is lost by switching to the more compact representation. And in this way we can easily compute the probabilities of extremely unusual states, including states that were never observed before. Bayesian networks give the lie to the common misconception that machine learning can’t predict very rare events, or “black swans,” as Nassim Taleb calls them. In retrospect, we can see that Naïve Bayes, Markov chains, and HMMs are all special cases of Bayesian networks. The structure of Naïve Bayes is: Markov chains encode the assumption that the future is conditionally independent of the past given the present. HMMs assume in addition that each observation depends only on the corresponding state.


pages: 309 words: 81,975

Brave New Work: Are You Ready to Reinvent Your Organization? by Aaron Dignan

"Friedman doctrine" OR "shareholder theory", Abraham Maslow, activist fund / activist shareholder / activist investor, adjacent possible, Airbnb, Albert Einstein, autonomous vehicles, basic income, benefit corporation, Bertrand Russell: In Praise of Idleness, bitcoin, Black Lives Matter, Black Swan, blockchain, Buckminster Fuller, Burning Man, butterfly effect, cashless society, Clayton Christensen, clean water, cognitive bias, cognitive dissonance, content marketing, corporate governance, corporate social responsibility, correlation does not imply causation, creative destruction, crony capitalism, crowdsourcing, cryptocurrency, David Heinemeier Hansson, deliberate practice, DevOps, disruptive innovation, don't be evil, Elon Musk, endowment effect, Ethereum, ethereum blockchain, financial engineering, Frederick Winslow Taylor, fulfillment center, future of work, gender pay gap, Geoffrey West, Santa Fe Institute, gig economy, Goodhart's law, Google X / Alphabet X, hiring and firing, hive mind, holacracy, impact investing, income inequality, information asymmetry, Internet of things, Jeff Bezos, job satisfaction, Kanban, Kevin Kelly, Kickstarter, Lean Startup, loose coupling, loss aversion, Lyft, Marc Andreessen, Mark Zuckerberg, minimum viable product, mirror neurons, new economy, Paul Graham, Quicken Loans, race to the bottom, reality distortion field, remote working, Richard Thaler, Rochdale Principles, Salesforce, scientific management, shareholder value, side hustle, Silicon Valley, single source of truth, six sigma, smart contracts, Social Responsibility of Business Is to Increase Its Profits, software is eating the world, source of truth, Stanford marshmallow experiment, Steve Jobs, subprime mortgage crisis, systems thinking, TaskRabbit, TED Talk, The future is already here, the High Line, too big to fail, Toyota Production System, Tragedy of the Commons, uber lyft, universal basic income, WeWork, Y Combinator, zero-sum game

If you don’t have a compelling vision—a dent in the universe beyond shareholder value—your strategies will fall flat. Because how can we win if we don’t know what winning looks like? Thought Starters Wild Swings and Sure Things. His politics and cantankerous demeanor aside, Nassim Nicholas Taleb introduced an extremely valuable concept in his book The Black Swan called the barbell strategy. This financial strategy is named for how it distributes risk—to two extremes: invest 85–90 percent of your assets in extremely safe instruments, and place all of the remainder in highly speculative bets. The reasoning holds that the “sure things” will create a floor for performance, limiting your downside risk, while the “wild swings” will expose you to potentially life-changing gains.

adjacent possible, 189, 201 Administration Industrielle et Générale (Fayol), 24 advice process, 70, 72–73 Afshar, Vala, 119 Agile Manifesto, 19, 89, 182 agility, 19, 20, 28–29 Airbnb, 140, 188, 254 al-Qaeda, 128 Amazon, 61, 86, 88, 89, 104–5, 254, 259, 268 Andreessen, Marc, 256 ants, 106 Apple, 86 Ask Me Anything sessions (AMAs), 135–36 authority, 14, 54, 63, 65–74 Automattic, 120 autonomy, 22, 42, 66–67, 74, 194, 258 Bain Capital, 253 Ballpoint, 199–200 banks, 94, 252 Handelsbanken, 13, 94, 227–28 barbell strategy, 86–87, 105–6 Barksdale, Jim, 59 Basecamp, 68, 69, 120 Bell, Alexander Graham, 103 Benchley, Robert, 39 Beyond Budgeting Institute, 97–98 Bezos, Jeff, 61 B Lab, 249, 259 Black Swan, The (Taleb), 86–87 Blank, Steve, 27 Boman, Pär, 227–28 bonuses, 171–72 boundaries, 193, 196–97 Box, George, 49 Boyd, John, 88 Braintrust, 119–20 Brandeis, Louis D., 22–23 Bridgewater Associates, 152, 153 Brin, Sergey, 136 Brookings Institution, 33 Bryant, Adam, 147 budgets, 25, 26, 27, 94–97, 99–100 Buffer, 130–31, 166, 170 bureaucracy, 26–27, 29, 68, 77, 112, 190, 193, 198, 212, 236 Burning Man, 139, 140 butterfly effect, 45 Buurtzorg, 13, 34–36, 38, 79, 105, 144, 218 Catmull, Ed, 120, 191, 192 centralization and decentralization, 77–79 CEOs, 80, 86, 223 change, 14, 28 authority in, 73–74 changing approach to, 187–91 compensation in, 172 continuous participatory, see continuous participatory change information in, 136 innovation in, 108 mastery in, 161 meetings in, 125 membership in, 149 plan for, 185–87 purpose in, 63 resistance to, 233–34 resources in, 100 strategy in, 91, 92 structure in, 81 workflow in, 116 charity: water, 224–25 Chesky, Brian, 254 Christensen, Clayton, 91, 237 Cointelegraph, 251 Colleague Letter of Understanding (CLOU), 55 commitment, 69, 193–96, 212 communities of practice, 160 compensation, 14, 54, 163–73 competence, 42 competition, 144 complexity, 43–45, 68, 79 Complexity Conscious mindset, 13, 36–37, 43–47, 53, 55–57, 190, 195, 199, 244, 258–59, 267 authority and, 74 compensation and, 173 information and, 137 innovation and, 109 mastery and, 162 meetings and, 126 membership and, 150 purpose and, 64 resources and, 101 strategy and, 90, 92 structure and, 82 workflow and, 117 complex systems, 45 adaptive, 129, 187–88 relationships and interactions in, 45, 140 compliance, 27, 46, 66, 122, 258 Cone, Sarah, 253 confidence, 236 consensus, 70 consent, 70–73, 195 continuity, 193, 218–19 continuous participatory change, 191–219 boundaries in, 193, 196–97 commitment in, 193–96 continuity in, 193, 218–19 criticality in, 193, 216–18 learning by doing in, 230–31 looping in, see looping participation in, 228–29 priming in, 193, 197–201, 236 principles for, 228–34 resistance and, 233–34 scaling of, 234–39 sensing and responding in, 231–32 starting by stopping in, 232–33 starting small in, 229–30 constraints, 46 contribution-based pay, 167 control, locus of, 154, 155 Control Inc., 181–83, 185, 196–97, 219, 220, 222 cooperatives, 250 Cornell University, 42 Corner Office, 147 Corning Inc., 103 corporations: new forms of incorporation, 248–51, 252 see also organizations Creativity, Inc.

To get started, gather a group with as much diversity as you can fit in the room, and ask them to generate as many possible futures or micro scenarios as possible. Cluster them and discuss the factors involved. Discuss what could be done to mitigate or navigate these scenarios. Listen closely for anything that’s too quickly dismissed—the black swans that are overlooked until it’s too late. And remember, we’re not trying to anticipate the future; that’s not Complexity Conscious. We’re trying to create awareness. Readiness. Preparedness. So that when something unexpected happens—and it will—your team is less likely to be surprised. Your OODA loop is short.


pages: 354 words: 105,322

The Road to Ruin: The Global Elites' Secret Plan for the Next Financial Crisis by James Rickards

"World Economic Forum" Davos, Affordable Care Act / Obamacare, Alan Greenspan, Albert Einstein, asset allocation, asset-backed security, bank run, banking crisis, barriers to entry, Bayesian statistics, Bear Stearns, behavioural economics, Ben Bernanke: helicopter money, Benoit Mandelbrot, Berlin Wall, Bernie Sanders, Big bang: deregulation of the City of London, bitcoin, Black Monday: stock market crash in 1987, Black Swan, blockchain, Boeing 747, Bonfire of the Vanities, Bretton Woods, Brexit referendum, British Empire, business cycle, butterfly effect, buy and hold, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, cellular automata, cognitive bias, cognitive dissonance, complexity theory, Corn Laws, corporate governance, creative destruction, Credit Default Swap, cuban missile crisis, currency manipulation / currency intervention, currency peg, currency risk, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, debt deflation, Deng Xiaoping, disintermediation, distributed ledger, diversification, diversified portfolio, driverless car, Edward Lorenz: Chaos theory, Eugene Fama: efficient market hypothesis, failed state, Fall of the Berlin Wall, fiat currency, financial repression, fixed income, Flash crash, floating exchange rates, forward guidance, Fractional reserve banking, G4S, George Akerlof, Glass-Steagall Act, global macro, global reserve currency, high net worth, Hyman Minsky, income inequality, information asymmetry, interest rate swap, Isaac Newton, jitney, John Meriwether, John von Neumann, Joseph Schumpeter, junk bonds, Kenneth Rogoff, labor-force participation, large denomination, liquidity trap, Long Term Capital Management, low interest rates, machine readable, mandelbrot fractal, margin call, market bubble, Mexican peso crisis / tequila crisis, Minsky moment, Money creation, money market fund, mutually assured destruction, Myron Scholes, Naomi Klein, nuclear winter, obamacare, offshore financial centre, operational security, Paul Samuelson, Peace of Westphalia, Phillips curve, Pierre-Simon Laplace, plutocrats, prediction markets, price anchoring, price stability, proprietary trading, public intellectual, quantitative easing, RAND corporation, random walk, reserve currency, RFID, risk free rate, risk-adjusted returns, Robert Solow, Ronald Reagan, Savings and loan crisis, Silicon Valley, sovereign wealth fund, special drawing rights, stock buybacks, stocks for the long run, tech billionaire, The Bell Curve by Richard Herrnstein and Charles Murray, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transfer pricing, value at risk, Washington Consensus, We are all Keynesians now, Westphalian system

A fellow witness was Nassim Taleb, celebrated author of The Black Swan. In the hearing, Taleb and I said Wall Street compensation of “heads I win, tails you lose” design was a contributing factor to the crash. We testified that bankers were grossly overpaid and incentivized to reckless behavior. One free market oriented member of Congress chastised us from his high dais and said our proposals to limit compensation would keep Wall Street from attracting “talent.” Taleb’s answer was priceless: “What talent? These people destroyed ten trillion dollars of wealth.” Taleb was right. Most traders on Wall Street are not super-talented.

Risk in capital markets is an exponential function of scale. Small changes in initial system conditions produce divergent results. System output can be orderly or chaotic. These observations are the scientific basis for what is popularly known as a black swan event. The term “black swan” is used widely to describe any surprising headline even by those who lack a theoretical understanding of the underlying dynamics. Black swan discussion tends to trivialize science with a fatalistic tinge, as if to say “stuff happens.” Stuff doesn’t just happen. Crises emerge because regulators don’t comprehend the statistical properties of the systems they regulate.

The difficulties of replacing trades of a bankrupt counterparty when notional amounts are in the tens of trillions of dollars, represented by thousands of contracts covering underlying instruments in stocks, bonds, commodities, and currencies, spread across the books of scores of subsidiaries and special purpose entities in multitudinous markets around the world, are extraordinary. This is why select banks are too big to fail. A single point of failure collapses the entire system. A crack-up has names like “Tipping Point,” “Black Swan,” and “Minsky Moment” given by sociologists, economists, and media. Those concepts, colorful as they may be, are not science. The dynamics of ruin are best understood using complexity theory, a hard science that offers tools to see collapse coming in advance. The term “complexity” is often used loosely as synonymous with complication or connectedness.


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Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives by Satyajit Das

accounting loophole / creative accounting, Alan Greenspan, Albert Einstein, Asian financial crisis, asset-backed security, Bear Stearns, beat the dealer, Black Swan, Black-Scholes formula, Bretton Woods, BRICs, Brownian motion, business logic, business process, buy and hold, buy low sell high, call centre, capital asset pricing model, collateralized debt obligation, commoditize, complexity theory, computerized trading, corporate governance, corporate raider, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, currency peg, currency risk, disinformation, disintermediation, diversification, diversified portfolio, Edward Thorp, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, financial engineering, financial innovation, fixed income, Glass-Steagall Act, Haight Ashbury, high net worth, implied volatility, index arbitrage, index card, index fund, interest rate derivative, interest rate swap, Isaac Newton, job satisfaction, John Bogle, John Meriwether, junk bonds, locking in a profit, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, Marshall McLuhan, mass affluent, mega-rich, merger arbitrage, Mexican peso crisis / tequila crisis, money market fund, moral hazard, mutually assured destruction, Myron Scholes, new economy, New Journalism, Nick Leeson, Nixon triggered the end of the Bretton Woods system, offshore financial centre, oil shock, Parkinson's law, placebo effect, Ponzi scheme, proprietary trading, purchasing power parity, quantitative trading / quantitative finance, random walk, regulatory arbitrage, Right to Buy, risk free rate, risk-adjusted returns, risk/return, Salesforce, Satyajit Das, shareholder value, short selling, short squeeze, South Sea Bubble, statistical model, technology bubble, the medium is the message, the new new thing, time value of money, too big to fail, transaction costs, value at risk, Vanguard fund, volatility smile, yield curve, Yogi Berra, zero-coupon bond

So, dealers are off to a day at the races, every day. Black swans, black sheep There is a huge number of books on trading secrets. Victor Niederhoffer, an eccentric contrarian investor, chronicled his trading ‘secrets’ in Education of a Speculator. Niederhoffer started in the early 1980s and was managing over $100 million by the late 1990s. His clients included George Soros, he had an impeccable track record, but in 1997 large losses caused his fund to close. It seems his education wasn’t complete. Some trading books take a philosophical approach. Nassim Taleb, a philosopher of trading and quantitative finance, in his celebrated Fooled By Randomness,4 introduced traders to John Stuart Mill’s ‘black swan hypotheses’.

Nassim Taleb, a philosopher of trading and quantitative finance, in his celebrated Fooled By Randomness,4 introduced traders to John Stuart Mill’s ‘black swan hypotheses’. ‘No amount of observations of white swans can allow the inference that all swans are white, but the observation of a single black swan is sufficient to refute that conclusion.’ Traders pondered the significance of this profound statement. The headline in Business Week shortly before Niederhoffer’s fund blew up read: ‘Whatever Voodoo He Uses, It Works.’ Niederhoffer himself once observed that ‘it was inconceivable that anybody would divulge a truly effective get rich scheme for the price of a book’. 05_CH04.QXD 17/2/06 4:22 pm Page 131 4 S h o w m e t h e m o n e y – g re e d l o s t a n d re g a i n e d 131 Trading places Trading is straightforward, you just need to buy at a cheaper price than you sell.

Chapter 4 Show me the money – greed lost and regained 1 Quoted in Francis Wheen (2004) How Mumbo Jumbo Conquered the World; Harper Perennial, London, p. 36. 2 Quoted in Frank Partnoy (2004) Infectious Greed; Owl Books, New York, p. 117. 3 Quoted in Frank Partnoy (2004) Infectious Greed; Owl Books, New York, pp. 117–118. 4 Nassim Taleb (2004) Fooled by Randomness; Texere, New York. 5 22 September 2002 Media Availability en route to Poland. 6 4 June 2002 Department of Defense News Briefing. Chapter 5 The perfect storm – risk mismanagement by the numbers 1 Tanya Styblo Beder ‘The Great Risk Hunt’ (May 1999) The Journal of Portfolio Management, p. 29. 2 Peter Bernstein (1998) Against the Gods: The Remarkable Story of Risk; John Wiley, New York. 3 See ‘The Jorion-Taleb Debate’ (April 1997) Derivatives Strategy, 25. 4 Roger Lowenstein (2002) When Genius Fails: The Rise and Fall of Long-Term Capital Management; Fourth Estate, London, p. 15. 5 For details of Salomon’s Treasury Bond trading scandal, see Nicholas Dunbar (2000) Inventing Money; John Wiley & Sons, Chichester, pp. 110–112; and Roger Lowenstein (2002) When Genius Fails: The Rise and Fall of Long-Term Capital Management; Fourth Estate, London, pp. 19–22; Frank Partnoy (2004) Infectious Greed; Owl Books, New York, pp. 97–109. 6 Quoted by Merton Miller in ‘Trillion Dollar Bet’ (8 February 2000) Nova PBS. 12_NOTES.QXD 17/2/06 4:43 pm Page 323 Notes 323 7 LTCM’s 1997 return is somewhat in dispute.


pages: 176 words: 55,819

The Start-Up of You: Adapt to the Future, Invest in Yourself, and Transform Your Career by Reid Hoffman, Ben Casnocha

Airbnb, Andy Kessler, Apollo 13, Benchmark Capital, Black Swan, business intelligence, Cal Newport, Clayton Christensen, commoditize, David Brooks, Donald Trump, Dunbar number, en.wikipedia.org, fear of failure, follow your passion, future of work, game design, independent contractor, information security, Jeff Bezos, job automation, Joi Ito, late fees, lateral thinking, Marc Andreessen, Mark Zuckerberg, Max Levchin, Menlo Park, out of africa, PalmPilot, Paul Graham, paypal mafia, Peter Thiel, public intellectual, recommendation engine, Richard Bolles, risk tolerance, rolodex, Salesforce, shareholder value, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, social web, Steve Jobs, Steve Wozniak, the strength of weak ties, Tony Hsieh, transaction costs, Tyler Cowen

The Volatility Paradox: Small Fires Prevent the Big Burn In his book The Black Swan, Nassim Taleb writes about the unexpected, rare, high-impact event. The September 11 terrorist attack, the stock market crash in 1987, and the Indian Ocean tsunami in 2004 were black swans. They were impossible to predict beforehand, had a low chance of happening in the first place, and exacted a large impact. Joshua Cooper Ramo, a friend, in his excellent book The Age of the Unthinkable, argues that we should expect to see more black swans in our lifetime. Ramo believes the number of unthinkable disruptions in the world is on the rise in part because we’ve become so globally interconnected that a minor disturbance anywhere can cause disruption everywhere.

So does that mean you should try to avoid those shocks by going into low-volatility careers like health care or teaching? Not necessarily. The way to intelligently manage risk is to make yourself resilient to these shocks by pursuing those opportunities with some volatility baked in. Taleb argues—furthering an argument popularized by ecologists who study resilience—that the less volatile the environment, the more destructive a black swan will be when it comes. Nonvolatile environments give only an illusion of stability: “Dictatorships that do not appear volatile, like, say, Syria or Saudi Arabia, face a larger risk of chaos than, say, Italy, as the latter has been in a state of continual political turmoil since the [Second World War].”5 Ramo explains why: Italy is resilient to dangerous chaos because it has absorbed frequent attacks like “small, controlled burns in a forest, clearing away just enough underbrush to make [them] invulnerable to a larger fire.”6 These small burns strengthen the political system’s capacity to respond to unexpected crises.

., Never Bet the Farm: How Entrepreneurs Take Risks, Make Decisions—and How You Can, Too (San Francisco: Jossey-Bass, 2006), 78. 4. Stephen H. Shore and Raven Saks, “Risk and Career Choice,” Advances in Economic Analysis and Policy 5, no. 1 (2005), http://​www.​bepress.​com/​bejeap/​advances/​vol5/​iss1/​art7 5. Nassim Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2010), 204. 6. Joshua Cooper Ramo, The Age of the Unthinkable: Why the New World Disorder Constantly Surprises Us and What We Can Do About It (New York: Back Bay Books, 2010), 181. 7. Ibid. 8. Aaron B. Wildavsky, Searching for Safety (Piscataway, NJ: Transaction Publishers, 2004), 98.


Systematic Trading: A Unique New Method for Designing Trading and Investing Systems by Robert Carver

asset allocation, automated trading system, backtesting, barriers to entry, Black Swan, buy and hold, cognitive bias, commodity trading advisor, Credit Default Swap, diversification, diversified portfolio, easy for humans, difficult for computers, Edward Thorp, Elliott wave, fear index, fixed income, global macro, implied volatility, index fund, interest rate swap, Long Term Capital Management, low interest rates, margin call, Market Wizards by Jack D. Schwager, merger arbitrage, Nick Leeson, paper trading, performance metric, proprietary trading, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, survivorship bias, systematic trading, technology bubble, transaction costs, Two Sigma, Y Combinator, yield curve

The Greatest Trade Ever, Gregory Zuckerman, 2010, Penguin A great story about a positive skew trade that worked: John Paulson’s bearish bet on mortgage backed securities. Optional reading. The Black Swan, Nassim Taleb, 2008, Penguin A book about unknown unknowns. Taleb’s usual mixture of unique philosophy and market folklore. Interesting, but optional reading. Trading rule fitting Fooled by Randomness, Nassim Taleb, 2001, Penguin A very interesting book on uncertainty in general. Compulsory for anyone who thinks back-testing is worthwhile. Trading rules and forecasts Trading Systems and Methods, 5th Edition, Perry J.

In a speech in 2002 US Secretary of State Donald Rumsfeld identified three kinds of knowledge: known knowns, known unknowns and unknown unknowns. 31. I’ll discuss exactly how you measure recent levels of standard deviation in chapter ten, ‘Position sizing’. If you can’t wait, it’s on page 155. 32. This essentially is the problem that Nassim Taleb discusses in his book The Black Swan. 39 Systematic Trading CONCEPT: VOLATILITY STANDARDISATION One of the most powerful techniques I use in my trading system framework is volatility standardisation. This is adjusting the returns of different assets so that they have the same expected risk. As I discussed above, my standard definition of expected risk is to use an estimate of recent standard deviation.

Thank you for that, and for everything. 301 Index 2001: A Space Odyssey, 19f 2008 crash, 170 Active management, 3 AIG, 2 Algorithms, 175, 199 Alpha, 3, 37, 106, 136 Alternative beta, 3-4 Amateur investors, 4, 6, 16, 48, 177, 210 and lack of diversification, 20 and over-betting, 21 and leverage, 35 and minimum sizes, 102 as day traders, 188 Anchored fitting: see Back-testing, expanding out of sample Annual returns, 178-179 Annualised cash volatility target, 137, 139, 149, 151, 159, 161, 171, 230, 250 Asset allocating investors, 3, 7, 42, 69, 98, 116, 147, 188, 225-244, 259 and Sharpe ratios, 46 and modular frameworks, 96 and the ‘no-rule’ rule, 116, 167, 196, 225, 228 and forecasts, 122-123, 159 and instrument weights, 166, 175, 189, 198-199 and correlation, 170 and instrument diversification multiplier, 175 and rules of thumb, 186 and trading speeds, 190-191, 205 and diversification, 206 Asset classes, 246&f Automation, 18-19 Back-testing, 5, 13-15, 16, 18, 19&f, 28, 53, 64, 67, 87, 113, 122, 146, 170, 182f, 187, 197, 205 and overfitting, 20, 29, 53f, 54, 68, 129f, 136, 145, 187 and skew, 40 and short holding periods, 43 in sample, 54-56 out of sample, 54-56 expanding out of sample, 56-57, 66, 71f, 84, 89f, 167f, 193-194 rolling window, 57-58, 66, 129f and portfolio weights, 69-73 and handcrafting, 85 and correlations, 129, 167&f, 175 and cost of execution, 179 simple and sophisticated, 186 need for mistrust of, 259 See also: Bootstrapping Barclays Bank, 1-2, 11, 31, 114 Barings, 41 Barriers to entry, 36, 43 Behavioural finance, 12 Beta, 3 Bid-Offer spread, 179 Block value, 153-154, 161, 182-183, 214, 219 Bollinger bands, 109 303 Systematic Trading Bond ETFs, 226 Bootstrapping, 70, 75-77, 80, 85-86, 146, 167, 175, 193-194&f, 199, 230, 248, 250 and forecast weights, 127, 205 see also Appendix C BP, 12, 13 Braga, Leda, 26 Breakouts, 109 Buffett, Warren, 37, 42 Calibration, 52-53 Carry, 67, 119, 123, 126, 127-128, 132, 247 and Skew, 119 Koijen et al paper on, 119f Central banks, 36, 103 Checking account value, recommended frequency, 149 Clarke, Arthur C, 19f ‘Close to Open’, 120-121 Cognitive bias, 12, 16, 17, 19-20, 28, 64, 179 and skew, 35 Collective funds, 4, 106, 116, 225 and derivatives, 107 and costs, 181 Commitment mechanisms, 17, 18 Compounding of returns, 143&f Contango: see Carry Contracts for Difference, 106, 181 Contrarians, 45 Corn trading, 247f Correlation, 42, 59f, 63, 68, 70, 73, 104, 107, 122, 129, 131, 167-168, 171 and Sharpe ratios, 64 and trading subsystems, 170 and ETFs, 231 Cost of execution, 179-181, 183, 188, 199, 203 Cost of trading, 42, 68, 104, 107, 174, 178, 181, 230 Credit Default Swap derivatives, 105 Crowded trades, 45 Crude oil futures, 246f Curve fitting: see over-fitting Daily cash volatility target, 137, 151, 158, 159, 161, 162, 163, 172, 175, 217, 218, 233, 254, 262. 270, 271, 217 Data availability, 102, 107 Data mining, 19f, 26-28 Data sources, 43-44 Day trading, 188 Dead cat bounces, 114 Death spiral, 35 DeMiguel, Victor, 743f Derivatives, 35 versus cash assets, 106 Desired trade, 175 Diary of trading, for semi-automatic trader, 219-224 Diary of trading, for asset allocating investor, 234- 244 Diary of trading, for staunch systems trader, 255- 257 Diversification, 20, 42, 44, 73f, 104, 107, 165, 170, 206 and Sharpe ratios, 65f, 147, 165 of instruments rather than rules, 68 and forecasts, 113 Dow Jones stock index, 23 Education of a Speculator, 17 Einstein, 70 Elliot waves, 109 Emotions, 2-3 Equal portfolio weights, 72-73 Equity value strategies, 4, 29, 31 Equity volatility indices, 34, 246, 247 Eurex, 180 Euro Stoxx 50 Index Futures, 179-180, 181, 182, 187-188, 193, 198 Eurodollar, trading recommendation, 247 Exchange rate, 161, 185 Exchange traded funds (ETFs), 4, 106, 183-184, 189, 197, 200, 214, 225, 226-228 holding costs of, 230 daily regearing of, 230f correlations, 231 Exchanges, trading on, 105, 107 Exponentially Weighted Moving Average Crossover 304 Index (EWMAC), 117-123, 126, 127-128, 132, 247 see also Appendix B Human qualities of successful traders, 259-260 Hunt brothers, 17 Fannie Mae and Freddie Mac, 2 Fees, 3 Fibonacci, 37, 109 Forecasts, 110-115, 121-123, 159, 175, 196, 211 scaling of, 112-113, 115, 133 combined, 125-133, 196, 248, 251 weighted average of, 126 and risk, 137 and speed of trading, 178 and turnover, 185 not changing once bet open, 211 see also Appendix D Forecast diversification multiplier, 128-133, 193f, 196, 249, 251 see also Appendix D Foreign exchange carry trading, 36 Fortune’s Formula, 143f FTSE 100 futures, 183, 210 Futures contracts, 181 and block value, 154-155 ‘Ideas First’, 26-27, 52-54, 103, 146 Ilmanen, Antti, 30f Illiquid assets, 198 Index trackers, 106 Inflation, 67 Instrument blocks, 154-155, 175, 182-183, 185, 206 Instrument currency volatility, 182-183, 203, 214 and turnover, 185, 195, 198 Instrument diversification multiplier, 166, 169-170, 171, 173, 175, 201, 206, 215, 229, 232, 253 Instrument forecast, 161, 162 Instrument riskiness, 155, 182 Instrument subsystem position, 175, 233 Instrument weights, 166-167, 169, 173, 175, 189, 198, 201, 202, 203, 206, 215, 229, 253 and Sharpe ratios, 168 and asset allocating investors, 226 and crash of 2008, 244 Gambling, 15, 20 Gaussian normal distribution, 22, 32&f, 39, 111f, 113, 114, 139f German bond futures, 112, 155, 181, 198 Gold, 246f Google, 29 Gross Domestic Product, 1 ‘Handcrafting’, 78-85, 116, 167-168, 175, 194, 199, 230, 248, 259 and over-fitting, 84 and Sharpe ratios, 85-90 and forecast weights, 127, 205 worked example for portfolio weights, 231-232 and allocation for staunch systems traders, 253 Hedge funds, 3, 177 High frequency trading, 6, 16, 30, 36, 180 Holding costs, 181 Housekeeping, daily, 217 for staunch systems traders, 254 Japan, 36 Japanese government bonds, 102, 112, 114, 200 JP Morgan, 156f Kahn, Richard, 42 Kaufman, Perry, 117 Kelly, John, and Kelly Criterion, 143-146, 149, 151 ‘Half-Kelly’ 146-147, 148, 230, 260 Koijen, Ralph, 119 Law of active management, 41-42, 43, 44, 46, 129f and Sharpe ratios, 47 Leeson, Nick, 41 Lehman Brothers, 2, 237 Leverage, 4, 21&f, 35, 95f, 138f, 142-143 and skew, 44-45 and low-risk assets, 103 and derivatives, 106 and volatility targeting, 151 realised leverage, 229 Life expectancy of investor, and risk, 141 305 Systematic Trading Limit orders, 179 Liquidity, 35, 104-105, 107 Lo, Andrew, 60f, 63f Long Term Capital Management (LTCM), 41, 46 Sharpe ratio of, 47 Low volatility instruments, need to avoid, 143, 151, 210, 230, 260 Lowenstein, Roger, 41, 46f Luck, need for, 260 Lynch, Peter, 37 Markowitz, Harry, 70, 72 Maximum number of bets, 215 Mean reversion trading, 31, 43, 45, 52, 213f ‘Meddling’, 17, 18, 19, 21, 136, 260 and forecasts, 115 and volatility targets, 148 Merger arbitrage, 29 Mid-price, 179, 181 Minimum sizes, 102, 107 Modular frameworks, 93, 95-99 Modularity, 5 Momentum, 42, 67, 68, 117 Moving averages, 94, 195, 197 MSCI, 156f Narrative fallacy, 20, 27, 28, 64 NASDAQ futures, 188 Nervousness, need for, 260 New position opening, 218 Niederhoffer, Victor, 17 Odean, Terence, 13, 20f Odysseus, 17 Oil prices, standard deviation of, 211 O’Shea, Colm, 94f Online portfolio calculators, 129f Overbetting, 21 Over the counter (OTC) trading, 105, 106, 107, 183f Overconfidence, 6, 17, 19f, 54, 58, 136 and lack of diversification, 20 and overtrading, 179 306 Over-fitting, 19-20, 27-28, 48, 51-54, 58, 65, 68, 121f, 156, 259 and Sharpe ratios, 46f, 47, 146 avoiding fitting, 67-68 of portfolio weights, 68-69 possibility of in ‘handcrafting’, 84 Overtrading, 179 Panama method, 247&f Passive indexing, 3 Passive management, 3, 4 Paulson, John, 31, 41 Pension funds, 3 ‘Peso problem’, 30&f Position inertia, 173-174, 193f, 196, 198, 217 Position sizing, 94, 153-163, 214 Poundstone, William, 143f Price movements, reasons for, 103, 107 Portfolio instrument position, 173, 175, 218, 254, 256, 257 Portfolio optimization, 70-90, 167 Portfolio size, 44, 178 Portfolio weighted position, 97, 99, 101, 109, 125, 135, 153, 165, 167, 177, 267 and diversification, 170 Price-to-earnings (P/E) ratios 4 Prospect theory, 12-13, 37 and momentum, 117 Quant Quake, the, 46 Raspberry Pi micro computers, 4 Relative value, 30, 43, 44-46, 213f Retail stockbrokers, 4 Risk, 39, 137-148, 170 Risk targeting, 136 Natural risk and leverage, 142 Risk parity investing, 38, 116&f Risk premia, 31, 119 RiskMetrics (TM), 156&f Roll down: see Carry Rolling up profits and losses, 149 Rogue Trader, 41 Rounded target position, 173, 175, 218 Index Rules of thumb, 186, 230 see also Appendix C Rumsfeld, Donald, 39&f Safe haven assets, 34 Schwager, Jack, 94f Self-fulfilling prophecies, 37 Semi-automatic trading, 4, 7, 11f, 18, 19f, 37, 38, 98, 163, 169, 209-224, 259 and portfolio size, 44, 203 and Sharpe ratios, 47, 147-148 and modular frameworks, 95 and trading rules, 109 and forecasts, 114, 122-123, 159 and eyeballing charts, 155, 195, 197, 214 and diversification, 166, 206 and instrument weights, 166, 175, 189 and correlation, 169 and trading subsystems, 169 and instrument diversification multiplier, 171, 175 and rules of thumb, 186 and overconfidence, 188 and stop losses, 189, 192 and trading speeds, 190-192, 205 Sharpe ratios, 25, 31-32, 34, 35, 42, 43, 44, 46-48, 53, 58, 60f, 67, 72, 73, 112, 184, 189, 210, 214, 250, 259 and overconfidence, 54, 136, 151 and rule testing, 59-60, 65 and T-Test, 61-63 and skew, 62f, 66 and correlation, 64 and diversification, 65f difficulty in distinguishing, 74 and handcrafting, 85-90 and factors of pessimism, 90 and risk, 137f, 138 and volatility targets, 144-145, 151 and speed of trading, 178-179, 196, 204 need for conservative estimation of, 195 and asset allocating investors, 225 and crash of 2008, 240 Schatz futures: see German bond futures Shefrin, Hersh, 13&f Short option strategies, 41 Short selling, 30, 37 Single period optimisation, 71, 85, 89 Skew, positive and negative, 32-34, 40-41, 48, 105, 107, 136, 139-141, 247, 259 and liquidity, 36 and prospect theory, 37 and risk, 39, 138 and leverage, 44-45, 142 and Sharpe ratios, 47, 62f, 146 and trend following, 115, 117 and EWMAC, 119 and carry, 119 and V2TX, 250 ‘Social trading’, 4f Soros, George, and sterling, 36f Speed of trading, 41-43, 47, 48, 104, 122, 174f, 177-205, 248 speed limits, 187-189, 196, 198-199, 204, 213, 228, 251, 260 Spread betting, 6, 106, 181, 197, 214 and block value, 154-155 and UK tax, 183f oil example, 214 Spreadsheets, 218 Stamp duty, 181 Standardised cost estimates, 203-205, 210, 226, 230 Standard deviations, 21-22, 31-32, 38, 40, 70, 103, 107, 111f, 129 and skew, 105 and forecasts, 112, 114, 128 recent, 155-158 returns, 167 and standardised cost, 182, 188, 192 and stop losses, 211 Static and dynamic trading, 38, 43, 168, 188 Staunch systems trading, 4, 7, 51-68, 69, 98, 109, 117-123, 167, 245-257 and Sharpe ratios, 46, 146, 189 and forecasts, 110-114, 122-123, 189 and instrument forecast, 161 and instrument weights, 166, 175, 198-199 and correlation, 170 and rules of thumb, 186 and trading speeds, 191-192, 205 307 Systematic Trading and back-testing, 193 and diversification, 206 Stop losses, 94-5, 115, 121f, 137f, 189, 192, 214, 216f, 217, 218 and forecasts, 211-212 and different instruments, 213 and price volatility, 216 Survivorship bias, 29 Swiss franc, 36, 103, 105, 142-143 System parameters, 186 Systematica hedge fund, 26 Taking profits and losses, 13-15, 16-18, 58, 94-95, 149 and trend following, 37 see also Appendix B Taleb, Nassim, 39f, 41 Tax (UK), 106, 183f Technical analysis, 18, 29 Technology bubble of 1999, 35 Templeton, John, 37 The Black Swan, 39f The Greatest Trade Ever, 31f, 41 Thorpe, Ed, 146f Thriftiness, need for, 260 Timing, 2 Too much/little capital, 206, 246f Trading capital, 150-151, 158, 165, 167, 178, 192, 199-202 starting low, 148 reducing, 149 and turnover, 185 daily calculation of, 217 Trading rules, 3-4, 7, 16, 25-26, 78, 95, 97-98, 101, 109, 121, 125, 135, 159, 161, 187, 249, 259 need for small number of, 67-68, 193 Kaufman, Perry’s guide to, 117 and speed of trading, 178, 205 cost calculations for, 204 see also Appendix B Trading subsystems, 98-99, 116, 159, 162, 163, 165, 166, 167&f, 169, 171f, 172, 175-176, 185, 187, 230, 251-252, 260 and correlation, 170 308 and turnover, 196 cost calculations for, 204 Traditional portfolio allocation, 167 Trend following, 28, 30, 37, 45, 47f, 67, 117, 137f, 194f, 212f, 247 and skew, 105, 115, 117, 213 Turnover, 184-186, 195, 197, 198, 205, 228, 260 methods of calculation, 204 back-testing of, 247-248 Twitter, 29 V2TX index, 246, 247, 249 Value at risk, 137 VIX futures, 105 Volatility, 21, 103, 107, 116, 129, 150, 226, 229 and targets, 95, 98, 106, 158, 159, 185 unpredictability of, 45 price volatility, 155-158, 162-163, 189, 196, 197, 200, 205, 214, 228, Appendix D and crash of 2008, 240-244 instrument currency volatility, 158, 161 instrument value volatility, 161, 172, 250 scalars, 159-160, 162, 185, 201, 206, 215, 217, 218, 229 look-back period, 155, 195-197 and speed of trading, 178 Volatility standardisation, 40, 71, 72, 73, 167, 182, 185 and forecasts, 112, 121, 129 and block value, 155 Volatility standardized costs, 247 Volatility targeting, 135-151, 171f, 188, 192, 201f, 213-215, 230, 233, 250, 259 Walk forward fitting: see Back testing, rolling window Weekly rebalancing process, for asset allocating investors, 233 When Genius Failed, 40, 46f Women as makers of investment decisions, 17&f www.systematictrading.org, 234 Zuckerman, Gregory, 31f THANKS FOR READING!


Quantitative Trading: How to Build Your Own Algorithmic Trading Business by Ernie Chan

algorithmic trading, asset allocation, automated trading system, backtesting, Bear Stearns, Black Monday: stock market crash in 1987, Black Swan, book value, Brownian motion, business continuity plan, buy and hold, classic study, compound rate of return, Edward Thorp, Elliott wave, endowment effect, financial engineering, fixed income, general-purpose programming language, index fund, Jim Simons, John Markoff, Long Term Capital Management, loss aversion, p-value, paper trading, price discovery process, proprietary trading, quantitative hedge fund, quantitative trading / quantitative finance, random walk, Ray Kurzweil, Renaissance Technologies, risk free rate, risk-adjusted returns, Sharpe ratio, short selling, statistical arbitrage, statistical model, survivorship bias, systematic trading, transaction costs

But, of course, the returns are not really Gaussian: large losses occur at far higher frequencies than would be predicted by a nice bell-shaped curve. Some people refer to the true distributions of returns as having “fat tails.” What this means is that the probability of an event far, far away from the mean is much higher than allowed by the Gaussian bell curve. These highly improbable events have been called “black swan” events by the author Nassim Taleb (see Taleb, 2007). To handle extreme events that fall outside the Gaussian distribution, we can use our simple backtest technique to roughly estimate what the maximum one-period loss was historically. (The period may be one week, one day, or one hour. The only criterion to use is that you should be ready to rebalance your portfolio according to the Kelly formula at the end of every period.)

Cowles Foundation Discussion Paper No. 1610. Available at: cowles.econ.yale.edu. Schiller, Robert. 2008. “Economic View; How a Bubble Stayed under the Radar.” New York Times, March 2. Available at www.nytimes.com/2008/ 03/02/business/02view.html?ex=1362286800&en=da9e48989b6f937a&ei= 5124&partner=permalink&exprod=permalink. Taleb, Nassim. 2007. The Black Swan: The Impact of the Highly Improbable. Random House. Thaler, Richard. 1994. The Winner’s Curse. Princeton, NJ: Princeton University Press. P1: JYS bib JWBK321-Chan Bibliography September 24, 2008 15:5 Printer: Yet to come 171 Thorp, Edward. 1997. “The Kelly Criterion in Blackjack, Sports Betting, and the Stock Market.”

See Factor models Artificial intelligence, 116 and stock picking, 26–27 B Backtesting, 20, 22, 24, 31–67, 144–148 common pitfalls to avoid, 50–60 data-snooping bias, 52–60 look-ahead bias, 51–52 common platforms, 32–36 Excel, 32 high-end, 35–36 R , 32–34 MATLAB TradeStation, 35 historical databases, finding and using, 36–43 high and low data, use of, 42–43 split and dividend-adjusted data, 36–40 survivorship bias, 40–42 January effect, 144–146 performance measurement, 43–50 strategy refinement, 65–66 transaction costs, 61–65 year-on-year seasonal trending strategy, 146–148 Bank of Montreal, 150 Bayes Net toolbox, 168 Behavioral bias, 108–109 Behavioral finance, 108–111 Beta, 14 Black Monday, 106 “Black swan” events, 105 Bloomberg, 14, 36, 75 Bollinger bands, 23 Brett Steenbarger Trading Psychology, 10 Bright Trading, 70 Business, setting up a, 69–78 choosing a brokerage or proprietary trading firm, 71–75 physical infrastructure, 75–77 structure, 69–71 175 P1: JYS ind JWBK321-Chan October 2, 2008 14:7 176 C C#, 80, 85, 164 C++, 80, 85, 164 Calendar effect.


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Stuffocation by James Wallman

3D printing, Abraham Maslow, Adam Curtis, Airbnb, Alvin Toffler, back-to-the-land, Berlin Wall, big-box store, Black Swan, BRICs, carbon footprint, Cass Sunstein, clean water, collaborative consumption, commoditize, creative destruction, crowdsourcing, David Brooks, Fall of the Berlin Wall, Future Shock, Great Leap Forward, happiness index / gross national happiness, hedonic treadmill, high net worth, income inequality, Intergovernmental Panel on Climate Change (IPCC), James Hargreaves, Joseph Schumpeter, Kitchen Debate, Martin Wolf, mass immigration, McMansion, means of production, Nate Silver, Occupy movement, Paul Samuelson, planned obsolescence, post-industrial society, post-materialism, public intellectual, retail therapy, Richard Florida, Richard Thaler, sharing economy, Silicon Valley, Simon Kuznets, Skype, spinning jenny, Streisand effect, The future is already here, The Signal and the Noise by Nate Silver, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Tyler Cowen, Tyler Cowen: Great Stagnation, World Values Survey, Zipcar

(If you are a dustman with forecasting skill, or know one who has an uncanny ability to know what’s next, please let me know by emailing james@stuffocation.org.) Forecasts Are Not Facts, They Are Maps For Nassim Nicholas Taleb’s dismal view of forecasting, read Nassim Nicholas Taleb, The Black Swan (New York: Penguin, 2007). The story of the turkey is borrowed, as Taleb notes, from the philosopher Bertrand Russell. Using the Past to Tell the Future I am indebted to three sources for this section: Peter N Stearns, “Why Study History?”, American Historical Association, 1998; Nate Silver, The Signal and the Noise (New York: Allen Lane, 2012); and Rob Hyndman, “Why are some things easier to forecast than others?”

And, which is more worrying, what is the point in trying to forecast the future if an expert’s forecasts are no more accurate than a prediction from the proverbial man on the street, no better, you might say, than rubbish? Forecasts Are Not Facts, They Are Maps The author Nassim Nicholas Taleb painted a similarly gloomy picture in his book The Black Swan, especially in a story about a turkey farmer and a turkey. See the world, for a moment, through a turkey’s eyes. Each day, the farmer comes to feed you. For a thousand days or so, he turns up, red bucket in hand, pulling out oats and corn and carrot peelings, sprinkling them on the ground.

You might draw those thousand data points on a graph and extrapolate them to predict that, yes, in fact, your nice, predictable, breakfast-bringing farmer will come out to feed you tomorrow, same as always. But what if the farmer’s long-lost cousins are coming for dinner tomorrow? What if instead of scattering food, he is going to wring your neck? What use would all your data points from the past be then? Life, Taleb says, is like that. No matter how much data we have, the world is unknowable. We can never know what is going to happen in the future. No matter how sure and safe and good things feel, fate might have other plans. It might even wring your neck. What all this tells us is that someone with no special knowledge, dustmen, for instance, can be just as good as people with insider knowledge at predicting the future.


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How to Run a Government: So That Citizens Benefit and Taxpayers Don't Go Crazy by Michael Barber

Affordable Care Act / Obamacare, anti-fragile, Atul Gawande, battle of ideas, Berlin Wall, Black Swan, Checklist Manifesto, collapse of Lehman Brothers, collective bargaining, deep learning, deliberate practice, facts on the ground, failed state, fear of failure, full employment, G4S, illegal immigration, invisible hand, libertarian paternalism, Mark Zuckerberg, Nate Silver, North Sea oil, obamacare, performance metric, Potemkin village, Ronald Reagan, school choice, The Signal and the Noise by Nate Silver, transaction costs, WikiLeaks

Table 17 It therefore makes sense to try to categorize problems by their nature so that systems can improve at diagnosis and learn systematically what the options are for solving different types of problem. Table 17 illustrates, as a start, what could be done. It is just a sketch, but as Nassim Nicholas Taleb’s ‘black swan’ argument makes clear, unexpected events of one sort or another will recur. How much more effectively could government work if it was systematic in identifying the type of problem and the intensity of the response required? Of course, any given problem may involve a number of these characteristics – for instance, poor leadership and poor implementation are likely to go together.

E. (2012), Eisenhower in War and Peace, New York, Random House State of Victoria (2005), Growing Victoria Together Steinberg, J. (2011), Bismarck: A Life, Oxford, Oxford University Press Stevenson, A. (2013), The Public Sector: Managing the Unmanageable, London, Kogan Page Sugden, J. (2012), Nelson: The Sword of Albion, London, Bodley Head Taleb, N. N. (2007), The Black Swan: The Impact of the Highly Improbable, London, Allen Lane — (2012), Antifragile: How to Live in a World We Don’t Understand, London, Allen Lane Taliaferro, J. (2013), All the Great Prizes: The Life of John Hay, from Lincoln to Roosevelt, New York, Simon & Schuster Thaler, R. and Sunstein, C. (2008), Nudge: Improving Decisions About Health, Wealth and Happiness, London, Penguin Timmins, N. (1995), The Five Giants: A Biography of the Welfare State, London, HarperCollins Trewhitt, K. et al (2014), How to Run a Country: A Collection of Essays, London, Reform Tuchman, B. (1990), The March of Folly: From Troy to Vietnam, St Ives, Abacus US Senate Committee on the Budget and Taskforce on Government Performance, Report, 29 October 2009 Wainwright, A. (2007), The Southern Fells, revised edition, London, Frances Lincoln Wales Audit Office (2006), Ambulance Services in Wales Weiss, M. (2014), ‘Government Entrepreneur’ is not an Oxymoron, Cambridge MA, Harvard Business Review Blog Network, 28 March 2014 Whelan, F. (2014), The Learning Challenge, self-published Wiggins, B. (2012), My Time, London, Yellow Jersey Press Williams, J. and Rossiter, A. (2004), Choice: The Evidence, London, Social Market Foundation Wolmar, C. (2013), To the Edge of the World: The Story of the Trans-Siberian Railway, London, Atlantic Books Notes PREFACE 1.

In the Delivery Unit, we were on the way to becoming as obsessive as Dave Brailsford. As Nassim Nicholas Taleb puts it with only slightly less obsession than Brailsford: Your last recourse against randomness is how you act – if you can’t control outcomes, you can control the elegance of your behaviour.6 This kind of obsession with your own processes at a level of detail unlocks the door to irreversibility. Next time someone tells you that leaders should focus on the big picture and leave the detail to subordinates, show them the door. RULE 46 LEARN THE LEARNABLE AND CONTROL THE CONTROLLABLE (obsessively) BUILDING CAPACITY Nassim Nicholas Taleb’s book Antifragile describes how organizations can become more than resilient; they can develop so that they don’t just survive shocks, they benefit from them.


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Adapt: Why Success Always Starts With Failure by Tim Harford

An Inconvenient Truth, Andrew Wiles, banking crisis, Basel III, behavioural economics, Berlin Wall, Bernie Madoff, Black Swan, Boeing 747, business logic, car-free, carbon footprint, carbon tax, Cass Sunstein, charter city, Clayton Christensen, clean water, cloud computing, cognitive dissonance, complexity theory, corporate governance, correlation does not imply causation, creative destruction, credit crunch, Credit Default Swap, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, Dava Sobel, Deep Water Horizon, Deng Xiaoping, disruptive innovation, double entry bookkeeping, Edmond Halley, en.wikipedia.org, Erik Brynjolfsson, experimental subject, Fall of the Berlin Wall, Fermat's Last Theorem, financial engineering, Firefox, food miles, Gerolamo Cardano, global supply chain, Great Leap Forward, Herman Kahn, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jane Jacobs, Jarndyce and Jarndyce, Jarndyce and Jarndyce, John Harrison: Longitude, knowledge worker, loose coupling, Martin Wolf, mass immigration, Menlo Park, Mikhail Gorbachev, mutually assured destruction, Netflix Prize, New Urbanism, Nick Leeson, PageRank, Piper Alpha, profit motive, Richard Florida, Richard Thaler, rolodex, Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, South China Sea, SpaceShipOne, special economic zone, spectrum auction, Steve Jobs, supply-chain management, tacit knowledge, the market place, The Wisdom of Crowds, too big to fail, trade route, Tyler Cowen, Tyler Cowen: Great Stagnation, Virgin Galactic, web application, X Prize, zero-sum game

Lotteries are a zero-sum game – all they do is redistribute existing resources, whereas research and development can make everyone better off. And unlike lottery tickets, bold innovation projects do not have a known payoff and a fixed probability of victory. Nassim Taleb, author of The Black Swan, calls such projects ‘positive black swans’. Whatever we call them, such ventures present us with a headache. They are vital, because the payoff can be so enormous. But they are also frustrating and unpredictable. Usually they do not pay off at all. We cannot ignore them, and yet we cannot seem to manage them effectively either.

.), Virtual History: Alternatives and Counterfactuals (New York: Basic Books, 1997), p. 284. 82 The RAF boasted fewer than 300 Spitfires: McKinstry, Spitfire, pp. 188–9. 82 Predicted that the Luftwaffe’s first week: Roberts, ‘Hitler’s England’, pp. 285–6. 82 It might even have given Germany the lead: Roberts, ‘Hitler’s England’, pp. 310, 320. 82 The prototype cost the government: McKinstry, Spitfire, p. 51, and Lawrence H. Officer, ‘Purchasing power of British pounds from 1264 to present’, MeasuringWorth, 2009, http://www.measuring-worth.com/ppoweruk/ 83 ‘Positive black swans’: Nassim Nicholas Taleb, The Black Swan (New York: Random House, 2007). 85 We should now build: McKinstry, Spitfire, p. 12. 86 He soon discovered some remarkable examples: Richard Dawkins, The Greatest Show on Earth (London: Bantam, 2009), pp. 254–73. 87 Bright ideas emerge from the swirling mix of other ideas: See also Richard Florida, ‘The world is spiky’, The Atlantic Monthly, October 2005, my The Logic of Life (2008), Matt Ridley’s The Rational Optimist (2010) and Steven Johnson’s Where Good Ideas Come From (2010). 87 A playboy politician most famous as a campaigner against lesbianism: McKinstry, Spitfire, pp.17–18. 88 ‘Bloody good cup of tea, Mitchell’: McKinstry, Spitfire, p. 20. 88 ‘It’s either him or me!’

Insightful and clever’ Alex Bellos, author of Alex’s Adventures in Numberland ‘Adapt is a highly readable, even entertaining, argument against top-down design. It debunks the Soviet-Harvard command-and-control style of planning and approach to economic policies and regulations, and vindicates trial-and-error (particularly the error part in it) as a means to economic and general progress. Very impressive!’ Nassim N. Taleb, author of The Black Swan and Fooled by Randomness ‘This is a brilliant and fascinating book – Harford’s range of research is both impressive and inspiring, and his conclusions are provocative. The message about the need to accept failure has important implications, not just for policy making but also for peoples’ professional and personal lives.


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Doing Good Better: How Effective Altruism Can Help You Make a Difference by William MacAskill

barriers to entry, basic income, behavioural economics, Black Swan, Branko Milanovic, Cal Newport, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, clean water, corporate social responsibility, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Edward Jenner, effective altruism, en.wikipedia.org, end world poverty, experimental subject, follow your passion, food miles, immigration reform, income inequality, index fund, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, job automation, job satisfaction, Lean Startup, M-Pesa, mass immigration, meta-analysis, microcredit, Nate Silver, Peter Singer: altruism, power law, public intellectual, purchasing power parity, quantitative trading / quantitative finance, randomized controlled trial, self-driving car, Skype, Stanislav Petrov, Steve Jobs, Steve Wozniak, Steven Pinker, The Future of Employment, The Wealth of Nations by Adam Smith, Tyler Cowen, universal basic income, William MacAskill, women in the workforce

Even in a situation of this sort it is unlikely that the human race would end, however. (the death tolls from disasters form a fat-tailed distribution): A comprehensive overview is given by Anders Sandberg, “Power Laws in Global Catastrophic and Existential Risks,” unpublished paper, 2014. (Nassim Taleb describes these as Black Swans): Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). most people who’ve died in war have died in the very worst wars: Steven Pinker, The Better Angels of Our Nature: Why Violence Has Declined (New York: Viking, 2011). This is what the Skoll Global Threats Fund focuses on: “About Us/Mission & Strategy,” Skoll Global Threats Fund, http://www.skollglobalthreats.org/about-us/mission-and-approach/.

Just as most of the value from aid programs comes from the very best aid programs (which we discussed in chapter three), it’s often the case that most of the expected harm from disasters come from the very worst disasters. (That is: the death tolls from disasters form a fat-tailed distribution. Nassim Taleb describes these as Black Swans: very rare events that have a very great impact.) For example, most people who’ve died in war have died in the very worst wars: of the four hundred wars in the last two hundred years, about 30 percent of deaths were from World War II alone. This means that if we’re concerned by war, we should spend most of our efforts trying to prevent the very largest wars from occurring, or to limit their scope.

academia, careers in, 171–73 accounting careers, 165 actuarial careers, 165 administrative costs of charities, 106, 107–8 advocacy careers, 174–75 Against Malaria Foundation cost effectiveness of, 53 and expected values, 81–82 founder of, 157, 177 funding needs of, 118 GiveWell’s endorsement of, 125, 127, 197 and program implementation, 117 AIDS, 35, 38, 60 aid skeptics/critics on best aid programs, 47 critiques of sums spent, 44 and Easterly, 43 on ineffectiveness of aid, 45–46 ALS Association, 110 Amazon jungle, 138 American Apparel, 128–29, 132 American Cancer Society, 110 Animal Charity Evaluators, 143, 190 animal welfare, 141–43, 189–90 Annan, Kofi, 104 antiretroviral therapy, 52, 52, 53 Apple, 129, 152 automation of jobs, 165 Banerjee, Abhijit, 19 Bangladesh, 128, 130, 131–32 Barré-Sinoussi, Françoise, 171 bed nets and Against Malaria Foundation, 125 cost effectiveness of, 52, 53 and evidence behind claims, 113–14 implementation of, 117 beef consumption, 136, 141, 142 bereavement, 42 Berger, Alexander, 162 Berger, Ken, 40 best aid programs, 47, 50, 52–53 BetaGov, 187 Black Swan events, 98 blindness, 37–38, 47, 61 Bolivia, 130 Books for Africa (BFA), 103–4, 106, 107, 108–9 Borlaug, Norman, 171 Bosch, Carl, 171 Brazil, 130 Brooks, David, 166 Brown, Laura, 89–94, 174 Bunker, John, 63 Burkina Faso, 104, 116, 122 Burma, 130 Bush, Laura, 3, 9 Cambodia, 130 Cameron, David, 90 Cameroon, 104, 123 Canada, homicide rate in, 185 cancer scale of problem, 182 treatment costs and funding, 61–62 carbon dioxide (CO2), 98, 138–40 carbon dioxide equivalent (CO2eq), 97, 135, 136 carbon footprint, 135–40 career choices, 147–78 and altruistic motivation, 166–67 and building career capital, 157, 158, 173 and career coaching, 199 and doctoral studies, 167–68 and entrepreneurship, 168–71 and exploration value, 158–59 and following one’s passion, 149–53, 154 and impact on later career, 158–60 and impact on the job, 155–57 and job satisfaction, 151 in later life, 176–77 and law of diminishing returns, 62–66 in medicine, 55–56, 62–66, 74–75, 164 and outsourcing or automation of jobs, 165 and personal fit, 148–55, 181 in politics and advocacy, 89–94, 174–75 with for-profit companies, 163 in research, 171–73 and skill building, 167–68 and volunteering, 175–76 working for effective organizations, 162–63 See also earning to give Case, Steve and Jean, 2–3 Case Foundation, 5, 9 cash transfers to aid recipients, 106, 111, 113, 115–16, 122 cattle, 141–42 Causevox.com, 198 Center for Global Development, 189 Centre for Effective Altruism, 180 Centre for the Study of Existential Risk, 194 CEOs of charities, 106, 107–8 Charity Navigator, 40, 105–7 Charity Science, 198–99 CheatNeutral.com, 140 chickens, 141–42, 143, 189–90 Child Labor Deterrence Act, 131–32 child workers, 131–32 China’s earthquake disaster of 2008, 59–60 Clemens, Michael, 188 climate change between 2 to 4°C, 190–91 catastrophic climate change, 191–92 evaluation of cause, 195 and expected values, 95–99 severity of, 179 Climate Works, 191, 193 Clinton, Bill, 3, 9 Cochrane Collaboration, 70–74 coffee, 133 Colgate Palmolive, 2, 5 Colorado, 86 condom promotion, 52, 52, 53 consumerism, ethical, 128–46 and fair-trade products, 132–35 and food choices, 87–88, 141–43, 189–90 and green living, 135–40 and moral licensing, 144–46 and sweatshop laborers, 129–32 Cool Earth, 138–40, 191, 193, 197 Costa Rica, 133 cost effectiveness and evaluation of aid programs, 109, 110–13, 119–20 in poor vs. rich countries, 62, 121 costs associated with saving a life, 54 cows, 141–42 Cramer, Christopher, 134 criminality, 70–74 criminal justice reform, 185–87, 194 dairy, 136 Dead Aid (Moyo), 43 deforestation, 138–40 dehydration, 112 Democratic Republic of the Congo, 104, 123, 191 depression, 35 Development Media International (DMI) cost effectiveness of, 111–13, 119–20 and evidence behind claims, 115–17, 119–20 financial overview of, 106, 108 founder of, 157 funding needs of, 118–19 GiveWell’s endorsement of, 122–23, 127, 197 implementation of, 117–18 mission of, 104 deworming school children, 8–9, 51, 51 Deworm the World Initiative cost effectiveness of, 9, 11, 123–24 founder of, 157 GiveWell’s endorsement of, 9, 123–24, 127, 197 dialysis, 38 diamonds paradox, 57 diarrhea deaths associated with, 47, 112 and effectiveness of aid programs, 121 disasters and disaster relief and effective uses of funding, 120 expected harm from disasters, 98 and law of diminishing returns, 58–61 Disney, 129 District of Columbia, 87 doctoral studies, 167–68 doctors as career choice, 64–66, 74–78 and lives saved, 63–66, 74–75 Doctors Without Borders, 30–31 Duflo, Esther, 19 Durbin, Drew, 170 earning to give and altruistic motivation, 166 and career choices, 74–78, 162, 163–67 and Giving Pledge, 166 political career compared to, 90, 93 earthquakes, 58–59 Easterly, William, 43, 47 economic empowerment aid programs, 121 economic perspectives on climate change, 97–98 economics degrees, 172 Edlin, Aaron, 85 education and attendance, 51, 51 best programs for, 50 and deworming programs, 8–9, 51, 51 testing effectiveness of programs benefiting, 7–9 and textbook availability, 7, 108 effective altruism and choosing causes to support, 32–33 community of, 198 definition of, 11–12 five key questions of, 13 telling others about, 198–99 effectiveness of aid programs and aid skeptics, 46–47 cost effectiveness compared to, 110–11 definition of, 12 and financial health of charities, 107–8 and regression to the mean, 73–74 of Scared Straight program, 70–74 See also cost effectiveness 80,000 Hours organization, 13, 153, 173, 199 80/20 rule, 49 Eldering, Grace, 171 electricity, 135, 136 Eliasch, Johan, 138 emotional appeal of causes, 9–10, 11, 60–61 employment, 55.


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Black Box Thinking: Why Most People Never Learn From Their Mistakes--But Some Do by Matthew Syed

Abraham Wald, Airbus A320, Alfred Russel Wallace, Arthur Eddington, Atul Gawande, Black Swan, Boeing 747, British Empire, call centre, Captain Sullenberger Hudson, Checklist Manifesto, cognitive bias, cognitive dissonance, conceptual framework, corporate governance, creative destruction, credit crunch, crew resource management, deliberate practice, double helix, epigenetics, fail fast, fear of failure, flying shuttle, fundamental attribution error, Great Leap Forward, Gregor Mendel, Henri Poincaré, hindsight bias, Isaac Newton, iterative process, James Dyson, James Hargreaves, James Watt: steam engine, Johannes Kepler, Joseph Schumpeter, Kickstarter, Lean Startup, luminiferous ether, mandatory minimum, meta-analysis, minimum viable product, publication bias, quantitative easing, randomized controlled trial, selection bias, seminal paper, Shai Danziger, Silicon Valley, six sigma, spinning jenny, Steve Jobs, the scientific method, Thomas Kuhn: the structure of scientific revolutions, too big to fail, Toyota Production System, US Airways Flight 1549, Wall-E, Yom Kippur War

Indeed, in one sense, it would not have even increased the probability of the assertion “water always boils at 100ºC.”8 This point was originally made by the Scottish philosopher David Hume in the eighteenth century, and popularized recently by Nassim Nicholas Taleb, the mathematician and author.9 Taleb has pointed out that you could observe a million white swans, but this would not prove the proposition: all swans are white. The observation of a single black swan, on the other hand, would conclusively demonstrate its falsehood. Failure, then, is hardwired into both the logic and spirit of scientific progress. Mankind’s most successful discipline has grown by challenging orthodoxy and by subjecting ideas to testing.

Gosse, Omphalos: An Attempt to Untie the Geological Knot (Rochester, NY: Scholar’s Choice, 2015). 7. Karl Popper, Conjectures and Refutations. 8. This example is cited in Bryan Magee’s Philosophy and the Real World: An Introduction to Karl Popper (Chicago: Open Court Publishing, 1985). 9. Nassim N. Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Penguin, 2008). 10. Daniel Kahneman and Gary Klein, “Conditions for Intuitive Expertise, Failure to Disagree,” American Psychologist 64, no. 6 (2009): 515–26. 11. Ibid. 12. K. Anders Ericsson (ed.), Development of Professional Expertise: Toward Measurement of Expert Performance and Design of Optimal Learning Environments (New York: Cambridge University Press, 2009). 13.

Architecture is a particularly interesting case, because it is widely believed that ancient buildings and cathedrals, with their wonderful shapes and curves, were inspired by the formal geometry of Euclid. How else could the ancients have built these intricate structures? In fact, geometry played almost no role. As Taleb shows, it is almost certain that the practical wisdom of architects inspired Euclid to write his Book of Elements, so as to formalize what the builders already knew. “Take a look at Vitruvius’ manual, De architectura, the bible of architects, written about three hundred years after Euclid’s Elements,” Taleb writes. “There is little formal geometry in it, and, of course, no mention of Euclid, mostly heuristics, the kind of knowledge that comes out of a master guiding his apprentices . . .


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Humans Are Underrated: What High Achievers Know That Brilliant Machines Never Will by Geoff Colvin

Ada Lovelace, autonomous vehicles, Baxter: Rethink Robotics, behavioural economics, Black Swan, call centre, capital asset pricing model, commoditize, computer age, corporate governance, creative destruction, deskilling, driverless car, en.wikipedia.org, flying shuttle, Freestyle chess, future of work, Google Glasses, Grace Hopper, Hans Moravec, industrial cluster, industrial robot, interchangeable parts, job automation, knowledge worker, low skilled workers, Marc Andreessen, meta-analysis, Narrative Science, new economy, rising living standards, self-driving car, sentiment analysis, Silicon Valley, Skype, social intelligence, Steve Jobs, Steve Wozniak, Steven Levy, Steven Pinker, theory of mind, Tim Cook: Apple, transaction costs, Tyler Cowen

The headline on Bloomberg reflected investors’ apparent aversion to risk: “U.S. Treasuries Rise; Hussein Capture May Not Curb Terrorism.” Within an hour, however, prices had fallen back. So Bloomberg rewrote its headline: “U.S. Treasuries Fall; Hussein Capture Boosts Allure of Risky Assets.” This nonsensical behavior was noted by Nassim Nicholas Taleb in his book The Black Swan, and it gives a tiny glimpse of how deeply embedded in us is the power of story. In this case, the Bloomberg headline writer could not stop himself from seeing a story—a cause-and-effect sequence of events—in the news of that day, and he apparently didn’t care that he told two directly contradictory stories, with a single cause leading to exactly opposite effects.

It was reprinted in Storytelling in Organizations: Why Storytelling is Transforming 21st Century Organizations and Management (Elsevier Butterworth-Heinemann, 2005), pp. 97–133. Research finds that we judge a person’s trustworthiness and likeability in about a tenth of a second . . . Gino, op. cit. (chap. 4, n. 6). This nonsensical behavior . . . Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (Random House, 2007). On the contrary, for centuries the conventional view . . . This is explained in Daniel Kahneman, Thinking, Fast and Slow (Farrar, Straus and Giroux, 2011), p. 76. The Belgian psychologist Albert Michotte . . . Ibid. Daniel Kahneman, the Nobelist who popularized the notions of two separate and distinct modes of thinking . . .

Abelson, Robert, 155 Affectiva, 25, 27 affective computing, 25 Afghanistan, 50, 51, 113, 201 after-action review (AAR), 94–96, 101–6 AI (artificial intelligence), 14 airline crews, 138–39, 140 American Express, 73 Anders, George, 72 Apple, 131, 138, 208 Appletree Answers, 134 Armed Forces Journal, 93 artisans, 15 Associated Press, 20 Autonomy, 17 Average Is Over (Cowen), 30–31 Avon, 204 Azinger, Paul, 117–20 Bair, Sheila, 185–86 Bank of America, 128 Baron-Cohen, Simon, 182, 183, 191 Bartlett, Marian, 27 Barton, Dominic, 42 Battle of 73 Easting, 107–11, 112 Baum, Dan, 51 Bear, Meg, 73 Berry, James, 175 Black Swan, The (Taleb), 148 Blank Slate, The: The Modern Denial of Human Nature (Pinker), 39 Bloomberg News, 148 body language, 51, 52, 56, 129, 136, 147, 187, 189 Boissy, Adrienne, 70–71, 86–88 bonding, 63–64, 153 Bossert, William H., 45 Boyd, John, 95 Boyd, Stowe, 14 brain, 37, 58, 79, 84 and empathizing vs. systemizing, 182–84, 191 and gender differences in focus, 185 handshakes and, 60 left, 24–25, 30, 44–46 neural coupling and, 151–52 oxytocin in, 153–54, 158 right, 25, 30, 44 and scanning vs. focusing, 184–86 social relationships and, 36–40, 57, 64–66 stories and, 147, 157 synchronizing of, 64 technology and, 59 testosterone in, 187–88 brain games, 66 Brennan, Neal, 171 Brown, Donald E., 39, 145 Buffett, Warren, 171 bullying, 84 Bush, Jim, 73 business(es), 122, 175, 204 management of, 74, 189 models for, 58 training in, 97 women leaders of, 184–85 business schools, 196–98 Harvard, 60, 139, 147, 196–97 call centers, 73, 128, 134 Campbell, Chad, 119–20 cancer, 69–70, 154 capital, 13–14 Carnegie Mellon University, 122–24 cars, 30 autonomous, 3, 13, 22, 40 stress-monitoring, 29 Carter, Ashton, 52 Casebeer, William, 157–58 Casey, George, 50–51 Chappelle, Dave, 171 Charoen Pokphand Group, 205 Chatham, Ralph, 52, 100, 102, 103, 107 Chen, Jessie, 23–24 chess, 22, 30–31, 38, 40 Cink, Stewart, 119–20 cities, 172, 191 civil-confinement laws, 33–36 Clearwell, 17 Cleveland Clinic, 70, 86–88, 90, 210 cloth, 10–11 cognitive computing systems, 19 cognitive skills, 59, 65, 89, 134–35 collaborative skills, 72, 121, 174, 176–77, 189–90, 195, 203 see also teams and groups computers: affective computing and, 25 coding of, 184, 211–12 cognitive computing and, 19 creativity in, 161–65, 166, 175 in Desk Set, 7–10 emerging economy and, 183–84 emotion recognition and, 25, 27–28, 79, 125 empathy and, 79–80, 83, 90 estimations of capabilities of, 40–41, 53 group work and, 140 in military training, 111–13 power of, 5–6, 14, 24, 41, 121 Watson, 1–3, 9–10, 18, 19, 161–63, 166 writing by, 19–22, 146–48, 164, 165 Cone, Robert, 23 conformity, 135–36 conversations: gender differences in, 183, 189 in groups, 125, 127, 132 in person, 56–58, 63–66 by phone, 61–63, 67, 82, 173, 174 spoken, 61 by text, 56, 61, 63, 67, 82, 83 cooking, 161–63 Cope, David, 163 Corporate Insight, 19 Country Meadows, 158–59 Cowen, Tyler, 30–31 creativity and innovation, 131, 160, 161–77 in cities, 172 computer-generated, 161–65, 166, 175 empathy and, 175–76 engagement in, 169–71, 74 exploration in, 169, 171, 173 in groups, 169, 170, 176–77 in groups of two, 170–71 human, 165–67, 175–77 interaction and, 167–69 motivation in, 175 real-world problems and, 166–67 as set of skills, 176 trust and, 170–71 Watson and, 161–63 Crick, Francis, 170 Cuckoo’s Calling, The (Galbraith), 165 Curtis, Ben, 119–20 cyborgs, 42 DARPA (Defense Advanced Research Projects Agency), 106, 197, 201–3 storytelling studied by, 156–57 Darwars Ambush, 201–2 Death of Distance, The (Cairncross), 171–72 de Beauvoir, Simone, 170, 171 Deep Blue, 30, 40 dementia, 158–60 Denning, Stephen, 141–47 DePuy, William E., 99, 101 Desk Set, 7–10 digital devices, 55–58 dishwashers, 41 distance, 171–74 Dream On, 134 Dreyfus, Hubert, 40 Drucker, Peter, 49 economics, 133, 172 economies, 11–12, 46, 160, 209, 212, 213 emerging, women in, 125, 178–92 trust and, 64 education, 16, 44–48 online, 197–98 STEM subjects in, 49, 209 student engagement in, 28–29 work and, 16, 47–48 writing and grading software in, 20–22 Education Week, 21 edX, 21 Ekman, Paul, 25–28 Elizabeth I, Queen, 10 Emotient, 25–27 emotions, 25 computers’ reading of, 25, 27–28, 79, 125 contagion of, 76–77 digital devices and, 55–57 empathy and, see empathy facial expressions and, see facial expressions nonverbal cues and, 55–56 oxytocin and, 153 pupil size as clue to, 77–80 reading, 3, 25–30 self-knowledge of, 29–30 touch and, 59–60 empathizers vs. systemizers, 182–84, 191 empathy, 57, 69–70, 129, 140, 207, 209 building, 83–84 in children, 83–84 computers and, 79–80, 83, 90 creativity and, 175–76 decline in, 80–82, 190 definitions of, 71 disorders of, 183 emotional contagion and, 76–77 genuine, two parts of, 89 influence of, 75–76 literary fiction and, 208 medicine and, 69–71, 74–76, 84–90 military and, 91–116, 200, 204 oxytocin and, 153 pupil size and, 77–80 and saying “I understand,” 87–88 as skill, not trait, 89–90, 98 survival and, 78–79 testosterone and, 187–88 as two-way street, 79–80 unconscious and, 78 in work, 71–74 endorphins, 136–37 engagement, 169–72, 174 engineers, 49, 174, 181, 184, 211 executive functions, 65, 66 expert witnesses, 33–36, 53 exploration, 169, 171–73 eyes: eye contact, 56, 181 pupil size in, 77–80 reading, 125, 179–80, 182 F-4 Phantom fighter jet, 91–92 Facebook, 62–63, 83, 130–31 Facial Action Coding System, 26 facial expressions, 25–28, 55–56, 77–79, 125, 147, 187 eyes in, 125, 179–80, 182 pain and, 27–28, 79 factories, 16, 53–54 farming, 14 Female Advantage, The (Helgesen), 184–85 fiction, reading of, 207–8 financial crisis and recession of 2008–2009, 11–12, 47–48, 64, 82, 185–86 financial services, 19 fitness monitors, 164 Fitzgerald, F.


pages: 265 words: 74,000

The Numerati by Stephen Baker

Berlin Wall, Black Swan, business process, call centre, correlation does not imply causation, Drosophila, full employment, illegal immigration, index card, information security, Isaac Newton, job automation, job satisfaction, junk bonds, McMansion, Myron Scholes, natural language processing, off-the-grid, PageRank, personalized medicine, recommendation engine, RFID, Silicon Valley, Skype, statistical model, surveillance capitalism, Watson beat the top human players on Jeopardy!, workplace surveillance

(This type of program detected financial irregularities on the part of New York governor Eliot Spitzer in 2007. The trail of these monies led to the discovery of payments for prostitutes and his resignation in March 2008.) But such tools are useless when it comes to recognizing or predicting something never seen before—the unexpected earth-shaking events that the author Nassim Nicholas Taleb discusses in his book The Black Swan. The second problem is that suspected terrorists, unlike most shoppers or voters, take measures to blur the data signal to cover their tracks. The simplest way is to conduct important business off the network—to hold meetings face to face and send coded messages on paper or committed to the memory of human couriers.

This provides sufficient data to create detailed simulations of launches. And yet during the first quarter-century of shuttle flights, there have been only two disasters. "We have a sample size of two," he said. This makes it difficult to pick out patterns of data that point to problems. [>] Unexpected earth-shaking events. Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, Random House, 2007. Jerry Friedman, a statistics professor at Stanford. See The Mathematical Sciences' Role in Homeland Security: Proceedings of a Workshop, National Academies Press, 2004. [>] Jeff Jonas, like many others. Jonas writes at length about security and privacy challenges surrounding data on his blog, http://www.jeffjonas.typepad.com/. [>] As many as 300 cameras.

Barnes & Noble Books, 2005 (originally published in 1911) * * * Index Accenture (company), [>]–[>], [>]–[>], [>]–[>], [>] Acxiom (company), [>]–[>] AdSense (Google service), [>] Advertisers, [>] calculating rate of return for, [>], [>] changes in methods of, [>]—[>], [>], [>], [>]–[>] customer lists shared by, [>], [>], [>]–[>], [>] and the Internet, [>]–[>], [>]–[>], [>], [>]–[>], [>], [>] microtargeting by, [>], [>], [>] and retail stores, [>]–[>], [>], [>], [>], [>], [>] selling our own data to, [>] See also "Buckets"; Shoppers; "Tribes" African American voters, [>] Age (generations) distinguishing, through word analysis, [>]–[>], [>], [>] on online dating questionnaire, [>]–[>] Alamo Rent A Car, [>]–[>], [>]–[>], [>], [>] Algorithms for analyzing patients, [>], [>], [>] for analyzing shoppers, [>], [>]–[>] for analyzing terrorists, [>]–[>], [>], [>] for analyzing voters, [>], [>], [>] for biological analysis, [>], [>] dating services' use of, [>], [>], [>], [>]–[>], [>], [>] defined, [>]–[>], [>]–[>] as Numerati tool, [>], [>], [>]–[>], [>], [>]–[>], [>], [>]–[>] Alhazmi, Nawaf, [>]–[>] Allen, Paul, [>] AllianceTech (company), [>] Almihdhar, Khalid, [>]–[>] Al Qaeda, [>], [>], [>], [>] Alzheimer's disease, [>], [>], [>], [>], [>] Amazon.com, [>], [>], [>], [>], [>] Andresen, Dan, [>]–[>], [>] ANNA (privacy software), [>] Anthropologists, [>]–[>], [>]–[>], [>], [>], [>] AOL (company), [>]–[>] Applebee's America (Dowd), [>], [>], [>] Arnold, Douglas, [>] Artificial intelligence, [>]–[>] See also Computers; Machine learning ASWORG, [>]–[>] AttentionTrust (company), [>] Baker, Mary Jane and Walter (author's parents), [>]–[>], [>], [>], [>], [>]–[>] Baker, Stephen, [>]–[>], [>]–[>] "Barnacle" shoppers, [>]–[>], [>] "Barn Raisers" tribe, [>], [>], [>], [>], [>], [>], [>] Bartering, [>] Baseball Prospective (website), [>] Baseball statistics, [>]–[>] BBN (company), [>] Bed sensors, [>], [>], [>] Behavior altering, [>]–[>], [>]–[>] predicting, [>], [>]–[>], [>], [>]–[>], [>], [>], [>], [>], [>], [>], [>]–[>], [>]–[>], [>] proxies for, [>], [>]–[>], [>] tracking of cell phone users', [>]–[>] tracking of elderly people's, [>]–[>] tracking of Internet users', [>]–[>], [>]–[>], [>], [>] tracking of terrorists', [>]–[>] tracking shoppers' patterns of, [>]–[>], [>] See also Data; Mathematical models "Behavioral markers," [>] Beltran, Carlos, [>]–[>], [>] Bin Laden, Osama, [>], [>] Biology and biologists, [>], [>], [>], [>], [>], [>], [>]–[>], [>]–[>], [>], [>] See also DNA; Genetics Black, Fischer, [>] The Black Swan (Taleb), [>] Bloggers, [>]–[>] Bluetooth data connections, [>]–[>] "Bootstrapper" tribe, [>]–[>] "Bootstrapping," [>] Brands, [>], [>], [>] Brin, Sergey, [>] Britain, [>] "Buckets," [>]–[>], [>], [>], [>]–[>], [>], [>], [>], [>], [>], [>] See also "Tribes" "Builders" (personality type), [>]–[>] Bush, George W., [>], [>]–[>], [>], [>]–[>], [>], [>] BusinessWeek (magazine), [>], [>] "Butterfly" shoppers, [>], [>] BuzzMetrics (company), [>], [>] Cameras (surveillance) at Accenture, [>], [>]–[>] in casinos, [>]–[>] in homes of the elderly, [>]–[>], [>] in public places, [>], [>], [>]–[>], [>]–[>] See also Facial recognition; Photos; Surveillance Capital IQ, [>], [>] Capital One, [>] Carbonell, Jaime, [>] Carbon nanotube, [>] Carley, Kathleen, [>]–[>] Carnegie Mellon University (CMU), [>], [>]–[>], [>]–[>], [>]–[>], [>] Casablanca (movie), [>] Casinos, [>]–[>], [>] Cavaretta, Michael, [>] Cell phones Bluetooth technology for, [>]–[>] data produced by, [>], [>], [>], [>]–[>] technical issues associated with, [>] tracking use of, [>], [>], [>]–[>] Central Intelligence Agency.


pages: 416 words: 106,582

This Will Make You Smarter: 150 New Scientific Concepts to Improve Your Thinking by John Brockman

23andMe, adjacent possible, Albert Einstein, Alfred Russel Wallace, Anthropocene, banking crisis, Barry Marshall: ulcers, behavioural economics, Benoit Mandelbrot, Berlin Wall, biofilm, Black Swan, Bletchley Park, butterfly effect, Cass Sunstein, cloud computing, cognitive load, congestion charging, correlation does not imply causation, Daniel Kahneman / Amos Tversky, dark matter, data acquisition, David Brooks, delayed gratification, Emanuel Derman, epigenetics, Evgeny Morozov, Exxon Valdez, Flash crash, Flynn Effect, Garrett Hardin, Higgs boson, hive mind, impulse control, information retrieval, information security, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, Jaron Lanier, Johannes Kepler, John von Neumann, Kevin Kelly, Large Hadron Collider, lifelogging, machine translation, mandelbrot fractal, market design, Mars Rover, Marshall McLuhan, microbiome, Murray Gell-Mann, Nicholas Carr, Nick Bostrom, ocean acidification, open economy, Pierre-Simon Laplace, place-making, placebo effect, power law, pre–internet, QWERTY keyboard, random walk, randomized controlled trial, rent control, Richard Feynman, Richard Feynman: Challenger O-ring, Richard Thaler, Satyajit Das, Schrödinger's Cat, scientific management, security theater, selection bias, Silicon Valley, Stanford marshmallow experiment, stem cell, Steve Jobs, Steven Pinker, Stewart Brand, Stuart Kauffman, sugar pill, synthetic biology, the scientific method, Thorstein Veblen, Turing complete, Turing machine, twin studies, Vilfredo Pareto, Walter Mischel, Whole Earth Catalog, WikiLeaks, zero-sum game

The few large-impact technologies (versus slightly incremental advances in technologies) that have occurred in the past ten years are black-swan technologies. In his book The Black Swan, Nassim Taleb defines a black swan as an event of low probability, extreme impact, and only retrospective predictability. Black swans can be positive or negative in their effects and are found in every sector. Still, the most pressing reason I believe black-swan technology to be a conceptual tool that should be in everybody’s cognitive toolkit is simply that the challenges of climate change and energy production we face are too big to be tackled by known solutions and safe bets. I recall fifteen years ago, when we were starting Juniper networks, that there was absolutely no interest in replacing traditional telecommunications infrastructure (ATM was the mantra) with Internet protocols.

., 86–87 Bayesian inference, 70 behavior, ignorance of causes of, 349–52 behavioral sciences, 365–66 belief, 336–37 proof, 355–57 Bell, Alexander Graham, 110 bell curve (Gaussian distribution), 199, 200 benchmarks, 186 bias, 18, 43–45 confirmation, 40, 134 self-serving, 37–38, 40 in technologies, 41–42 biochemical cycles, 170–71 bioengineering, 16 biological ecosystems, 312–14 biological teleology, 4 biology, 234, 312 biophilia, 386 Bird, Sheila, 274 birds, 155, 359 chickens, 62–63, 155 herring gulls, 160 songbirds, 154–55 black box, 303 Blackmore, Sue, 215–17 Black Swan, The (Taleb), 315 black-swan technologies, 314–17 Blake, William, 44 blame, 35–36, 106, 386 blindness, 144 Bloch waves, 297 Boccaletti, Giulio, 184–87 body, life-forms in, 13, 290–91, 292 Boeri, Stefano, 78 Bohr, Niels, 28 Bolyai, János, 109 Bony, Jean, 247–48 Bostrom, Nick, 275–77 bottom-up thinking, 157–59 Boyer, Pascal, 182–83 bradykinesia, 63 brain, 48, 129–30, 148, 149, 150, 158, 172, 346, 347, 389, 394 consciousness and, 217 evolution of, 10, 207, 257 mind and, 364, 366 neurons in, see neurons plasticity of, 250–51 predictive coding and, 132–34 self and, 212 size of, 257 of split-brain patients, 349–50 synapses in, 164 temperament traits and, 229–30 white and gray matter in, 162–63 Bramante, Donato, 248–49 Brand, Stewart, 15–16 Bray, Dennis, 171–72 bricolage, 271–72 Brin, Sergey, xxv Bronowski, Jacob, 340, 341–42 Brooks, David, xxv–xxviii Brown, Louise, 165 Bryson, Bill, 387 Buddha, 373 business planning, 186 Buss, David M., 353–54 Byars, James Lee, xxix–xxx Cabot, John, 90 calculus, 34, 109 Calvin, William, 201–2 cancer, 390 body scans and, 69, 259–60, 264, 265 tests for, 264–65 cannibalism, 361–62 carbon, 81, 82 carbon dioxide (CO2) emissions, 202, 207, 217, 262 car insurance, 66–67 Carr, Nicholas, 116–17 Carroll, Sean, 9–10 Cartesian science, 82–83 Caspi, Avshalom, 279 cats, 286 causality, 34–36, 58–61, 396 blame, 35–36, 106, 386 confabulation, 349–52 correlation and, 215–17, 219 of diseases, 59, 303–4 entanglement and, 331 information flow and, 218–20 nexus, 34–35 root-cause analysis, 303–4 in universe, 9–10 web of causation, 59–60, 61 central-limit theorem, 107–8 certainty, 73, 260 proof, 355–57 uselessness of, 51–52 see also uncertainty Challenger, 236 chance, 7, 18 change, 127–28, 290 fixation on, 373 chaos theory, 103, 202 character traits, 229 charitable activities, 194 cheating, 351 chess, 343 chickens, 62–63, 155 children, 148, 155, 252 chocolate, 140 cholera, 338 Chomsky, Noam, xxv Christakis, Nicholas A., xxvii, 81–83, 306 Church, George, 88–89 CINAC (“correlation is not a cause”), 215–17 civil rights movement, 370 Clark, Andy, 132–34 Clarke, Arthur C., 61 climate change, 51, 53, 99, 178, 201–2, 204, 268, 309, 315, 335, 386, 390 CO2 levels and, 202, 207, 217, 262 cultural differences in view of, 387–88 global economy and, 238–39 procrastination in dealing with, 209, 210 clinical trials, 26, 44, 56 cloning, 56, 165 coastlines, xxvi, 246 Cochran, Gregory, 360–62 coffee, 140, 152, 351 cognition, 172 perception and, 133–34 cognitive humility, 39–40 cognitive load, 116–17 cognitive toolkit, 333 Cohen, Daniel, 254 Cohen, Joel, 65 Cohen, Steven, 307–8 cold fusion, 243, 244 Coleman, Ornette, 254, 255 collective intelligence, 257–58 Colombia, 345 color, 150–51 color-blindness, 144 Coltrane, John, 254–55 communication, 250, 358, 372 depth in, 227 temperament and, 231 companionship, 328–29 comparative advantage, law of, 100 comparison, 201 competition, 98 complexity, 184–85, 226–27, 326, 327 emergent, 275 computation, 227, 372 computers, 74, 103–4, 146–47, 172 cloud and, 74 graphical desktops on, 135 memory in, 39–40 open standards and, 86–87 computer software, 80, 246 concept formation, 276 conduction, 297 confabulation, 349–52 confirmation bias, 40, 134 Conner, Alana, 367–70 Conrad, Klaus, 394 conscientiousness, 232 consciousness, 217 conservatism, 347, 351 consistency, 128 conspicuous consumption, 228, 308 constraint satisfaction, 167–69 consumers, keystone, 174–76 context, sensitivity to, 40 continental drift, 244–45 conversation, 268 Conway, John Horton, 275, 277 cooperation, 98–99 Copernicanism, 3 Copernican Principle, 11–12, 25 Copernicus, Nicolaus, 11, 294 correlation, and causation, 215–17, 219 creationism, 268–69 creativity, 152, 395 constraint satisfaction and, 167–69 failure and, 79, 225 negative capability and, 225 serendipity and, 101–2 Crick, Francis, 165, 244 criminal justice, 26, 274 Croak, James, 271–72 crude look at the whole (CLAW), 388 Crutzen, Paul, 208 CT scans, 259–60 cultural anthropologists, 361 cultural attractors, 180–83 culture, 154, 156, 395 change and, 373 globalization and, see globalization culture cycle, 367–70 cumulative error, 177–79 curating, 118–19 currency, central, 41 Cushman, Fiery, 349–52 cycles, 170–73 Dalrymple, David, 218–20 DALYs (disability-adjusted life years), 206 danger, proving, 281 Darwin, Charles, 2, 44, 89, 98, 109, 156, 165, 258, 294, 359 Das, Satyajit, 307–9 data, 303, 394 personal, 303–4, 305–6 security of, 76 signal detection theory and, 389–93 Dawkins, Richard, 17–18, 180, 183 daydreaming, 235–36 DDT, 125 De Bono, Edward, 240 dece(i)bo effect, 381–85 deception, 321–23 decision making, 52, 305, 393 constraint satisfaction and, 167–69 controlled experiments and, 25–27 risk and, 56–57, 68–71 skeptical empiricism and, 85 deduction, 113 defeasibility, 336–37 De Grey, Aubrey, 55–57 delaying gratification, 46 democracy, 157–58, 237 Democritus, 9 Demon-Haunted World, The (Sagan), 273 Dennett, Daniel C., 170–73, 212, 275 depth, 226–28 Derman, Emanuel, 115 Descent of Man, The (Darwin), 156 design: mind and, 250–53 recursive structures in, 246–49 determinism, 103 Devlin, Keith, 264–65 Diagnostic and Statistical Manual of Mental Disorders (DSM-5), 233–34 “Dial F for Frankenstein” (Clarke), 61 Diesel, Rudolf, 170 diseases, 93, 128, 174 causes of, 59, 303–4 distributed systems, 74–77 DNA, 89, 165, 223, 244, 260, 292, 303, 306 Huntington’s disease and, 59 sequencing of, 15 see also genes dopamine, 230 doughnuts, 68–69, 70 drug trade, 345 dualities, 296–98, 299–300 wave-particle, 28, 296–98 dual view of ourselves, 32 dynamics, 276 Eagleman, David, 143–45 Earth, 294, 360 climate change on, see climate change distance between sun and, 53–54 life on, 3–5, 10, 15 earthquakes, 387 ecology, 294–95 economics, 100, 186, 208, 339 economy(ies), 157, 158, 159 global, 163–64, 238–39 Pareto distributions in, 198, 199, 200 and thinking outside of time, 223 ecosystems, 312–14 Edge, xxv, xxvi, xxix–xxx education, 50, 274 applying to real-world situations, 40 as income determinant, 49 policies on, controlled experiments in, 26 scientific lifestyle and, 20–21 efficiency, 182 ego: ARISE and, 235–36 see also self 80/20 rule, 198, 199 Einstein, Albert, 28, 55, 169, 301, 335, 342 on entanglement, 330 general relativity theory of, 25, 64, 72, 234, 297 memory law of, 252 on simplicity, 326–27 Einstellung effect, 343–44 electrons, 296–97 Elliott, Andrew, 150 Eliot, T.

., 310–11 Smith, John Maynard, 96 Smolin, Lee, 221–24 social microbialism, 16 social networks, 82, 262, 266 social sciences, 273 Socrates, 340 software, 80, 246 Solomon Islands, 361 something for nothing, 84 specialness, see uniqueness and specialness Sperber, Dan, 180–83 spider bites, 68, 69, 70 spoon bending, 244 stability, 128 Standage, Tom, 281 stars, 7, 128, 301 statistically significant difference, 378–80 statistics, 260, 356 stem-cell research, 56, 69–70 stock market, 59, 60–61, 151, 339 Flash Crash and, 60–61 Pareto distributions and, 199, 200 Stodden, Victoria, 371–72 stomach ulcers, 240 Stone, Linda, 240–41 stress, 68, 70, 71 string theories, 113, 114, 299, 322 subselves and the modular mind, 129–31 success, failure and, 79–80 sun, 1, 7, 11, 164 distance between Earth and, 53–54 sunk-cost trap, 121 sunspots, 110 Superorganism, The (Hölldobler and Wilson), 196–97 superorganisms, 196 contingent, 196–97 supervenience, 276, 363–66 Susskind, Leonard, 297 Swets, John, 391 symbols and images, 152–53 synapses, 164 synesthesia, 136–37 systemic equilibrium, 237–39 Szathmáry, Eörs, 96 Taleb, Nassim, 315 TANSTAAFL (“There ain’t no such thing as a free lunch”), 84 Tapscott, Don, 250–53 taste, 140–42 tautologies, 355–56 Taylor, F. W., 186 Taylor, G. I., 185–86 Taylor, Timothy, 333 Taylorism, 186 technology(ies), 223, 249, 251, 257, 259, 273, 315 biases in, 41–42 black-swan, 315–17 humanity and, 333 Tegmark, Max, 19–22 telepathy, 244, 245 telephone game, 177, 178, 179 television, 287 temperament dimensions, 229–31 temperature, 151–52 ten, powers of, 162–64 terrorism, 69, 262, 264, 265 September 11 attacks, 386 testosterone, 230, 231 Thaler, Richard, 338–39 theater, science vs., 262–63 theory, effective, 192–93 Theory of Everything, 365 There’s No Such Thing as a Free Lunch (Friedman), 84 thermodynamics, 108, 227, 237, 302 Thich Nhat Hanh, 289 ’t Hooft, Gerard, 297 thought, thinking, 395 bottom-up vs. top-down, 157–59 design for, 250–53 flow of, 211–13 language and, 242 projective, 240–41 reactive, 240 thought, thinking (cont.)


pages: 355 words: 92,571

Capitalism: Money, Morals and Markets by John Plender

activist fund / activist shareholder / activist investor, Alan Greenspan, Andrei Shleifer, asset-backed security, bank run, Berlin Wall, Big bang: deregulation of the City of London, Black Monday: stock market crash in 1987, Black Swan, bond market vigilante , bonus culture, Bretton Woods, business climate, business cycle, Capital in the Twenty-First Century by Thomas Piketty, central bank independence, collapse of Lehman Brothers, collective bargaining, computer age, Corn Laws, Cornelius Vanderbilt, corporate governance, creative destruction, credit crunch, Credit Default Swap, David Ricardo: comparative advantage, deindustrialization, Deng Xiaoping, discovery of the americas, diversification, Eugene Fama: efficient market hypothesis, eurozone crisis, failed state, Fall of the Berlin Wall, fiat currency, financial engineering, financial innovation, financial intermediation, Fractional reserve banking, full employment, Glass-Steagall Act, God and Mammon, Golden arches theory, Gordon Gekko, greed is good, Hyman Minsky, income inequality, industrial research laboratory, inflation targeting, information asymmetry, invention of the wheel, invisible hand, Isaac Newton, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", James Watt: steam engine, Johann Wolfgang von Goethe, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, joint-stock company, Joseph Schumpeter, labour market flexibility, liberal capitalism, light touch regulation, London Interbank Offered Rate, London Whale, Long Term Capital Management, manufacturing employment, Mark Zuckerberg, market bubble, market fundamentalism, mass immigration, means of production, Menlo Park, money market fund, moral hazard, moveable type in China, Myron Scholes, Nick Leeson, Northern Rock, Occupy movement, offshore financial centre, paradox of thrift, Paul Samuelson, plutocrats, price stability, principal–agent problem, profit motive, proprietary trading, quantitative easing, railway mania, regulatory arbitrage, Richard Thaler, rising living standards, risk-adjusted returns, Robert Gordon, Robert Shiller, Ronald Reagan, savings glut, shareholder value, short selling, Silicon Valley, South Sea Bubble, spice trade, Steve Jobs, technology bubble, The Chicago School, The Great Moderation, the map is not the territory, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, too big to fail, tulip mania, Upton Sinclair, Veblen good, We are the 99%, Wolfgang Streeck, zero-sum game

Many have been tempted to attribute the crisis to what the author Nassim Nicholas Taleb calls black swans, or high-impact, hard-to-predict events that are beyond the realm of normal expectations. Yet anyone who knew anything about the financial crises of 1907, which prompted the creation of the US Federal Reserve, and of 1929, which led to the 1930s depression, would have been well equipped to see the risks in the property bubble that preceded the latest crisis. Indeed, financial crises have been normal, regular events since the invention of modern banking. And Nassim Nicholas Taleb was himself immensely prescient about the crisis. Those black swans, if the reader will excuse a solecism, were a canard.

Muller. 204 This was attributed to Coolidge in the Reader’s Digest of June 1960, but I have been unable to find the original source. 205 http://www.project-syndicate.org/commentary/a-crisis-in-two-narratives 206 See Efficiency, Equality and the Ownership of Private Property, Harvard University Press, 1964. I was alerted to this by Benjamin M. Friedman’s thought-provoking article ‘“Brave New Capitalists’ Paradise”: The Jobs?’ in the New York Review of Books, 7 November 2013. 207 The Black Swan: The Impact of the Highly Improbable, Random House, 2007. 208 http://www.worldbank.org/en/topic/poverty/overview 209 Divided We Stand: Why Inequality Keeps Rising, OECD, 2011. 210 See Jon Bakija, Adam Cole, and Bradley T. Heim, ‘Jobs and Income Growth of Top Earners and the Causes of Changing Income Inequality: Evidence from US Tax Return Data’, Department of Economics Working Paper, Williams College, Williamstown, MA, 2012. 211 Figures from Lawrence Mishel of the Economic Policy Institute of the US, see http://www.epi.org/publication/ceo-pay-231-times-greater-average-worker 212 ‘The Crises of Democratic Capitalism’, New Left Review, September–October 2011. 213 Remarks at THEARC, Washington DC, 4 December 2013. 214 ‘What did QE achieve, apart from boosting the price of Warhols?’

Wilson) 1, 2 Alberti, Leon Battista 1 Alessandri, Piergiorgio 1 Allen, Maurice 1 Ambassadors, The (Henry James) 1 Americans for Tax Reform 1 Anatomy of Change-Alley (Daniel Defoe) 1 Angell, Norman 1 Anglosphere 1, 2 Arab Spring 1 Aramaic 1 arbitrage 1 Argentina 1 Aristotle 1, 2, 3, 4, 5, 6, 7, 8, 9 art 1 Asian Tiger economies 1 Atlas Shrugged (Ayn Rand) 1 Austen, Jane 1 Austrian school 1 aviation 1 Babbitt (Sinclair Lewis) 1 Bair, Sheila 1 Balloon Dog (Orange) (sculpture) 1 Balzac 1 Bank for International Settlements 1, 2, 3, 4, 5, 6 Bank of England 1, 2, 3, 4, 5 bank runs 1 bankers 1, 2 bankruptcy laws 1, 2 Banks, Joseph 1 Banksy 1 Barbon, Nicholas 1, 2, 3 Bardi family 1 Barings 1 Baruch, Bernard 1, 2 base metal, transmutation into gold 1 Basel regulatory regime 1, 2, 3 Baudelaire, Charles 1 Baum, Frank 1 behavioural finance 1 Belgium 1, 2 Bell, Alexander Graham 1 Benjamin, Walter 1 Bernanke, Ben 1, 2, 3 Bi Sheng 1 Bible 1 bimetallism 1 Bismarck, Otto von 1 Black Monday (1987) 1 black swans 1 Blake William 1, 2, 3 Bloch, Marcel 1 Bloomsbury group 1, 2 Boccaccio 1 bond market 1 bonus culture 1 Bootle, Roger 1 Boston Tea Party 1 Boswell, James 1 Boulton, Matthew 1 Bowra, Maurice 1 Brandeis, Louis 1 Bretton Woods conference 1 British Land (property company) 1 British Rail pension fund 1 Brookhart, Smith 1, 2 Brunner, Karl 1 Bryan, William Jennings 1 Bubble Act (Britain 1720) 1 bubbles 1, 2, 3 Buchanan, James 1 Buffett, Warren 1, 2, 3 Buiter, Willem 1 Burdett, Francis 1 van Buren, Martin 1 Burke, Edmund 1, 2 Burns, Robert 1 Bush, George W. 1, 2 Butler, Samuel 1 Candide (Voltaire) 1 Carlyle, Thomas 1, 2, 3 Carnegie, Andrew 1 Carville, James 1 cash nexus 1 Cash Nexus, The (Niall Ferguson) 1 Cassel, Ernest 1, 2 Catholic Church 1, 2, 3 Cecchetti, Stephen 1 Centre for the Study of Capital Market Dysfunctionality, (London School of Economics) 1 central bankers 1 Cervantes 1 Chamberlain, Joseph 1 Chancellor, Edward 1 Chapter 11 bankruptcy 1 Charles I of England 1, 2 Charles II of England 1 Chaucer 1 Cheney, Dick 1 Chernow, Ron 1 Chicago school 1, 2 Child & Co. 1 China 1, 2 American dependence on 1, 2 industrialisation 1, 2, 3 manufacturing 1 paper currency 1 Christianity 1, 2, 3, 4, 5 Churchill, Winston 1 Cicero 1, 2 Citizens United case 1 Cleveland, Grover 1 Clyde, Lord (British judge) 1 Cobden, Richard 1, 2, 3, 4 Coggan, Philip 1 Cohen, Steven 1 Colbert, Jean-Baptiste 1, 2 Cold War 1 Columbus, Christopher 1 commodity futures 1 Companies Act (Britain 1862) 1 Condition of the Working Class in England (Engels) 1 Confucianism 1, 2, 3 conquistadores 1 Constitution of Liberty, The (Friedrich Hayek) 1 Coolidge, Calvin 1, 2, 3 Cooper, Robert 1 copyright 1 Cort, Cornelis 1 Cosimo the Elder 1 crash of 1907 1 crash of 1929 1, 2, 3, 4, 5, 6, 7, 8, 9, 10, 11 creative destruction 1, 2 credit crunch (2007) 1, 2, 3 cum privilegio 1 Cyprus 1, 2 Dale, Richard 1, 2 Dante 1 Darwin, Erasmus 1 Das Kapital (Karl Marx) 1 Dassault, Marcel 1 Daunton, Martin 1 Davenant, Charles 1, 2, 3 Davies, Howard 1 debt 1 debt slavery 1 Decameron (Boccaccio) 1 Defoe, Daniel 1, 2, 3, 4, 5, 6, 7, 8 Dell, Michael 1 Deng Xiaoping 1, 2 derivatives 1 Deserted Village, The (Oliver Goldsmith) 1, 2, 3 Devil Take the Hindmost (Edward Chancellor) 1 Dickens, Charles 1, 2, 3, 4, 5, 6, 7, 8, 9 portentously named companies 1 Die Juden und das Wirtschaftsleben (Werner Sombart) 1 A Discourse of Trade (Nicholas Barbon) 1 Ding Gang 1 direct taxes 1, 2 Discorsi (Machiavelli) 1 diversification 1 Dodd–Frank Act (US 2010) 1, 2, 3 ‘dog and frisbee’ speech 1 dot.com bubble 1, 2, 3, 4 Drayton, Harley 1 Dumas, Charles 1, 2 Dürer, Albrecht 1 Duret, Théodore 1, 2 Dutch East India Company 1 Duttweiler, Gottlieb 1 Dye, Tony 1 East of Eden (film version) 1 Economic Consequences of the Peace (Keynes) 1, 2 Edison, Thomas 1, 2 efficient market hypothesis 1 electricity 1 Eliot, T.


pages: 1,088 words: 228,743

Expected Returns: An Investor's Guide to Harvesting Market Rewards by Antti Ilmanen

Alan Greenspan, Andrei Shleifer, asset allocation, asset-backed security, availability heuristic, backtesting, balance sheet recession, bank run, banking crisis, barriers to entry, behavioural economics, Bernie Madoff, Black Swan, Bob Litterman, bond market vigilante , book value, Bretton Woods, business cycle, buy and hold, buy low sell high, capital asset pricing model, capital controls, carbon credits, Carmen Reinhart, central bank independence, classic study, collateralized debt obligation, commoditize, commodity trading advisor, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, deal flow, debt deflation, deglobalization, delta neutral, demand response, discounted cash flows, disintermediation, diversification, diversified portfolio, dividend-yielding stocks, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, fiat currency, financial deregulation, financial innovation, financial intermediation, fixed income, Flash crash, framing effect, frictionless, frictionless market, G4S, George Akerlof, global macro, global reserve currency, Google Earth, high net worth, hindsight bias, Hyman Minsky, implied volatility, income inequality, incomplete markets, index fund, inflation targeting, information asymmetry, interest rate swap, inverted yield curve, invisible hand, John Bogle, junk bonds, Kenneth Rogoff, laissez-faire capitalism, law of one price, London Interbank Offered Rate, Long Term Capital Management, loss aversion, low interest rates, managed futures, margin call, market bubble, market clearing, market friction, market fundamentalism, market microstructure, mental accounting, merger arbitrage, mittelstand, moral hazard, Myron Scholes, negative equity, New Journalism, oil shock, p-value, passive investing, Paul Samuelson, pension time bomb, performance metric, Phillips curve, Ponzi scheme, prediction markets, price anchoring, price stability, principal–agent problem, private sector deleveraging, proprietary trading, purchasing power parity, quantitative easing, quantitative trading / quantitative finance, random walk, reserve currency, Richard Thaler, risk free rate, risk tolerance, risk-adjusted returns, risk/return, riskless arbitrage, Robert Shiller, savings glut, search costs, selection bias, seminal paper, Sharpe ratio, short selling, sovereign wealth fund, statistical arbitrage, statistical model, stochastic volatility, stock buybacks, stocks for the long run, survivorship bias, systematic trading, tail risk, The Great Moderation, The Myth of the Rational Market, too big to fail, transaction costs, tulip mania, value at risk, volatility arbitrage, volatility smile, working-age population, Y2K, yield curve, zero-coupon bond, zero-sum game

Sun, Zheng; Ashley Wang; and Lu Zheng (2009), “The road less traveled: Strategy distinctiveness and hedge fund performance,” working paper, available at SSRN: http://ssrn.com/ abstract = 1337424 Swensen, David F. (2009), Pioneering Portfolio Management: An Unconventional Approach to Institutional Investment (Revised Edition), New York: Free Press. Taleb, Nassim Nicholas (2001), Fooled by Randomness: The Hidden Role of Chance in the Markets and Life, New York: Texere. Taleb, Nassim Nicholas (2004), “Bleed or blowup? What does empirical psychology tell us about the preference for negative skewness?” Journal of Behavioral Finance 5(1), 2–7. Taleb, Nassim Nicholas (2007), The Black Swan: The Impact of the Highly Improbable, New York: Penguin Books. Takats, Elod (2010), “Ageing and asset prices,” BIS working paper 318.

Peso problem Return regularities may also reflect an abnormal or unrepresentative sample period (say, 2003–2007). The peso problem refers to the difficulty of assessing time series that are plagued by important rare events which may or may not be realized in sample—closely linked to fat tails and black swans (see Rogoff, 1980; Taleb, 2007) [1]. Peso problems are especially important when we interpret the performance of assets or strategies with asymmetric return distributions. If a rare adverse event to which the market assigns a low probability does not materialize during the sample period, selling insurance against such an event appears highly profitable.

Risk, and particularly risk in the sense of survival, is all the rage in these days following a major financial crisis. This wide-ranging discussion of risk is right and proper. If some investors took too much risk and that caused or exacerbated the financial crisis, that’s a pretty important event to learn from. If some investors thought risk was simple and all figured out, and got a black swan dropped on their heads, it is important to learn from that too. However, it’s not the whole story. While perhaps differing from the vast majority of risk-focused researchers and authors these days, I’d argue that the study of expected returns deserves more of our attention, even just after one of the biggest “left tails” in history.


pages: 726 words: 172,988

The Bankers' New Clothes: What's Wrong With Banking and What to Do About It by Anat Admati, Martin Hellwig

Alan Greenspan, Andrei Shleifer, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, Bernie Madoff, Big bang: deregulation of the City of London, Black Swan, bonus culture, book value, break the buck, business cycle, Carmen Reinhart, central bank independence, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, diversified portfolio, en.wikipedia.org, Exxon Valdez, financial deregulation, financial engineering, financial innovation, financial intermediation, fixed income, George Akerlof, Glass-Steagall Act, Growth in a Time of Debt, income inequality, information asymmetry, invisible hand, Jean Tirole, joint-stock company, joint-stock limited liability company, junk bonds, Kenneth Rogoff, Larry Wall, light touch regulation, London Interbank Offered Rate, Long Term Capital Management, margin call, Martin Wolf, Money creation, money market fund, moral hazard, mortgage debt, mortgage tax deduction, negative equity, Nick Leeson, Northern Rock, open economy, Paul Volcker talking about ATMs, peer-to-peer lending, proprietary trading, regulatory arbitrage, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, Satyajit Das, Savings and loan crisis, shareholder value, sovereign wealth fund, subprime mortgage crisis, technology bubble, The Market for Lemons, the payments system, too big to fail, Upton Sinclair, Yogi Berra

At the time, Wuffli was the chief financial officer and Gummerlock the chief risk officer of Swiss Bank Corporation, which later merged into UBS; Freeland was the deputy secretary general of the Basel Committee for Banking Supervision. The limitations of quantitative models and stress tests are discussed in Chapter 11. 50. Taleb (2001, 2010) refers to such risks as “black swan” risks. Black swans are events that have been deemed impossible and that have significant consequences when they occur anyway. Taleb gives several examples in which neglect of black swan risk led to disaster. Das (2010, Chapter 5) discusses the pitfalls of “risk management by the numbers,” including the story of LTCM. Gillian Tett, in “Clouds Sighted off CDO Asset Pool” (Financial Times, April 18, 2005), noted that “if a nasty accident did ever occur with CDOs, it could ricochet through the financial system in unexpected ways,” and that “while banks insist that these risks can be accurately measured by their models … projecting default probabilities remains an art, not science.”

American Economic Review 90 (2): 1–16. Sundaresan, Suresh, and Zhenyu Wang. 2010. “Design of Contingent Capital with Stock Price Trigger for Conversion.” Staff Report 448. Federal Reserve Bank of New York, New York. April 23. Taleb, Nassim N. 2001. Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life. New York: W. W. Norton. ———. 2010. The Black Swan, Second Edition: The Impact of the Highly Improbable, with a New Section: On Robustness and Fragility. New York: Random House. Tarullo, Daniel K. 2008. Banking on Basel: The Future of International Financial Regulation. Washington, DC: Peter G.

., 242n20, 243n27, 290n29, 292n41, 308n44 Berglöf, Erik, 253n35 Bernanke, Ben, 11, 238n47, 246n16, 249n15, 253n38, 330n13 Berra, Yogi, 109, 110, 129, 141 Better Markets, 233n19, 237n42, 259n32, 265n4, 288n13, 327n66 Bhagat, Sanjai, 284n24, 284n27, 285n35 Bhide, Amar, 282n14 Big Short, The (Lewis), 60 bills of exchange, as liquid assets, 272n45 BIS. See Bank for International Settlements Black Rock, 257n16 black swan risks, 261n50 blanket guarantees, 139, 142–43, 146, 287n6, 291n30 Blankfein, Lloyd, 230n8 Bloomberg, data on Fed lending programs, 288n14 BNP Paribas: formed by merger of Banque Nationale de Paris and Compagnie Financière de Paris et des Pays-Bas, 269n28, 324n45; liquidity problems of, 256n13 boards of directors, corporate: conflicts of interest in, 126–27; in culture of ROE, 126–27, 285n32; focus of, 126; responses to price declines, 106, 277n13; responsibilities of, 285n32 boards of directors, of Federal Reserve banks, 205 Bolton, Brian, 284n27, 285n35 Bolton, Patrick, 300n54, 306n29 Bomhard, Nikolaus von, 327n65 bonds: as liquid assets, 272n44; required return on, 107, 277n14.


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A Man for All Markets by Edward O. Thorp

"RICO laws" OR "Racketeer Influenced and Corrupt Organizations", 3Com Palm IPO, Alan Greenspan, Albert Einstein, asset allocation, Bear Stearns, beat the dealer, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, book value, Brownian motion, buy and hold, buy low sell high, caloric restriction, caloric restriction, carried interest, Chuck Templeton: OpenTable:, Claude Shannon: information theory, cognitive dissonance, collateralized debt obligation, Credit Default Swap, credit default swaps / collateralized debt obligations, diversification, Edward Thorp, Erdős number, Eugene Fama: efficient market hypothesis, financial engineering, financial innovation, Garrett Hardin, George Santayana, German hyperinflation, Glass-Steagall Act, Henri Poincaré, high net worth, High speed trading, index arbitrage, index fund, interest rate swap, invisible hand, Jarndyce and Jarndyce, Jeff Bezos, John Bogle, John Meriwether, John Nash: game theory, junk bonds, Kenneth Arrow, Livingstone, I presume, Long Term Capital Management, Louis Bachelier, low interest rates, margin call, Mason jar, merger arbitrage, Michael Milken, Murray Gell-Mann, Myron Scholes, NetJets, Norbert Wiener, PalmPilot, passive investing, Paul Erdős, Paul Samuelson, Pluto: dwarf planet, Ponzi scheme, power law, price anchoring, publish or perish, quantitative trading / quantitative finance, race to the bottom, random walk, Renaissance Technologies, RFID, Richard Feynman, risk-adjusted returns, Robert Shiller, rolodex, Sharpe ratio, short selling, Silicon Valley, Stanford marshmallow experiment, statistical arbitrage, stem cell, stock buybacks, stocks for the long run, survivorship bias, tail risk, The Myth of the Rational Market, The Predators' Ball, the rule of 72, The Wisdom of Crowds, too big to fail, Tragedy of the Commons, uptick rule, Upton Sinclair, value at risk, Vanguard fund, Vilfredo Pareto, Works Progress Administration

As long as the world of asset prices was normal, all was well, but just as in 1929 when investors on 10 percent margin were wiped out by a small reversal in prices, so LTCM, with its margin ranging from 1 to 3 percent, was ruined by a sea change in markets. As Nassim Taleb points out eloquently in his book The Black Swan, apparent excess returns like those for LTCM in normal times may be illusory as they may be more than offset by infrequent large losses from extreme events. Such “black swans” can be bad for some and good for others. Ironically, having passed in 1994 on the chance to invest in LTCM and temporarily get rich, I made money in 1998 by exploiting the distorted market prices left in the wake of their collapse.

New York: Bantam, 2008. Segel, Joel. Recountings: Conversations with MIT Mathematicians. Wellesley, MA: A K Peters/CRC Press, 2009. Siegel, Jeremy J. Stocks for the Long Run: The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies. New York: McGraw-Hill, 2008. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. ———. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. New York: Random House, 2005. Thorp, Edward O., and Sheen T. Kassouf. Beat the Market: A Scientific Stock Market System. New York: Random House, 1967.

When I studied this for Princeton Newport, I learned that the practice in the financial industry was to assume that default rates would follow normal historical experience. There was no attempt to quantify and adjust for infrequent large-scale bad events like the Great Depression, and the massive increase in defaults that could occur. The models failed to incorporate Black Swan risk into the pricing. Another problem was forecasting the rate at which homeowners might pay off their mortgages early, perhaps to refinance their existing home. A thirty-year mortgage held for the full period is much like a long-term bond. Paid off in five to ten years, it is more like an intermediate bond, and if it is retired in two or three years, the payments resemble those from a very short-term bond.


pages: 484 words: 136,735

Capitalism 4.0: The Birth of a New Economy in the Aftermath of Crisis by Anatole Kaletsky

"World Economic Forum" Davos, Alan Greenspan, bank run, banking crisis, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Black Swan, bond market vigilante , bonus culture, Bretton Woods, BRICs, business cycle, buy and hold, Carmen Reinhart, classic study, cognitive dissonance, collapse of Lehman Brothers, Corn Laws, correlation does not imply causation, creative destruction, credit crunch, currency manipulation / currency intervention, currency risk, David Ricardo: comparative advantage, deglobalization, Deng Xiaoping, eat what you kill, Edward Glaeser, electricity market, Eugene Fama: efficient market hypothesis, eurozone crisis, experimental economics, F. W. de Klerk, failed state, Fall of the Berlin Wall, financial deregulation, financial innovation, Financial Instability Hypothesis, floating exchange rates, foreign exchange controls, full employment, geopolitical risk, George Akerlof, global rebalancing, Goodhart's law, Great Leap Forward, Hyman Minsky, income inequality, information asymmetry, invisible hand, Isaac Newton, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, Kickstarter, laissez-faire capitalism, long and variable lags, Long Term Capital Management, low interest rates, mandelbrot fractal, market design, market fundamentalism, Martin Wolf, military-industrial complex, Minsky moment, Modern Monetary Theory, Money creation, money market fund, moral hazard, mortgage debt, Nelson Mandela, new economy, Nixon triggered the end of the Bretton Woods system, Northern Rock, offshore financial centre, oil shock, paradox of thrift, Pareto efficiency, Paul Samuelson, Paul Volcker talking about ATMs, peak oil, pets.com, Ponzi scheme, post-industrial society, price stability, profit maximization, profit motive, quantitative easing, Ralph Waldo Emerson, random walk, rent-seeking, reserve currency, rising living standards, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, seminal paper, shareholder value, short selling, South Sea Bubble, sovereign wealth fund, special drawing rights, statistical model, systems thinking, The Chicago School, The Great Moderation, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, too big to fail, Vilfredo Pareto, Washington Consensus, zero-sum game

Had these models been valid, events such as the 1987 stock market crash and the bankruptcy of the 1998 hedge fund crisis would not have occurred even once in the fifteen billion years since the creation of the universe.9 In fact, four such extreme events occurred in just two weeks after the Lehman bankruptcy. Mandelbrots’s ideas were popularized by Nassim Taleb in Fooled by Randomness and The Black Swan.10 These books, and the mathematical research they reflect, show that movements in financial prices are not “normally” distributed11 and that markets are much riskier than standard models indicate. The implication is that all the standard risk-management employed by bankers, regulators, and credit-rating agencies before the Lehman crisis were deeply flawed, and their use was bound eventually to produce enormous losses leading to a total breakdown of the financial system.

Available from http://www.federalreserve.gov/boarddocs/speeches/1996/19961205.htm. 8 Robert Shiller, Irrational Exuberance. 9 Benoit Mandelbrot and Richard Hudson, The (Mis)behavior of Markets: A Fractal View of Risk, Ruin and Reward, 4. 10 Nassim Nicholas Taleb, Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life and the Black Swan: The Impact of the Highly Probable. 11 The term normal distribution describes prices or any other form of data that cluster predictably and reliably around a mean value in a bell curve pattern. 12 Malcolm C. Sawyer, The Economics of Michal Kalecki.

“The Role of the State in Financial Markets.” World Bank Research Observer Annual Conference on Development Economics Supplement (1993): 19-61. Studwell, Joe. “Nurturing the Chinese Economy.” Far Eastern Economic Review (December 2009). Swift, Jonathan. Gulliver’s Travels. New York: Penguin Classics, 2003. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Probable. New York: Random House, 2007. ——. Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life. New York: W.W. Norton, 2001. Tobin, James. “The Monetarist Counter-Revolution Today—An Appraisal.” Cowles Foundation Paper No. 532. Yale University, 1981.


pages: 94 words: 26,453

The End of Nice: How to Be Human in a World Run by Robots (Kindle Single) by Richard Newton

3D printing, Abraham Maslow, adjacent possible, Black Swan, British Empire, Buckminster Fuller, Clayton Christensen, crowdsourcing, deliberate practice, digital divide, disruptive innovation, fail fast, fear of failure, Filter Bubble, future of work, Google Glasses, growth hacking, Isaac Newton, James Dyson, Jaron Lanier, Jeff Bezos, job automation, lateral thinking, Lean Startup, lolcat, low skilled workers, Mark Zuckerberg, move fast and break things, Paul Erdős, Paul Graham, reality distortion field, recommendation engine, rising living standards, Robert Shiller, Silicon Valley, Silicon Valley startup, skunkworks, social intelligence, Steve Ballmer, Steve Jobs, Tyler Cowen, Y Combinator

The importance of accident in the making a of a successful business isn’t what we are used to hearing. In his book The Black Swan, the author Nassim Taleb said: “The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship upon them. Explanations bind facts together. They make them all the more easily remembered; they help them make more sense. Where this propensity can go wrong is when it increases our impression of understanding.” (In his book, Nassim Taleb explained that our certainties are liable to be unravelled in an instant because of the partial information on which they are based.

(In his book, Nassim Taleb explained that our certainties are liable to be unravelled in an instant because of the partial information on which they are based. Thus it was once a certain fact that all swans were white because no one had seen a swan of another colour. Then in 1697, the Dutch explorer Willem de Vlaming discovered black swans in Australia.) Because we are used to having the past retold as a sequence of causal events we think the events of the future can also be predicted. The desire to make sense of everything is our brain’s pesky desire for logic asserting itself and trying to lay a thick dust sheet of certainty and order on a world which is more complex, intricate and messy.


pages: 524 words: 143,993

The Shifts and the Shocks: What We've Learned--And Have Still to Learn--From the Financial Crisis by Martin Wolf

air freight, Alan Greenspan, anti-communist, Asian financial crisis, asset allocation, asset-backed security, balance sheet recession, bank run, banking crisis, banks create money, Basel III, Bear Stearns, Ben Bernanke: helicopter money, Berlin Wall, Black Swan, bonus culture, break the buck, Bretton Woods, business cycle, call centre, capital asset pricing model, capital controls, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, collateralized debt obligation, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, currency risk, debt deflation, deglobalization, Deng Xiaoping, diversification, double entry bookkeeping, en.wikipedia.org, Erik Brynjolfsson, Eugene Fama: efficient market hypothesis, eurozone crisis, Fall of the Berlin Wall, fiat currency, financial deregulation, financial innovation, financial repression, floating exchange rates, foreign exchange controls, forward guidance, Fractional reserve banking, full employment, Glass-Steagall Act, global rebalancing, global reserve currency, Growth in a Time of Debt, Hyman Minsky, income inequality, inflation targeting, information asymmetry, invisible hand, Joseph Schumpeter, Kenneth Rogoff, labour market flexibility, labour mobility, Les Trente Glorieuses, light touch regulation, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, Long Term Capital Management, low interest rates, mandatory minimum, margin call, market bubble, market clearing, market fragmentation, Martin Wolf, Mexican peso crisis / tequila crisis, Minsky moment, Modern Monetary Theory, Money creation, money market fund, moral hazard, mortgage debt, negative equity, new economy, North Sea oil, Northern Rock, open economy, paradox of thrift, Paul Samuelson, price stability, private sector deleveraging, proprietary trading, purchasing power parity, pushing on a string, quantitative easing, Real Time Gross Settlement, regulatory arbitrage, reserve currency, Richard Feynman, risk-adjusted returns, risk/return, road to serfdom, Robert Gordon, Robert Shiller, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, shareholder value, short selling, sovereign wealth fund, special drawing rights, subprime mortgage crisis, tail risk, The Chicago School, The Great Moderation, The Market for Lemons, the market place, The Myth of the Rational Market, the payments system, The Wealth of Nations by Adam Smith, too big to fail, Tyler Cowen, Tyler Cowen: Great Stagnation, vertical integration, very high income, winner-take-all economy, zero-sum game

The Austrian school derives from the work of pre-Second World War Austrian economists, particularly Ludwig von Mises and Friedrich Hayek, but is now most influential in the US. Thus, ‘Austrian’ refers to a set of staunchly free-market ideas, not to the nationality of the believers. 7. Nouriel Roubini and Stephen Mihm, Crisis Economics: A Crash Course in the Future of Finance (London: Penguin, 2011), ch. 1. For ‘white swan’ and ‘black swan’ events, see Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 8. For a succinct discussion of Minsky’s views of big government and central banks, see Hyman P. Minsky, ‘Can “It” Happen Again? A Reprise’ (1982), Hyman P. Minsky Archive, Paper 155. http://digitalcommons.bard.edu/hm_archive/155. 9.

Summers, Lawrence and Martin Wolf. ‘A Conversation on New Economic Thinking’, Bretton Woods Conference, Institute for New Economic Thinking, 8 April 2011. http://ineteconomics.org/video/bretton-woods/larry-summers-and-martin-wolf-new-economic-thinking. Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in Life and the Markets (London: Penguin, 2004). Taleb, Nassim Nicholas.The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). Tarullo, Daniel K. ‘Statement by Daniel K. Tarullo, Member, Board of Governors of the Federal Reserve System before the Committee on Banking, Housing, and Urban Affairs, US Senate’, Washington DC, 11 July 2013. http://www.federalreserve.gov/newsevents/testimony/tarullo20130711a.htm.

Despite their huge differences, the ‘post-Keynesian’ school, with its suspicion of free markets, and the ‘Austrian’ school, with its fervent belief in them, would agree on that last point, though they would disagree on what causes crises and what to do about them when they happen.6 Minsky’s view that economics should include the possibility of severe crises, not as the result of external shocks, but as events that emerge from within the system, is methodologically sound. Crises, after all, are economic phenomena. Moreover, they have proved a persistent feature of capitalist economies. As Nouriel Roubini and Stephen Mihm argue in their book Crisis Economics, crises and subsequent depressions are, in the now celebrated terminology of Nassim Nicholas Taleb, not ‘black swans’ – rare and unpredictable events – but ‘white swans’ – normal, if relatively infrequent, events that even follow a predictable pattern.7 Depressions are indeed one of the states a capitalist economy can fall into. An economic theory that does not incorporate that possibility is as relevant as a theory of biology that excludes the risk of extinctions, a theory of the body that excludes the risk of heart attacks, or a theory of bridge-building that excludes the risk of collapse.


pages: 422 words: 113,830

Bad Money: Reckless Finance, Failed Politics, and the Global Crisis of American Capitalism by Kevin Phillips

"World Economic Forum" Davos, Alan Greenspan, algorithmic trading, asset-backed security, bank run, banking crisis, Bear Stearns, Bernie Madoff, Black Swan, Bretton Woods, BRICs, British Empire, business cycle, buy and hold, collateralized debt obligation, computer age, corporate raider, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency peg, diversification, Doha Development Round, energy security, financial deregulation, financial engineering, financial innovation, fixed income, Francis Fukuyama: the end of history, George Gilder, Glass-Steagall Act, housing crisis, Hyman Minsky, imperial preference, income inequality, index arbitrage, index fund, interest rate derivative, interest rate swap, Joseph Schumpeter, junk bonds, Kenneth Rogoff, large denomination, Long Term Capital Management, low interest rates, market bubble, Martin Wolf, Menlo Park, Michael Milken, military-industrial complex, Minsky moment, mobile money, money market fund, Monroe Doctrine, moral hazard, mortgage debt, Myron Scholes, new economy, oil shale / tar sands, oil shock, old-boy network, peak oil, plutocrats, Ponzi scheme, profit maximization, prosperity theology / prosperity gospel / gospel of success, Renaissance Technologies, reserve currency, risk tolerance, risk/return, Robert Shiller, Ronald Reagan, Satyajit Das, Savings and loan crisis, shareholder value, short selling, sovereign wealth fund, stock buybacks, subprime mortgage crisis, The Chicago School, Thomas Malthus, too big to fail, trade route

If speculative excesses represent an albatross for the U.S. financial sector, the prospective burden of quantitative mathematics represents a black albatross. Or perhaps we should say a bevy of black swans, author Nassim Nicholas Taleb’s shorthand for mathematical impossibilities that cannot occur in hedge funds’ quantitative strategies but always manage to occur two, three, seven, or eleven times in the real world of every significant financial crisis.47 The idea that policymakers have allowed the U.S. economy to be guided by a financial sector increasingly dominated by black box makers and algorithm vendors itself seems like a black swan—an impossibility, save that it’s happening. According to one U.S. consultancy, by 2010 algorithmic trading, an aspect of “quant”based investing, is expected to account for half of all trading in U.S. equity markets.48 There is no better distillation of the harm inflicted—and probably yet to be inflicted—than that of hedge fund manager Richard Bookstaber in his 2007 volume, A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation.

Dialynas and Marshall Auerbeck, “Renegade Economics: The Bretton Woods II Fiction,” Pimco Viewpoints, September 2007. 40 “America’s Vulnerable Economy,” Economist, November 15, 2007. 41 “Dollar’s Last Lap as the Only Anchor Currency,” Financial Times, November 25, 2007. 42 John Authers, “The Short View: Weak Dollar,” Financial Times, September 10, 2007. 43 “Why Banking Is an Accident Waiting to Happen,” Financial Times, November 27, 2007. 44 Martin Wolf, “Why the Credit Squeeze Is a Turning Point for the World,” Financial Times, December 11, 2007. 45 “Mortgage Crisis Perplexes Even Shrewd Investor Warren Buffett,” San Francisco Chronicle, December 12, 2007. 46 “European Bosses Warming to Foreign Funds,” Financial Times, December 11, 2007. 47 Nassim Nicholas Taleb, The Black Swan (New York: Random House, 2007). 48 “Does Not Compute: How Misfiring Quant Funds Are Distorting the Markets,” Financial Times, December 9, 2007. 49 Richard Bookstaber, A Demon of Our Own Design (New York: John Wiley & Sons, 2007), pp. 5, 259-60. 50 Mike Muehleck, “Exit U.S.,” www.agorafinancial.com//afrude/.

Treatises on the origin of scientific economics leave out mercantilism, and its preoccupation with gold, silver, and national aggrandizement of precious metals, as unscientific. But economics can be emotional as well as scientific—the psychologies of human nature, panic, and bubbling, for example. Indeed, this emotional explanation is becoming chic—witness the recent spate of books and articles on emotions trumping rationalism, the case for “black swan” (supposedly impossible) events, and the unlikely specialty of neuroeconomics.42 The early mercantilists propounded an economics based on the accumulation of precious-metal assets. These were the measure of a monarch’s or nation’s wealth. One got them from mines, from conquest, from captured ships, from colonies, and from exporting manufactures or commodities.


pages: 168 words: 50,647

The End of Jobs: Money, Meaning and Freedom Without the 9-To-5 by Taylor Pearson

Airbnb, barriers to entry, Ben Horowitz, Black Swan, call centre, cloud computing, commoditize, content marketing, creative destruction, David Heinemeier Hansson, drop ship, Elon Musk, en.wikipedia.org, Frederick Winslow Taylor, future of work, Google Hangouts, Hacker Conference 1984, Kaizen: continuous improvement, Kevin Kelly, Kickstarter, knowledge economy, knowledge worker, loss aversion, low skilled workers, Lyft, Marc Andreessen, Mark Zuckerberg, market fragmentation, means of production, Oculus Rift, passive income, passive investing, Peter Thiel, power law, remote working, Ronald Reagan: Tear down this wall, scientific management, sharing economy, side hustle, side project, Silicon Valley, Skype, software as a service, software is eating the world, Startup school, Steve Jobs, Steve Wozniak, Stewart Brand, systems thinking, TED Talk, telemarketer, the long tail, Thomas Malthus, Uber and Lyft, uber lyft, unpaid internship, Watson beat the top human players on Jeopardy!, web application, Whole Earth Catalog

Risk Lives in the Future “Artisans, say, taxi drivers, prostitutes (a very, very old profession), carpenters, plumbers, tailors, and dentists, have some volatility in their income but they are rather robust to a minor professional Black Swan, one that would bring their income to a complete halt. Their risks are visible. Not so with employees, who have no volatility, but can be surprised to see their income going to zero after a phone call from the personnel department. Employees’ risks are hidden. Thanks to variability, these artisanal careers harbor a bit of antifragility: small variations make them adapt and change continuously by learning from the environment and being, sort of, continuously under pressure to be fit.” N. N. Taleb Many of us have been fed the belief that traditional careers are safe and that they have always been safe.

“This is the central illusion in life: that randomness is risky, that it is a bad thing—and that eliminating randomness is done by eliminating randomness…Mediocristan has a lot of variations, not a single one of which is extreme; Extremistan has few variations, but those that take place are extreme.” N.N. Taleb Antifragile Source: 80/20 Sales and Marketing Everyone that attended high school or college is familiar with the graph above. When the teacher wrote everyone’s grades on the board, they looked like a bell curve. A few students did really well, a few did very poorly, and most people ended up somewhere in the middle.

“A turkey is fed for a thousand days by a butcher; every day confirms to its staff of analysts that butchers love turkeys ‘with increased statistical confidence.’ The butcher will keep feeding the turkey until a few days before Thanksgiving…[The] turkey will have a revision of belief—right when its confidence in the statement that the butcher loves turkeys is maximal and ‘it is very quiet’ and soothingly predictable in the life of the turkey.” N.N. Taleb The most obvious example of a world where a single, irreversible decision dictates the future is that of a turkey before Thanksgiving. From the day a Thanksgiving turkey is born, everything about its life indicates that things are only going to get better. It’s hatched in a safe, sterile environment.


pages: 364 words: 99,613

Servant Economy: Where America's Elite Is Sending the Middle Class by Jeff Faux

air traffic controllers' union, Alan Greenspan, back-to-the-land, Bear Stearns, benefit corporation, Bernie Sanders, Black Swan, Bretton Woods, BRICs, British Empire, business cycle, call centre, centre right, classic study, cognitive dissonance, collateralized debt obligation, collective bargaining, creative destruction, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, currency manipulation / currency intervention, David Brooks, David Ricardo: comparative advantage, disruptive innovation, falling living standards, financial deregulation, financial innovation, full employment, Glass-Steagall Act, guns versus butter model, high-speed rail, hiring and firing, Howard Zinn, Hyman Minsky, illegal immigration, indoor plumbing, informal economy, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, junk bonds, Kevin Roose, Kickstarter, lake wobegon effect, Long Term Capital Management, low interest rates, market fundamentalism, Martin Wolf, McMansion, medical malpractice, Michael Milken, military-industrial complex, Minsky moment, mortgage debt, Myron Scholes, Naomi Klein, new economy, oil shock, old-boy network, open immigration, Paul Samuelson, plutocrats, price mechanism, price stability, private military company, public intellectual, radical decentralization, Ralph Nader, reserve currency, rising living standards, Robert Shiller, rolodex, Ronald Reagan, Savings and loan crisis, school vouchers, Silicon Valley, single-payer health, Solyndra, South China Sea, statistical model, Steve Jobs, Suez crisis 1956, Thomas L Friedman, Thorstein Veblen, too big to fail, trade route, Triangle Shirtwaist Factory, union organizing, upwardly mobile, urban renewal, War on Poverty, We are the 99%, working poor, Yogi Berra, Yom Kippur War, you are the product

As examples, Tuchman presented the Renaissance popes who lost half of Christendom for the Catholic Church; the Aztec king Montezuma, who gave away his empire to the Spanish conquistador Hernando Cortez; King George III of England, who provoked the American Revolution; King Philip of Spain, who destroyed his navy in an effort to invade Britain; the World War I German general staff’s U-boat campaign against U.S. ships; Napoleon and Hitler, who each foolishly invaded Russia; the Japanese bombing of Pearl Harbor; and the three U.S. presidents who committed their nation to the Vietnam War. The future is, of course, unknowable, and prediction is always a matter of probabilities. History, like life, is marked by unexpected turns. Black swans, to use author Nassim Nicholas Taleb’s metaphor for the unforeseen, fly in undetected by our best radar. But major dislocating events that could not have been foretold are rarer than we commonly acknowledge. It’s true that plenty of forecasted disasters never occurred. An old joke has it that economists have predicted five out of the last three recessions.

The United States will triumph, of course, and North America will remain the economic and political power center of the world. But because conflict among nation-states is a permanent condition, the century’s end will see the United States menaced by a resurgent, nationalist Mexico. Friedman does not expect that we will completely swallow his predicted scenarios. But he reminds us that the “black swan” thesis of financial contrarian Nassim Nicholas Taleb (see chapter 1 of this book) taught us to expect the improbable. And Friedman’s improbable future is built on assumptions about military technology, demographics, and the maintenance of global hegemony that are widely accepted by the U.S. governing class and are generally compatible with the beliefs of Zakaria, Slaughter, Rose, and Kotkin.

This is the United States of America, after all. A prominent economist, Robert Hall, succinctly summarizes the catechism: “We’re not Japan. In America, the bet is still that we will somehow find ways to get people spending and investing again.”1 “Somehow” something will come up. Some unpredictable black swan will appear to lead us back to the old-time prosperity. Some deus ex machina will descend from above the stage to rescue the middle class from the script described in chapter 11 without discomforting the rich and powerful. Perhaps we will invent another Internet, the Chinese will self-destruct, or the magical tax cut will bring back full employment.


pages: 823 words: 220,581

Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned? by Steve Keen

accounting loophole / creative accounting, Alan Greenspan, banking crisis, banks create money, barriers to entry, behavioural economics, Benoit Mandelbrot, Big bang: deregulation of the City of London, Black Swan, Bonfire of the Vanities, book value, business cycle, butterfly effect, capital asset pricing model, cellular automata, central bank independence, citizen journalism, clockwork universe, collective bargaining, complexity theory, correlation coefficient, creative destruction, credit crunch, David Ricardo: comparative advantage, debt deflation, diversification, double entry bookkeeping, en.wikipedia.org, equity risk premium, Eugene Fama: efficient market hypothesis, experimental subject, Financial Instability Hypothesis, fixed income, Fractional reserve banking, full employment, Glass-Steagall Act, Greenspan put, Henri Poincaré, housing crisis, Hyman Minsky, income inequality, information asymmetry, invisible hand, iterative process, John von Neumann, Kickstarter, laissez-faire capitalism, liquidity trap, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, market microstructure, means of production, minimum wage unemployment, Money creation, money market fund, open economy, Pareto efficiency, Paul Samuelson, Phillips curve, place-making, Ponzi scheme, Post-Keynesian economics, power law, profit maximization, quantitative easing, RAND corporation, random walk, risk free rate, risk tolerance, risk/return, Robert Shiller, Robert Solow, Ronald Coase, Savings and loan crisis, Schrödinger's Cat, scientific mainstream, seigniorage, six sigma, South Sea Bubble, stochastic process, The Great Moderation, The Wealth of Nations by Adam Smith, Thorstein Veblen, time value of money, total factor productivity, tulip mania, wage slave, zero-sum game

The complete failure of neoclassical economics to anticipate the crisis also meant, as I expected, that economic theory and economists are under public attack as never before. Their defense has been to argue that ‘no one could have seen this coming.’ They have taken refuge in the phrase that this crisis was a ‘Black Swan,’ using Nassim Taleb’s phrase completely out of context (Taleb 2007), and ignoring the fact that I and many other non-neoclassical economists did in fact see this coming. I therefore decided that, for both positive and negative reasons, a new edition of Debunking Economics was needed. The negative reason is that there is no better time to attack a fallacious theory than after it has made a spectacularly wrong prediction.

However, ‘rational expectations’ makes no sense in non-ergodic models: any predictions made from within such a model about the model’s future behavior would be wrong (let alone predictions made about the economy the model is alleged to simulate). Crucially, the errors made by agents within that model would not be ‘normally distributed’ – they would not be neatly distributed around the model’s mean as in the classic ‘Bell Curve.’ Instead the distribution would be ‘chaotic,’ with lots of what Nassim Taleb labeled ‘Black Swan events’ (Taleb 2007). It would be futile to have ‘rational expectations’ in such a model, because these would be misleading guides to the model’s future. The model’s future would be uncertain, and the best thing any agent in such a model could do would be to project forward its current trajectory, while also expecting that expectation to be wrong.

Stiglitz, J. (2000) ‘What I learned at the world economic crisis,’ New Republic, 17–24 April, pp. 56–60. Strange, S. (1997) Casino Capitalism, Manchester: Manchester University Press. Swan, T. W. (2002) ‘Economic growth,’ Economic Record, 78(243): 375–80. Sweezy, P. M. (1942) The Theory of Capitalist Development, New York: Oxford University Press. Taleb, N. (2007) The Black Swan: The Impact of the Highly Improbable, New York: Random House. Taslim, F. and A. Chowdhury (1995) Macroeconomic Analysis for Australian Students, Sydney: Edward Elgar. Taylor, J. B. (1993) ‘Discretion versus policy rules in practice,’ Carnegie-Rochester Conference Series on Public Policy, 39: 195–214.


pages: 695 words: 194,693

Money Changes Everything: How Finance Made Civilization Possible by William N. Goetzmann

Albert Einstein, Andrei Shleifer, asset allocation, asset-backed security, banking crisis, Benoit Mandelbrot, Black Swan, Black-Scholes formula, book value, Bretton Woods, Brownian motion, business cycle, capital asset pricing model, Cass Sunstein, classic study, collective bargaining, colonial exploitation, compound rate of return, conceptual framework, Cornelius Vanderbilt, corporate governance, Credit Default Swap, David Ricardo: comparative advantage, debt deflation, delayed gratification, Detroit bankruptcy, disintermediation, diversified portfolio, double entry bookkeeping, Edmond Halley, en.wikipedia.org, equity premium, equity risk premium, financial engineering, financial independence, financial innovation, financial intermediation, fixed income, frictionless, frictionless market, full employment, high net worth, income inequality, index fund, invention of the steam engine, invention of writing, invisible hand, James Watt: steam engine, joint-stock company, joint-stock limited liability company, laissez-faire capitalism, land bank, Louis Bachelier, low interest rates, mandelbrot fractal, market bubble, means of production, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, new economy, passive investing, Paul Lévy, Ponzi scheme, price stability, principal–agent problem, profit maximization, profit motive, public intellectual, quantitative trading / quantitative finance, random walk, Richard Thaler, Robert Shiller, shareholder value, short selling, South Sea Bubble, sovereign wealth fund, spice trade, stochastic process, subprime mortgage crisis, Suez canal 1869, Suez crisis 1956, the scientific method, The Wealth of Nations by Adam Smith, Thomas Malthus, time value of money, tontine, too big to fail, trade liberalization, trade route, transatlantic slave trade, tulip mania, wage slave

The story goes that a system built on mathematical formulas took finance higher and higher until their structural weaknesses were exposed and the entire edifice collapsed, leaving taxpayers around the world to clean up the mess. Provocative money manager Nassim Taleb went so far in 2008 as to propose jail time for quants who used standard risk models. “We would like society to lock up quantitative risk managers before they cause more damage.”5 Respondents to his blog used even stronger language. Of course, Taleb was promoting his book The Black Swan, which argues that the standard probability models, based as they are on Bernoulli’s original formulation, cannot account for the frequent occurrence of extreme events.

In the 1960s, Benoit Mandelbrot began to investigate whether Lévy processes described economic time series like cotton prices and stock prices. He found that the ones that generated jumps and extreme events better described financial markets. He developed a mathematics around these unusual Lévy processes that he called “fractal geometry.” He argued that unusual events—Taleb’s black swan—were in fact much more common phenomena than Brownian motion would suggest. The crash of 1987 was not a surprise to him—he took it as a vindication of his theory. One of his major contributions to the literature on finance (published in 1966) was a proof that an efficient market implies that stock prices may not follow a random walk, but that they must be unpredictable.

European Journal of the History of Economic Thought 8(3): 323–362. 3. Jovanovic, Franck. 2006. “Economic instruments and theory in the construction of Henri Lefèvre’s science of the stock market.” Pioneers of Financial Economics 1: 169–190. 4. William Sharpe, John Cox, Stephen Ross, and Mark Rubenstein. 5. This is Money. 2008. “Nassim Taleb and the Secret of the Black Swan,” Daily Mail, November 3. Available at: http://www.thisismoney.co.uk/markets/article.html?in_article_id=456175&in_page_id=3#ixzz161dvBHe7. CHAPTER 17 1. Fratianni, Michele. 2006. “Government debt, reputation and creditors’ protections: The tale of San Giorgio.” Review of Finance 10(4): 487–506. 2.


pages: 304 words: 82,395

Big Data: A Revolution That Will Transform How We Live, Work, and Think by Viktor Mayer-Schonberger, Kenneth Cukier

23andMe, Affordable Care Act / Obamacare, airport security, Apollo 11, barriers to entry, Berlin Wall, big data - Walmart - Pop Tarts, Black Swan, book scanning, book value, business intelligence, business process, call centre, cloud computing, computer age, correlation does not imply causation, dark matter, data science, double entry bookkeeping, Eratosthenes, Erik Brynjolfsson, game design, hype cycle, IBM and the Holocaust, index card, informal economy, intangible asset, Internet of things, invention of the printing press, Jeff Bezos, Joi Ito, lifelogging, Louis Pasteur, machine readable, machine translation, Marc Benioff, Mark Zuckerberg, Max Levchin, Menlo Park, Moneyball by Michael Lewis explains big data, Nate Silver, natural language processing, Netflix Prize, Network effects, obamacare, optical character recognition, PageRank, paypal mafia, performance metric, Peter Thiel, Plato's cave, post-materialism, random walk, recommendation engine, Salesforce, self-driving car, sentiment analysis, Silicon Valley, Silicon Valley startup, smart grid, smart meter, social graph, sparse data, speech recognition, Steve Jobs, Steven Levy, systematic bias, the scientific method, The Signal and the Noise by Nate Silver, The Wealth of Nations by Adam Smith, Thomas Davenport, Turing test, vertical integration, Watson beat the top human players on Jeopardy!

The figure was also referenced by two former Amazon executives in interviews with Cukier. Netflix price information—Xavier Amatriain and Justin Basilico, “Netflix Recommendations: Beyond the 5 stars (Part 1),” Netflix blog, April 6, 2012. [>] “Fooled by Randomness”—Nassim Nicholas Taleb, Fooled by Randomness (Random House, 2008); for more, see Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (2nd ed., Random House, 2010). [>] Walmart and Pop-Tarts—Constance L. Hays, “What Wal-Mart Knows About Customers’ Habits,” New York Times, November 14, 2004 (http://www.nytimes.com/2004/11/14/business/yourmoney/14wal.html). [>] Examples of predictive models by FICO, Experian, and Equifax—Scott Thurm, “Next Frontier in Credit Scores: Predicting Personal Behavior,” Wall Street Journal, October 27, 2011 (http://online.wsj.com/article/SB10001424052970203687504576655182086300912.html). [>] Aviva’s predictive models—Leslie Scism and Mark Maremont, “Insurers Test Data Profiles to Identify Risky Clients,” Wall Street Journal, November 19, 2010 (http://online.wsj.com/article/SB10001424052748704648604575620750998072986.html).

The Digital Person: Technology and Privacy in the Information Age. NYU Press, 2004. Surowiecki, James. “A Billion Prices Now.” New Yorker, May 30, 2011 (http://www.newyorker.com/talk/financial/2011/05/30/110530ta_talk_surowiecki). Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. Random House, 2008. ———. The Black Swan: The Impact of the Highly Improbable. 2nd ed., Random House, 2010. Thompson, Clive. “For Certain Tasks, the Cortex Still Beats the CPU.” Wired, June 25, 2007 (http://www.wired.com/techbiz/it/magazine/15-07/ff_humancomp?currentPage=all).

Correlations let us analyze a phenomenon not by shedding light on its inner workings but by identifying a useful proxy for it. Of course, even strong correlations are never perfect. It is quite possible that two things may behave similarly just by coincidence. We may simply be “fooled by randomness,” to borrow a phrase from the empiricist Nassim Nicholas Taleb. With correlations, there is no certainty, only probability. But if a correlation is strong, the likelihood of a link is high. Many Amazon customers can attest to this by pointing to a bookshelf laden with the company’s recommendations. By letting us identify a really good proxy for a phenomenon, correlations help us capture the present and predict the future: if A often takes place together with B, we need to watch out for B to predict that A will happen.


pages: 249 words: 77,342

The Behavioral Investor by Daniel Crosby

affirmative action, Asian financial crisis, asset allocation, availability heuristic, backtesting, bank run, behavioural economics, Black Monday: stock market crash in 1987, Black Swan, book value, buy and hold, cognitive dissonance, colonial rule, compound rate of return, correlation coefficient, correlation does not imply causation, Daniel Kahneman / Amos Tversky, disinformation, diversification, diversified portfolio, Donald Trump, Dunning–Kruger effect, endowment effect, equity risk premium, fake news, feminist movement, Flash crash, haute cuisine, hedonic treadmill, housing crisis, IKEA effect, impact investing, impulse control, index fund, Isaac Newton, Japanese asset price bubble, job automation, longitudinal study, loss aversion, market bubble, market fundamentalism, mental accounting, meta-analysis, Milgram experiment, moral panic, Murray Gell-Mann, Nate Silver, neurotypical, Nick Bostrom, passive investing, pattern recognition, Pepsi Challenge, Ponzi scheme, prediction markets, random walk, Reminiscences of a Stock Operator, Richard Feynman, Richard Thaler, risk tolerance, Robert Shiller, science of happiness, Shai Danziger, short selling, South Sea Bubble, Stanford prison experiment, Stephen Hawking, Steve Jobs, stocks for the long run, sunk-cost fallacy, systems thinking, TED Talk, Thales of Miletus, The Signal and the Noise by Nate Silver, Tragedy of the Commons, trolley problem, tulip mania, Vanguard fund, When a measure becomes a target

Given both the psychological (we hate losses 2.5 times as much as gains) and mathematical (it takes a 100% gain to erase a 50% loss) realities of negative events, they warrant special consideration by behavioral investors. Nassim Taleb gives a wonderful example of this in his book, Fooled by Randomness. He relates the story of meeting with fellow traders and sharing with them his belief that the market would likely rise in the following week. Realizing that he had a short position on, the traders were confused. Why be short a market you think is likely to rise? To explain, Taleb showed them the following chart. Event Probability Outcome Expected Value Market Goes Up 70% 1% 0.7 Market Goes Down 30% −10% −3.0 Total 100% −2.3 Taleb believed there to be an asymmetry between the size of losses and gains that might occur.

Behavioral economist Robert Shiller suggested that the ubiquity of the internet made it easier for investors to bid up the prices of internet stocks to unprecedented levels during the dot.com bubble. Evidence of the usefulness of the WWW was everywhere, making it easy to create internal narratives about how the internet could be paradigm changing. Likewise, we see the effects of black swan events like the Great Recession linger in the public consciousness for years after the fact, unusual and impactful as they are. Unfortunately for us, the imperfections of the availability heuristic are hard at work as we attempt to gauge the riskiness of different ways of living and investing.

It is only when our personal choices and pet beliefs come under scrutiny that we rally the ego to our defense. Backfire “My characterization of a loser is someone who, after making a mistake, doesn’t introspect, doesn’t exploit it, feels embarrassed and defensive rather than enriched with a new piece of information, and tries to explain why he made the mistake rather than moving on.” — Nassim Taleb “Paper or plastic?” It’s a question you’ve been asked a thousand times but one you’ve likely never thought too deeply about. But since I’m asking now, which do you think is better for the environment? Which do you choose when presented with alternatives at the grocery store? If you’re like me, you likely choose paper, assuming that you’re doing Mother Earth a favor in the process.


The Ecotechnic Future: Envisioning a Post-Peak World by John Michael Greer

back-to-the-land, Black Swan, clean water, Community Supported Agriculture, David Strachan, deindustrialization, Easter island, European colonialism, Extropian, failed state, feminist movement, financial innovation, Francis Fukuyama: the end of history, George Santayana, hydrogen economy, hygiene hypothesis, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), invention of agriculture, Jevons paradox, Lewis Mumford, mass immigration, McMansion, oil shale / tar sands, peak oil, post-industrial society, Project for a New American Century, Ray Kurzweil, Stewart Brand, the scientific method, Thomas Kuhn: the structure of scientific revolutions, upwardly mobile, Whole Earth Catalog, Y2K

Many people predicted the First World War, but nobody dreamed that it would turn a penniless exile who wrote under the pen name “Lenin” into the Communist dictator of Russia and topple Nicholas II from what most people thought was the most secure throne in Europe. Surprises on the same scale are doubtless lying in wait in our own future. In his valuable book The Black Swan, Nassim Nicholas Taleb showed that most of the dominant facts of contemporary life have been shaped by such surprises. He pointed out, for example, that no one could have known that Google, which began as one Internet search engine among many, would rise to dominate much of the Internet, while other equally promising firms went under.1 He’s quite 37 38 T he E cotechnic F u t u re correct, but there’s another side to the story.

See Colin Tudge, Neanderthals, Bandits, and Farmers: The Origins of Agriculture, Yale University Press, 1998, for a survey of recent (and less polemical) scholarship on the origins of agriculture, on which this section is based. 5. Ernest Callenbach, Ecotopia, Banyan Tress, 1975, is the classic example. Chapter Three: A Short History of the Future 1. Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, Random House, 2007. 2. See, for example, the archives of housingpanic.blogspot.com, where nearly every element of 2008’s financial crisis was discussed at length up to three years in advance. 3. See John Kenneth Galbraith, The Great Crash 1929, Houghton Mifflin, 1954, for a discussion of the repetitive and predictable nature of speculative booms and busts. 4.

Strachan, David, “Hay fever, hygiene, and household size,” British Medical Journal 299 (1989), pp. 1259–1260. Suskind, Ron, “Faith, certainty, and the presidency of George W. Bush,” New York Times Magazine, 17 October, 2004. Tainter, Joseph A., The Collapse of Complex Societies, Cambridge University Press, 1988. Taleb, Nassim Nicholas, The Black Swan: The Impact of the Highly Improbable, Random House, 2007. Taylor, Graeme, Evolution’s Edge: The Coming Collapse and Transformation of Our World, New Society Publishers, 2008. Telleen, Maurice, The Draft Horse Primer, Rodale Press, 1977. Thornburg, Newton, Valhalla, Little, Brown, 1980.


pages: 292 words: 81,699

More Joel on Software by Joel Spolsky

a long time ago in a galaxy far, far away, AOL-Time Warner, barriers to entry, Black Swan, Build a better mousetrap, business process, call centre, Danny Hillis, David Heinemeier Hansson, Dennis Ritchie, failed state, Firefox, fixed income, functional programming, George Gilder, Larry Ellison, Larry Wall, lolcat, low cost airline, Mars Rover, Network effects, Paradox of Choice, Paul Graham, performance metric, place-making, price discrimination, prisoner's dilemma, Ray Oldenburg, Ruby on Rails, Salesforce, Sand Hill Road, Silicon Valley, slashdot, social software, Steve Ballmer, Steve Jobs, Superbowl ad, The Great Good Place, The Soul of a New Machine, Tragedy of the Commons, type inference, unpaid internship, wage slave, web application, Y Combinator

Even the most notoriously reliable systems, like AT&T’s long distance service, have had long outages (six hours in 1991) that put them at a rather embarrassing three nines . . . and AT&T’s long distance service is considered “carrier grade,” the gold standard for uptime. Keeping Internet services online suffers from the problem of black swans. Nassim Taleb, who invented the term, defines it thus (www.edge. org/3rd_culture/taleb04/taleb_indexx.html): “A black swan is an outlier, an event that lies beyond the realm of normal expectations.” Almost all Internet outages are unexpected unexpecteds: extremely lowprobability outlying surprises. They’re the kind of things that happen so rarely it doesn’t even make sense to use normal statistical methods like “mean time between failure.”

Measuring the number of minutes of downtime per year does not predict the number of minutes of downtime you’ll have the next year. It reminds me of commercial aviation today: the NTSB has done such a great job of eliminating all the common causes of crashes that nowadays, each commercial crash they investigate seems to be a crazy, one-off, black-swan outlier. Somewhere between the “extremely unreliable” level of service, where it feels like stupid outages occur again and again and again, and the “extremely reliable” level of service, where you spend millions and millions of dollars getting an extra minute of uptime a year, there’s a sweet spot, where all the expected unexpecteds have been taken care of.

We let the customer decide how much they want to be credited, up to a whole month, because not every customer is even going to notice the outage, let alone suffer from it. I hope this system will improve our 288 More from Joel on Software reliability to the point where the only outages we suffer are really the extremely unexpected black swans. P.S. Yes, we want to hire another system administrator so Michael doesn’t have to be the only one to wake up in the middle of the night. thirty-six SET YOUR PRIORITIES Wednesday, October 12, 2005 It was getting time to stop futzing around with FogBugz 4.0 and start working on 5.0. We just shipped a big service pack, fixing a zillion tiny little bugs that nobody would ever come across (and introducing a couple of new tiny little bugs that nobody will ever come across), and it was time to start adding some gen-yoo-ine new features.


pages: 204 words: 66,619

Think Like an Engineer: Use Systematic Thinking to Solve Everyday Challenges & Unlock the Inherent Values in Them by Mushtak Al-Atabi

3D printing, agricultural Revolution, Albert Einstein, Barry Marshall: ulcers, Black Swan, Blue Ocean Strategy, business climate, call centre, Clayton Christensen, clean water, cognitive bias, corporate social responsibility, dematerialisation, disruptive innovation, Elon Musk, follow your passion, global supply chain, Great Leap Forward, happiness index / gross national happiness, invention of the wheel, iterative process, James Dyson, Kickstarter, knowledge economy, Lao Tzu, Lean Startup, mirror neurons, On the Revolutions of the Heavenly Spheres, remote working, shareholder value, six sigma, Steve Jobs, Steven Pinker, systems thinking

Such highly unlikely events are called “black swans,” a term popularised by Nassim Taleb who wrote a book carrying the same title. Black swans are a manifestation of the uncertainty in the system. The term black swan is derived from the fact that the statement “All swans are white” was thought to be validated by countless observations. It took only one sighting of a swan that is black in Australia to render this statement false. Black swans can be negative, like if a meteor hits where I am sitting now; or positive, like a gold mine is discovered underneath my house. In order for us to benefit from a positive black swan, it is necessary that we build a system and a culture that encourages tinkering, experimentation, risk taking and yes, failure.

In order for us to benefit from a positive black swan, it is necessary that we build a system and a culture that encourages tinkering, experimentation, risk taking and yes, failure. This culture should prevail in both the education and business world. The history of black swans is filled with unintended discoveries such as the microwave oven, vaccination, and Viagra. These discoveries were made possible because highly motivated people kept on pushing the limits of our knowledge while keeping an open mind to capture any unexpected opportunity or a positive black swan. 12.4 Education and Encouraging Failure The importance of failure can never be underestimated in learning, progress and development. Unfortunately, the education system is geared only to celebrate success.

Chan 78 Kohlieser, George 63 leader, 13, 29, 34, 55, 58-61, 71, 117, 120, 146, 152-153, 173 leadership, 55, 58-59, 121, 154-155, 178 Lean Entrepreneurship, 191, 194 Lean Startup, 191, 193 learner, 16, 21, 28, 151, 201 lifecycle, 3, 184-185, 187 logbook, 145 management, 5-6, 12, 57-59, 81, 104, management, 5-6, 12, 57-59, 81, 104, 170, 176, 226 170, 176, 226 160, 162, 164, 166, 168, 170, 172 Mann, Darrell 71 Manoeuvrability, 164 manufacturability, 91, 98, 100 marketability, 184 Massive Online Open Course, 220 mastery, 23, 27-29, 69, 138, 174, 198 Mauborgne, Renée 78 measurement, 43, 107, 132-133, 219 media, 13, 34, 61, 128, 165, 180, 190 medication, 37 mentor, 30 Mesopotamia, 10 methodology, 82, 147, 150, 214 Middle Brain, 24, 44, 46, 142 mindset, 2, 5, 19-20, 26-30, 36, 38, 42, 69, 173-174, 200, 217 mission, 50-52, 58, 65, 183 Mission Zero, 224-226, 228 MOOC, 16, 43, 55, 64, 173, 194, 217, 216-221, 223 multidisciplinary, 5, 104, 137, 155 myelin, 22-23, 27, 30-31, 50 myelinate, 26 myelinated, 23 myelination, 23, 31 Network Diagram, 166-167, 170 neuron, 21-23, 27-28, 30-31, 50, 53 neuroscience, 22, 25 New Brain, 24-25, 32, 44, 141 NGOs, 191-193 Norming, 154-155 Operate, 3, 5, 8-9, 11, 16, 27, 29, 34, 100, 102, 110-116, 118, 120, 122, 124, 127, 130-131, 137, 151, 155, 161, 175, 178, 182, 184, 220 optimisation, 98 optimise, 106 optimism, 49-50 optimistic, 20, 174 optimum, 115, 203 Orang Asli, 55-56 Organisation chart, 152-153, 183 outliers, 27 overdesign, 100 Panasonic, 215 Panzer, 214 paradigm, 29, 69-70, 174 passion, 2, 196, 219 PDM, 167 performance, 20, 27, 29-30, 81, 89, 94, 106, 156, 170, 173, 176, 184, 186-187, 191, 198, 200-203, 226 Performing, 15, 21, 23, 27, 42, 47, 50, 70, 78, 87, 97, 113, 133, 154-155, 168, 222 personalisation, 16, 88 Picasso, 138-139 Piketty,Thomas 224 pitchin, 194 Polaroid, 97-98 positivity, 196 pozible, 194-195 presentation, 143-144 project based, 122, 225 Project Based Learning, 2 proposal, 34, 144, 162, 164 Oei,John-Son 55-56 Old Brain, 24, 44, 140 openlearning, 190, 219 Random Entry, 74-77, 215 recyclability, 98 recyclable, 101 Reduce, 9, 15, 78, 80, 85-86, 90-91, 168, 204, 225 redundancy, 100 relationship, 42, 45-47, 50, 52, 58,122, 131, 142, 152, 161, 178, 181, 223 Relationship Management, 45, 58 reliability, 90-91, 100, 107 reliable, 7, 124 renewing, 47 reptilian, 24 requirements, 7, 17, 69-70, 83, 94-95, 97-99, 106-107, 115, 159, 169, 184, 222, 225 resilience, 217, 227 resilient, 42, 174 Return on Failure, 191, 198, 200, 202, 204, 206 revenue, 81, 180-181, 225 rewire, 196, 220 rewired, 49 rewiring, 27 Risk Management, 168 Root Cause Analysis, 210 Rumsfeld, Donald 204 SaniShop, 61 sanitation, 14, 61, 175 satisfaction, 159-161, 169-170, 196, 214, 217 scalable, 191 Segway, 187-188 Self Management, 45, 48-49, 223 Self Assessment, 47 Self Awareness, 42, 46 Shakespeare, 19 shareholder, 167-177 Sim, Jack 61-62 simulation, 98, 138, 143 Sinek, Simon 29 Social Awareness, 45, 53, 57, 63, 223 SOPs, 212 Stakeholders Management, 170 stimuli, 19-20, 24, 26, 43-44, 48-49 Storming, 54, 154-155 subsystem, 7, 37, 94-95, 97, 107 subtasks, 166 SUCCES, 138 success, 2, 20, 28-30, 34, 38, 43, 45, 53, 59, 64, 70, 118, 124, 137-138, 142, 144, 59, 64, 70, 118, 124, 137-138, 142, 144, 170, 172-173, 178, 182, 198, 200-205, 216-219, 221-223 SWOT, 47-48, 58 System Architecture, 94-96 systematic, 3-4, 9, 34-35, 69, 90, 124, 191, 209, 220, 228 systematically, 5, 44, 90, 214 systemic, 36 tactile, 19 Taleb, Nassim Nicholas 204 Tandemic, 191-192 Taylor's Racing Team, 107, 116-121, 151 teamwork, 7, 26, 45, 58, 137-138, 140, 142, 144, 146, 148, 150, 152, 154, 156, 158 Tesla, 4 Trend Recognition, 82 trimming, 77, 215 Tuckman Model, 153-154 Twitter, 88 uncertainty, 75, 204 Value, 3, 5, 9, 12, 15, 27-28, 49, 52, 69, 78-81, 90-91, 93, 124, 152, 156, 168, 78-81, 90-91, 93, 124, 152, 156, 168, 212, 214-215, 218-219, 225, 228 Verification, 106 viability, 204 viable, 9, 52, 55, 91, 101 Viagra, 205 vision, 29, 50-51, 58-60, 183, 219, 224, 228 Vodafail, 190 Vodafone, 189-190 Vujicic, Nick 68 Wagner, Tony 44 Warner, Jim 46 Warner, Jim 46 165 WD, 198-199 wellbeing, 218 WMSDs, 133 WTO, 61


pages: 756 words: 120,818

The Levelling: What’s Next After Globalization by Michael O’sullivan

"World Economic Forum" Davos, 3D printing, Airbnb, Alan Greenspan, algorithmic trading, Alvin Toffler, bank run, banking crisis, barriers to entry, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, bond market vigilante , Boris Johnson, Branko Milanovic, Bretton Woods, Brexit referendum, British Empire, business cycle, business process, capital controls, carbon tax, Celtic Tiger, central bank independence, classic study, cloud computing, continuation of politics by other means, corporate governance, credit crunch, CRISPR, cryptocurrency, data science, deglobalization, deindustrialization, disinformation, disruptive innovation, distributed ledger, Donald Trump, driverless car, eurozone crisis, fake news, financial engineering, financial innovation, first-past-the-post, fixed income, gentrification, Geoffrey West, Santa Fe Institute, Gini coefficient, Glass-Steagall Act, global value chain, housing crisis, impact investing, income inequality, Intergovernmental Panel on Climate Change (IPCC), It's morning again in America, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", junk bonds, knowledge economy, liberal world order, Long Term Capital Management, longitudinal study, low interest rates, market bubble, minimum wage unemployment, new economy, Northern Rock, offshore financial centre, open economy, opioid epidemic / opioid crisis, Paris climate accords, pattern recognition, Peace of Westphalia, performance metric, Phillips curve, private military company, quantitative easing, race to the bottom, reserve currency, Robert Gordon, Robert Shiller, Robert Solow, Ronald Reagan, Scramble for Africa, secular stagnation, Silicon Valley, Sinatra Doctrine, South China Sea, South Sea Bubble, special drawing rights, Steve Bannon, Suez canal 1869, supply-chain management, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, total factor productivity, trade liberalization, tulip mania, Valery Gerasimov, Washington Consensus

Other philosophers, notably Karl Popper, sought to overlay more stringent rules that would help prove or disprove the new models resulting from paradigm shifts (he introduced the idea of falsifiability or “black swan” principle, which states that the test of whether something can be called scientific depends on whether it can be proven to be false). Indeed, Kuhn’s paradigm shift is as badly abused and misused as Popper’s notion of black swans. Both phrases have become popularized and have fallen into the vocabulary of management consultants, and as a result they have lost their meaning. For example, many people today refer to a risky scenario (e.g., could the stock market fall by 5 percent?) as a black swan event, though the original meaning of the term is quite different.

Indeed, there continue to be blistering attacks on this approach to economics from such experts as former World Bank chief economist Paul Romer, author Nassim Taleb, and former Federal Reserve governor Kevin Warsh. In their own ways they highlight the shortcomings in the socialization and groupthink of academic economists. Romer states, “As a result, if facts disconfirm the officially sanctioned theoretical vision, they are subordinated.” Taleb more provocatively holds, “Beware the semi-erudite who thinks he is an erudite. He fails to naturally detect sophistry.” And Warsh criticized the Federal Reserve: “Its models are unreliable, its policies erratic and its guidance confusing.

One field that needs more rather than less coordination and expertise is climate policy. Climate change and the increasingly obvious damage being done to the planet is something I would have liked to feature more in this book. When people ask me to state what the biggest risk to the world is (they usually use the phrase “black swan”), I usually reply that it is climate change. The slow buildup of evidence for global warming, the risks it poses to the world, the denial, and the lack of real policy change remind me all too much of the lead-up to the global financial crisis. Consistent with this template, I do not expect drastic action by the larger industrialized countries to address damage to the earth’s atmosphere until the human cost of climate change becomes stark.


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The Filter Bubble: What the Internet Is Hiding From You by Eli Pariser

A Declaration of the Independence of Cyberspace, A Pattern Language, adjacent possible, Amazon Web Services, An Inconvenient Truth, Apple Newton, augmented reality, back-to-the-land, Black Swan, borderless world, Build a better mousetrap, Cass Sunstein, citizen journalism, cloud computing, cognitive dissonance, crowdsourcing, Danny Hillis, data acquisition, disintermediation, don't be evil, Filter Bubble, Flash crash, fundamental attribution error, Gabriella Coleman, global village, Haight Ashbury, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, jimmy wales, John Perry Barlow, Kevin Kelly, knowledge worker, Mark Zuckerberg, Marshall McLuhan, megacity, Metcalfe’s law, Netflix Prize, new economy, PageRank, Paradox of Choice, Patri Friedman, paypal mafia, Peter Thiel, power law, recommendation engine, RFID, Robert Metcalfe, sentiment analysis, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, social graph, social software, social web, speech recognition, Startup school, statistical model, stem cell, Steve Jobs, Steven Levy, Stewart Brand, technoutopianism, Ted Nordhaus, The future is already here, the scientific method, urban planning, We are as Gods, Whole Earth Catalog, WikiLeaks, Y Combinator, Yochai Benkler

., xxi–xxii. 83 “predictably irrational”: Dan Ariely, Predictably Irrational: The Hidden Forces That Shape Our Decisions (New York: HarperCollins, 2008) 83 figuring out what makes us happy: Dan Gilbert, Stumbling on Happiness (New York: Knopf, 2006). 83 only one part of the story: Kathryn Schulz, Being Wrong: Adventures in the Margin of Error (New York: HarperCollins, 2010). 84 “Information wants to be reduced”: Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007), 64. 85 quickly converted into schemata: Doris Graber, Processing the News: How People Tame the Information Tide (New York: Longman, 1988). 85 “condensation of all features of a story”: Ibid., 161. 85 woman celebrating her birthday: Steven James Breckler, James M.

Popper posed his problem in a slightly different way: Just because you’ve only ever seen white swans doesn’t mean that all swans are white. What you have to look for is the black swan, the counterexample that proves the theory wrong. “Falsifiability,” Popper argued, was the key to the search for truth: The purpose of science, for Popper, was to advance the biggest claims for which one could not find any countervailing examples, any black swans. Underlying Popper’s view was a deep humility about scientifically induced knowledge—a sense that we’re wrong as often as we’re right, and we usually don’t know when we are.

Even for animals with rudimentary senses, nearly all of the information coming in through their senses is meaningless, but a tiny sliver is important and sometimes life-preserving. One of the primary functions of the brain is to identify that sliver and decide what to do about it. In humans, one of the first steps is to massively compress the data. As Nassim Nicholas Taleb says, “Information wants to be reduced,” and every second we reduce a lot of it—compressing most of what our eyes see and ears hear into concepts that capture the gist. Psychologists call these concepts schemata (one of them is a schema), and they’re beginning to be able to identify particular neurons or sets of neurons that correlate with each one—firing, for example, when you recognize a particular object, like a chair.


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The New Nomads: How the Migration Revolution Is Making the World a Better Place by Felix Marquardt

"World Economic Forum" Davos, agricultural Revolution, Anthropocene, Black Lives Matter, Black Swan, Boris Johnson, Bretton Woods, Brexit referendum, British Empire, carbon footprint, carbon tax, coronavirus, COVID-19, dark matter, digital nomad, Donald Trump, George Floyd, ghettoisation, glass ceiling, green new deal, Greta Thunberg, Intergovernmental Panel on Climate Change (IPCC), Joi Ito, Kickstarter, knowledge economy, labour market flexibility, Les Trente Glorieuses, out of africa, phenotype, place-making, Ponzi scheme, pre–internet, QAnon, Ray Kurzweil, remote working, Richard Feynman, road to serfdom, Silicon Valley, Skype, Snapchat, social distancing, sustainable-tourism, technological solutionism, technoutopianism, Yogi Berra, young professional

Black Elephant is a rare, magical pachyderm born in confinement, somewhere between a platformless media, an artistic current, a think tank and an influence ecosystem. The name is derived from Nassim Taleb’s Black Swan, an unforeseen event with momentous consequences, as some people have taken to describing Covid-19. But for decades now, countless experts have been warning us that such a pandemic was bound to happen. The coronavirus is hence not a black swan but rather what happens when the elephant in the room crashes the party and defecates on the dinner table. It is what happens when we choose to ignore the unsustainability of our civilisation’s present course.

movement and 48–54, 69, 123–7, 130, 145–6 Black Elephant and 232–9, 241 communities/networks, importance of to 161–2 education 29–30, 43–4, 45, 56–7 family background 26, 32–8, 41, 42, 43, 47 Greek roots 35, 36, 37, 43, 47 ‘hyper-nomad’ past 188–9 Islam, conversion to 24, 25 Kawaakibi Foundation and 24–6 marriage 24, 27, 63 Parisian childhood 38–43 Paris terror attacks and 23–6 Sweden, emigration to 25–7 transformative power of migration in life of 23–47 United States and 26, 34–8, 41–4, 47 WEF/Davos and see World Economic Forum Youthonomics Global Index (YGI) and see Youthonomics Global Index (YGI) Zagreb, Croatia, travels to during war in Yugoslavia (1993) 44–5 Marquardt, Horst (FM’s grandfather) 33–4, 36 Marquardt, Nikki (FM’s mother) 35–6, 37–8, 39, 47, 116 Marquardt, Sigrid (FM’s grandmother) 33, 34, 47 Maskoun, Amr 169–73 Maskoun, Ghazwa 170, 171 Maskoun, Lama 170–1 Maskoun, Nador 171 Maskoun, Shahm 169–70, 171 Maskoun, Wahid 170–1 Mateschitz, Dietrich 71 Mauritania 148 Ma Voisine (My Neighbour) 239 May, Theresa 146 Meadows, Dennis: The Limits of Growth 237 Mediterranean, migrants crossing 9, 122, 148–50, 152, 160, 238 meritocracy 20, 54, 210–11, 234 Mexico 201–8, 209 mid-sized countries, fast-growing 76 migration economic 122–47 see also economic migration education and 48–69 see also education, immigration and emigration and 93–121 see also emigration entrepreneurs and 70–92 see also entrepreneurs, migration and Felix Marquardt, transformative power in life of 23–47 see also Marquardt, Felix internal ix, 10 labelling of 169–200 see also labelling, migration and multilateral phenomenon 72–92 nomadism and see nomadism ‘out of Africa’ migration of early humans 9, 18, 69 pushback against 201–23 see also liberals refugees and 148–68 see also refugees South-South 74, 85–90 World Economic Forum, Davos and see World Economic Forum, Davos ‘migrant’ term 9, 174–5 Millicom 83–4 Mirian (Spanish migrant in London) 128, 129 Mitterrand, François 188 mobility injustice 53 Mokless 124 Monbiot, George 195 Montaigne 57 Montana, US 1–4, 7–8, 13, 14, 22, 34, 166, 229, 232, 238 Morrison, Toni: Beloved 169 Mozambique 97 multilateral phenomenon, migration as 72–92 Muslims 4, 23–5, 27, 51, 52, 102, 105, 134, 137, 139, 140, 153, 185, 209, 234 Myanmar 89 Nando’s 80–1 nationalism 8–9, 16, 27, 30, 140, 239 nation, definition of 21 Naveed (entrepreneur) 75–82, 92 Nayyar (entrepreneur) 142, 143 New Nomad Visa 233 New York, US 27, 34, 35, 35–7, 38, 43, 61–2, 75, 76, 116, 122, 137, 186, 191, 196, 220 New York Times 115, 126 nomadism changing perceptions of 31 digital nomad see digital nomad networks and 153 ‘nomad’, etymology/usage of 18, 31–2, 187, 226, 227 pre-agricultural 9–10, 18, 187 reclamation of term/giving equal weight to mobility and location 226, 228–9, 232 Northfield Mount Hermon (NMH), US 44 Norway 59, 128, 130, 145 Nussimbaum, Lev 27 Obama, Barack 30, 113, 123, 210, 213–14 online communities/virtual friendships 164–8 Ortega, Anamari Garcia ‘Annie’ 201–4, 205–8, 210, 218, 223, 229 Othering African American emigration and 111 Brexit and 15–16 defined 15–16 hallmark of sedentary civilisation 16 humour and 173 labelling and 111, 168 leaving behind 21, 228 liberals and 209–10 refugees and 168 Pablo (Barcelona) 154, 156 Palau 65–6 Paris, France African American immigrants in 111–14 banlieue 51, 55, 115 digital nomads in 188, 190–1, 194, 196 emigration from 116–21 FM’s family and 34, 37–42, 111–17 ISIS terror attacks (7 January 2015) 23–6 youth opportunity/unemployment in 48–54, 55, 69, 123–7, 130, 145–6 ‘Patriot’ movement, US 64 Pauly, Daniel 86 People’s Pilgrimage (climate march) 218–21 Phoenicians 57 pioneering spirit 51, 54, 93, 229 piroguistes (youngsters who risk their lives on rafts while trying to enter Europe) 148–9 Pizza Pie 76 Poe, Edgar Allan: Marginalia 23 populism 8–9, 16, 30, 31, 90, 158–9, 210, 218, 230 post-traumatic growth 19, 167 progressive myth 19–20 Rabelais 57 Rachid (Ch’klah) (rapper) 50–2, 55, 59, 68 racism 60, 227 Africa and 115 China and 131 emigration and 111–15 France and 52 Japan and 95 Othering and 15 suffering of both racist and victim of 21, 115 US and 7, 8, 44, 83, 111–15, 202, 207, 208, 209, 210 refugees 9, 19, 62, 70, 102, 147, 148–64, 167–8, 169–75, 207, 231, 236 African refugees in Europe 9, 122, 148–57, 158, 161, 167, 229, 236 criminals profiting from 160 early humans and 147 health concerns over 161 Israel and 157–8 labelling/oversimplification of 169–82 ‘migrant’ term and 9, 19 Mediterranean, crossing of in boats/rafts 9, 122, 148–50, 152, 160, 238 motivations behind a refugee’s movement compared to other migrants 158 networks/community, reliance on and creation of 150–7, 161–8 online communities/virtual friendships and 164–8 ‘Othering’ and 168 social media and 163–4 Spain and 148–57, 158, 161, 167, 229, 236 as ‘successful’ migrant 19 Syrian 169–75, 179–82 terrorists among, fear/risk of 160 uneasiness people feel about 159–61 United States and 156, 157, 158 René (Paraguay) 89 ‘republican equality of chances’ (les valeurs de la République) 20, 211 Ribbenvik, Mikael 174 Rice, Condoleezza 28 Rivas, Franco 205–6 Rocket Internet 79 Romain (Parisian entrepreneur) 55, 59 Russia 27, 32, 33, 70, 80, 102, 164, 175–6 Saakashvili, Mikheil 176, 177 SAE Asia 138 Said, Edward 39 Said, Kurban 27 Salina, Kansas 201–3 Sall, Macky 134 Sanbar, Jamie 102–7, 115–16, 118, 119 Saño, Yeb 218 Sarmiento, Gonzalo Sanchez 190–4, 197, 199 Saudi Arabia 24 Sciences Po, Paris 54, 118 Seattle Freeze 26–7 Second World War (1939–45) 32, 36, 42–3, 100, 125, 157 sedentarism 11, 13, 16, 40, 222, 226, 227, 228 Seely, Jeff 3, 4, 7–8, 14, 21, 234 Senegal 83, 98–9, 132–5, 145, 148–9, 152, 155, 162 7-Eleven 179–81 Shake Shack 81 Shakespeare, William: Romeo and Juliet 93 Shanghai, China 73, 132, 136, 137 shifting baselines 86 Shinagawa, Natsuno 93–9, 100, 102, 107, 115, 119, 122, 229, 236 Shoprite 88 Sieben, Henry 1, 2 Sieben Live Stock Company/Ranch Sieben, Montana, US 1–5, 21–2, 34, 233–4 Sierra Leone 63, 67–8 Silicon Valley, US 177, 187, 211 Singapore 94, 107, 108–9, 110, 178, 191, 240 Singularity University 191 sixth species’ extinction 216 slavery 44, 114 Slovenia 116, 118 Smale, Alison 53 social media 68, 163–4, 172, 189, 192, 196 Södermalm, Stockholm 181, 208 South Africa 24, 86–8, 156 southern Europe, youth emigration from 128–30 South-South migration 74, 85–90 Spain 126 African migrants in 148–56, 161, 229 youth emigration from 128–30 Spencer, Thomas 71 Spur Steak Ranch, South Africa 87–8, 89 Stafstrom, Isaac 2, 3 Stanford University 2, 7, 233, 234 Stockholm, Sweden 26–7, 179–82, 191, 208, 212–15 Sweden 26–7, 82–3, 85, 179–82, 191, 208, 212–15 Syria 9, 10, 169–73, 176, 179 Taleb, Nassim: Black Swan 236 Tanzania 76–7, 79–80, 81, 82, 83–5, 88, 97, 114 Teshuva (הבושת) (repentance or salvation) 17 Tetlow, Daniel 101 Thunberg, Greta 214, 221 Thunder Competition 154 The Times 125 Tola 239 Tomlinson, Sally 100 Tompkins, Berenice 218–21, 223, 229 Total 28 ‘totalitarian corporatism’ 32 Tounkara, Fatou 155 Tounkara, Lamine 148–57, 158, 161, 167, 229, 236 Tounkara, Salim 154–5 transfer of wealth, parent-child 127 Trump, Donald climate change and 217 immigration policies of administration 201–10 supporters of, liberal attitudes towards 1–8, 12, 13–14, 16, 21–2, 28, 30, 47, 59, 68, 99, 113, 119, 133, 166, 201–23, 224, 232–4, 235, 238, 241 Tunisia 24, 27, 63 Ukraine 76, 80, 176 unemployment, youth France 48–54, 123–7 Spain 128–30 Youthonomics Global Index (YGI) and 127–30 United Arab Emirates 75, 76–7, 81, 171 United States: African American emigration from 44, 111–15 African immigrants in (‘Abdi’) 1–8, 12, 13–14, 21–2, 47, 59, 68, 133, 218, 224, 232–4, 235, 238, 241 American Civil War (1861–5) 1 American Dream 20, 35, 72, 73, 81, 196, 211, 234 American Exceptionalism 28, 35 Central American immigrants and 9, 10 children separated from their parents at Mexican border 201–2 climate change and 218–21 county supremacy doctrine 64 dual citizenship and Covid-19 in 185–6 employer enterprise birth rate in 144 entrepreneurs, immigrant 71–2, 81–85 FM’s childhood and 42, 43–5 FM’s family and 34–8, 39, 41, 42, 43–5, 47 Mexican border internment camps 168, 201–2, 205–8 Mexican immigrants in 201–8, 209 Obama and see Obama, Barack refugees and 156, 157, 158 Second World War and 32, 34 Swedish immigrants in 2, 47, 82–3 Trump and see Trump, Donald Trump supporters within, liberal dismissal of 1–8, 12, 13–14, 16, 21–2, 28, 30, 47, 59, 68, 99, 113, 119, 133, 166, 201–23, 224, 232–4, 235, 238, 241 Youthonomics Global Index (YGI) and 130, 139–46 University of Cape Coast, Ghana 134 USAID 79 Venezuela 163, 176, 231 Vengetsamy, Ravendra ‘Son’ 85–90 Victor (Spanish migrant in London) 128, 129 Videlles, France 42 Virgil: Aeneid 201 virtual friendship 164–8 vulgarisation (ability to explain very complicated ideas in layman’s terms) 55–6 Waseda University, Tokyo 96–7 Wertheimer, Ashley 1–2 white supremacism 15, 21 Williams, Thomas Chatterton 111–14, 115 Losing My Cool 113–14 ‘The Next Great Migration’ article 115 World Economic Forum, Davos 28, 230 ‘Davos man’ 195–6 as parody of diversity 232–5 shutting down 240–1 (2017) 30–1, 187, 232–4, 235 (2020) 237, 239–40 (2021) (exceptional meeting, Singapore) 240 World of Warcraft (multiplayer game) 165 Wright, Richard: I Choose Exile 113 Yassir (Indian entrepreneur) 140–5 Young, Toby 210 Youthonomics Global Index (YGI) 127–30, 139–40, 145, 146 Yugoslavia, war in (1991–2001) 44–5 Zandi, Emmanuella 239 Zulu restaurant, Ciudad del Este, Paraguay 85–6 Zweig, Stefan 62 First published in Great Britain by Simon & Schuster UK Ltd, 2021 Copyright © Felix Marquardt, 2021 The right of Felix Marquardt to be identified as the author of this work has been asserted in accordance with the Copyright, Designs and Patents Act, 1988.


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Quantitative Value: A Practitioner's Guide to Automating Intelligent Investment and Eliminating Behavioral Errors by Wesley R. Gray, Tobias E. Carlisle

activist fund / activist shareholder / activist investor, Alan Greenspan, Albert Einstein, Andrei Shleifer, asset allocation, Atul Gawande, backtesting, beat the dealer, Black Swan, book value, business cycle, butter production in bangladesh, buy and hold, capital asset pricing model, Checklist Manifesto, cognitive bias, compound rate of return, corporate governance, correlation coefficient, credit crunch, Daniel Kahneman / Amos Tversky, discounted cash flows, Edward Thorp, Eugene Fama: efficient market hypothesis, financial engineering, forensic accounting, Henry Singleton, hindsight bias, intangible asset, Jim Simons, Louis Bachelier, p-value, passive investing, performance metric, quantitative hedge fund, random walk, Richard Thaler, risk free rate, risk-adjusted returns, Robert Shiller, shareholder value, Sharpe ratio, short selling, statistical model, stock buybacks, survivorship bias, systematic trading, Teledyne, The Myth of the Rational Market, time value of money, transaction costs

Green, “Mutual Fund Flows and Performance in Rational Markets.” Journal of Political Economy 112 (2004): 1269–1295. 6. Leinweber. 7. J. D. Freeman, “Behind the Smoke and Mirrors: Gauging the Integrity of Investment Simulations,” Financial Analysts Journal 48 (6) (November–December 1992): 26–31. 8. Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 9. Claire I. Tsai, Joshua Klayman, and Reid Hastie, “Effects of Amount of Information on Judgment Accuracy and Confidence.” Organizational Behavior and Human Decision Processes 107 (2008): 97–105. Available at http://ssrn.com/abstract=1297347. 10.

In short, even the best-trained investors would make the same mistakes that investors have been making forever, and for the same immutable reason—that they cannot help it. If mere awareness that our judgments are biased does little to correct the errors we make, how then can we protect against these errors? Nassim Taleb, author of Fooled by Randomness44and who calls himself a “literary essayist and mathematical trader,” argues that we should not even attempt to correct our behavioral flaws, but should instead seek to “go around” our emotions: We are faulty and there is no need to bother trying to correct our flaws.

As an empiricist (actually a skeptical empiricist) I despise the moralizers beyond anything on this planet: I wonder why they blindly believe in ineffectual methods. Delivering advice assumes that our cognitive apparatus rather than our emotional machinery exerts some meaningful control over our actions. We will see how modern behavioral science shows this to be completely untrue. Research seems to support Taleb's method—tricking ourselves into doing the right thing—works better than simply trying to do the right thing (or flagellating ourselves if we don't).45 Montier says, “Even once we are aware of our biases, we must recognize that knowledge does not equal behavior. The solution lies in designing and adopting an investment process that is at least partially robust to behavioral decision-making errors.”46The advantage of the quantitative method is that it starts with the idea that most of us are temperamentally unsuited to investment, and then seeks to protect against those potential errors.


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The Bitcoin Standard: The Decentralized Alternative to Central Banking by Saifedean Ammous

"World Economic Forum" Davos, Airbnb, Alan Greenspan, altcoin, bank run, banks create money, bitcoin, Black Swan, blockchain, Bretton Woods, British Empire, business cycle, capital controls, central bank independence, Charles Babbage, conceptual framework, creative destruction, cryptocurrency, currency manipulation / currency intervention, currency peg, delayed gratification, disintermediation, distributed ledger, Elisha Otis, Ethereum, ethereum blockchain, fiat currency, fixed income, floating exchange rates, Fractional reserve banking, full employment, George Gilder, Glass-Steagall Act, global reserve currency, high net worth, initial coin offering, invention of the telegraph, Isaac Newton, iterative process, jimmy wales, Joseph Schumpeter, low interest rates, market bubble, market clearing, means of production, military-industrial complex, Money creation, money: store of value / unit of account / medium of exchange, moral hazard, Network effects, Paul Samuelson, peer-to-peer, Peter Thiel, price mechanism, price stability, profit motive, QR code, quantum cryptography, ransomware, reserve currency, Richard Feynman, risk tolerance, Satoshi Nakamoto, scientific management, secular stagnation, smart contracts, special drawing rights, Stanford marshmallow experiment, The Nature of the Firm, the payments system, too big to fail, transaction costs, Walter Mischel, We are all Keynesians now, zero-sum game

Keynes, “The End of Laissez‐Faire,” in Essays in Persuasion, pp. 272–295. 18 Murray Rothbard, “A Conversation with Murray Rothbard,” Austrian Economics Newsletter, vol. 11, no. 2 (Summer 1990). 19 John Kenneth Galbraith, The Great Crash 1929 (Boston, Ma: Houghton Mifflin Harcourt, 1997), p. 133. 20 If for some reason you haven't already, you really should read Nassim Nicholas Taleb's works on this: Fooled by Randomness, The Black Swan, Antifragility, and Skin in the Game. 21 For more on this topic, see James M. Buchanan and Gordon Tullock, The Calculus of Consent: Logical Foundations of Constitutional Democracy (1962). 22 Mark Skousen, “The Perseverance of Paul Samuelson's Economics,” Journal of Economic Perspectives, vol. 11, no. 2 (1997): 137–152. 23 David Levy and Sandra Peart, “Soviet Growth and American Textbooks: An Endogenous Past,” Journal of Economic Behavior & Organization, vol. 78, issues 1–2 (April 2011): 110–125. 24 Mark Skousen, “The Perseverance of Paul Samuelson's Economics,” Journal of Economic Perspectives, vol. 11, no. 2 (1997): 137–152. 25 Paul Krugman, “Secular Stagnation, Coalmines, Bubbles, and Larry Summers,” New York Times, November 16, 2003. 26 For a formal modeling of this statement, see D.

Szabo, Nick. 2001. Trusted Third Parties Are Security Holes. Available on NakamotoInstitute.org Szabo, Nick. Shelling Out: The Origins of Money. (2002). Available on NakamotoInstitute.org Taleb, Nassim Nicholas. Antifragile: How to Live in a World We Don't Understand. London: Allen Lane, 2012. _____. Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets. Random House, 2005. _____. The Black Swan: The Impact of the Highly Improbable. Random House, 2007. Thiel, Peter. From Zero to One: Notes on Start‐ups, or How to Build the Future. Crown Business, 2014. Zweig, Stefan. The World of Yesterday: Memoirs of a European.

And to Satoshi Nakamoto, who gave me something worth writing about. About the Author Saifedean Ammous is a Professor of Economics at the Lebanese American University and member of the Center on Capitalism and Society at Columbia University. He holds a PhD in Sustainable Development from Columbia University. Foreword by Nassim Nicholas Taleb Let us follow the logic of things from the beginning. Or, rather, from the end: modern times. We are, as I am writing these lines, witnessing a complete riot against some class of experts, in domains that are too difficult for us to understand, such as macroeconomic reality, and in which not only is the expert not an expert, but he doesn't know it.


pages: 350 words: 103,270

The Devil's Derivatives: The Untold Story of the Slick Traders and Hapless Regulators Who Almost Blew Up Wall Street . . . And Are Ready to Do It Again by Nicholas Dunbar

Alan Greenspan, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, behavioural economics, Black Swan, Black-Scholes formula, bonus culture, book value, break the buck, buy and hold, capital asset pricing model, Carmen Reinhart, Cass Sunstein, collateralized debt obligation, commoditize, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, delayed gratification, diversification, Edmond Halley, facts on the ground, fear index, financial innovation, fixed income, George Akerlof, Glass-Steagall Act, Greenspan put, implied volatility, index fund, interest rate derivative, interest rate swap, Isaac Newton, John Meriwether, junk bonds, Kenneth Rogoff, Kickstarter, Long Term Capital Management, margin call, market bubble, money market fund, Myron Scholes, Nick Leeson, Northern Rock, offshore financial centre, Paul Samuelson, price mechanism, proprietary trading, regulatory arbitrage, rent-seeking, Richard Thaler, risk free rate, risk tolerance, risk/return, Ronald Reagan, Salesforce, Savings and loan crisis, seminal paper, shareholder value, short selling, statistical model, subprime mortgage crisis, The Chicago School, Thomas Bayes, time value of money, too big to fail, transaction costs, value at risk, Vanguard fund, yield curve, zero-sum game

Solving these problems was an ample test of PhD-level math skills. On the final leg of my trip in April 1998, I went to New York, where I had brunch with Nassim Taleb, an option trader at the French bank Paribas (now part of BNP Paribas). Not yet the fiery, best-selling intellectual he subsequently became (author of 2007’s The Black Swan), Taleb had already attacked VAR in a 1997 magazine interview as “charlatanism,” but he was in no doubt about how options theory had changed the world. “Merton had the premonition,” Taleb said admiringly. “One needs arbitrageurs to make markets efficient, and option markets provide attractive opportunities for replicators.

Nitpickers will point out that the economics Nobel Prize was not actually established by the inventor of dynamite but was rather an add-on created by the Swedish central bank in his memory. 7. Robert C. Merton, Continuous-Time Finance (Cambridge, MA: Blackwell, 1990), chap. 14. 8. After our meeting, Taleb wrote up his views as an article, “How the Ought Became the Is,” which I published in a Black-Scholes twenty-fifth anniversary supplement for the trade magazine Futures & Options World in July 1998. 9. See Nassim Taleb and Pablo Triana, “Bystanders to This Financial Crime Were Many,” Financial Times, December 8, 2008. 10. For example, see the report Improving Counterparty Risk Management Practices published in June 1999 by an industry working group chaired by Gerald Corrigan. 11.

Motivated to find the balance between collective and individual greed, with little prompting by regulators, Goldman managed to get the governance right. If markets didn’t evolve and financial innovation didn’t take place, that might be the end of the story—a happy ending provided by VAR models. But this story does not have a happy ending. VAR quickly became dangerous not so much because of technical pitfalls like “black swans” or “fat tails,” but because it was used as an incentive rather than as a restraint. Suppose that a way could be found to stop scrabbling around as a middleman and earn big money instead by making bets—but without the risk. And suppose that the VAR system—the policing mechanism keeping the firm safe—said that the bet had low VAR and didn’t require much capital.


pages: 428 words: 103,544

The Data Detective: Ten Easy Rules to Make Sense of Statistics by Tim Harford

Abraham Wald, access to a mobile phone, Ada Lovelace, affirmative action, algorithmic bias, Automated Insights, banking crisis, basic income, behavioural economics, Black Lives Matter, Black Swan, Bretton Woods, British Empire, business cycle, Cambridge Analytica, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, Charles Babbage, clean water, collapse of Lehman Brothers, contact tracing, coronavirus, correlation does not imply causation, COVID-19, cuban missile crisis, Daniel Kahneman / Amos Tversky, data science, David Attenborough, Diane Coyle, disinformation, Donald Trump, Estimating the Reproducibility of Psychological Science, experimental subject, fake news, financial innovation, Florence Nightingale: pie chart, Gini coefficient, Great Leap Forward, Hans Rosling, high-speed rail, income inequality, Isaac Newton, Jeremy Corbyn, job automation, Kickstarter, life extension, meta-analysis, microcredit, Milgram experiment, moral panic, Netflix Prize, Northpointe / Correctional Offender Management Profiling for Alternative Sanctions, opioid epidemic / opioid crisis, Paul Samuelson, Phillips curve, publication bias, publish or perish, random walk, randomized controlled trial, recommendation engine, replication crisis, Richard Feynman, Richard Thaler, rolodex, Ronald Reagan, selection bias, sentiment analysis, Silicon Valley, sorting algorithm, sparse data, statistical model, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, survivorship bias, systematic bias, TED Talk, universal basic income, W. E. B. Du Bois, When a measure becomes a target

Of course, this was bad news worth being aware of: problems in these markets were at the center of the catastrophic financial crisis of 2007–08, and Gillian Tett was one of the few people who could honestly say she’d been paying attention beforehand.25 Some commentators argue that the cure for all this is simply to stop reading the newspapers. The author Rolf Dobelli—amusingly, writing in the Guardian newspaper—gives us ten reasons to stop reading the news.26 Nassim Taleb, author of The Black Swan, puts it succinctly: “To be completely cured of newspapers, spend a year reading the previous week’s newspapers.”27 Because I work for a newspaper, you might expect me to protest. I have a lot of sympathy, though. I often find that my Saturday Financial Times column is unmoored from the news of the week.

See also choice research Bell, Vanessa, 256–57 Bem, Daryl, 111, 113–14, 119–23 benefits of statistical analysis, 9 Berti, Gasparo, 172 Bevacqua, Graciela, 194–95, 212 Beyth, Ruth, 248–49, 251, 254 biases biased assimilation, 35–36 confirmation bias, 33 current offense bias, 169 and motivated reasoning, 27–29, 32–36, 38, 131, 268 negativity bias, 95–99 non-response bias, 146–47 novelty bias, 95–99, 113, 114, 122 optimism bias, 96 and power of doubt, 13 publication bias, 113–16, 118–23, 125–27 racial bias in criminal justice, 176–79 in sampling, 135–38, 142–45, 147–51 selection bias, 2, 245–46 survivorship bias, 109–10, 112–13, 122–26 systematic bias in algorithms, 166 and value of statistical knowledge, 17 big data and certification of researchers, 182 and criminal justice, 176–79 and excessive credulity in data, 164–67 and found data, 149, 151, 152, 154 and Google Flu Trends, 153–57 historical perspective on, 171–75 influence in today’s world, 183 limitations and misuse of, 159–63, 170–71 proliferation of, 157–59 and teacher evaluations, 163–64 See also algorithms Big Data (Cukier and Mayer-Schönberger), 148, 157 “Big Duck” graphics, 216–18, 217, 229–30 Big Issue, The, 226n “Billion Pound-O-Gram, The” (infographic), 223 billionaires, 78–80 binge drinking, 75 Bird, Sheila, 68 bird’s-eye view of data, 61–64, 203, 221, 265 BizzFit, 108 Black Swan, The (Taleb), 101 Blastland, Michael, 10, 68, 93 blogs, 76 Bloomberg TV, 89 body count metrics, 58 Boijmans Museum, 20 Boon, Gerard, 19, 30–31 border wall debate, 93–94 Borges, Jorge Luis, 118 Boyle, Robert, 172–75 brain physiology, 270 Bredius, Abraham, 19–23, 29–32, 35, 43–45, 78, 242, 262 Bretton Woods conference, 262 Brettschneider, Brian, 224 Brexit, 71, 277 British Army, 213–14, 220–21 British Election Study, 145–46 British Medical Journal, 6, 67 British Treasury, 256–57 Broward County Sheriff’s Office, 176 Brown, Derren, 115 Brown, Zack “Danger,” 108 Buchanan, Larry, 229, 232 budget deficits, 188, 192–93, 195 Buffett, Warren, 259 Bureau of Economic Analysis, 190, 205 Bureau of Labor Statistics, 190, 205, 212 business-cycle forecasting, 258–59 business writing, 123–24 Butoyi, Imelda, 62–63 Cairo, Alberto, 227 Cambridge Analytica, 158 Cambridge University, 162.

It’s easy to mock Peters and Waterman—and people did—but the truth is that a healthy economy has a lot of churn in it. Corporate stars rise, and burn out. Sometimes they have lasting qualities, sometimes fleeting ones, and sometimes no qualities at all, bar some luck. By all means look at the success stories and try to learn lessons, but be careful. It is easy, in Nassim Taleb’s memorable phrase, to be “fooled by randomness.” Perhaps all such business writing is harmless: when daily data from the shop floor contradict the business-book wisdom, the shop floor will win. While the jam study became famous among the chattering classes, there is scant sign that many businesses took the “Choice is bad” finding seriously in the decisions they made about stocking their shelves.


pages: 304 words: 80,965

What They Do With Your Money: How the Financial System Fails Us, and How to Fix It by Stephen Davis, Jon Lukomnik, David Pitt-Watson

activist fund / activist shareholder / activist investor, Admiral Zheng, banking crisis, Basel III, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, buy and hold, Carl Icahn, centralized clearinghouse, clean water, compensation consultant, computerized trading, corporate governance, correlation does not imply causation, credit crunch, Credit Default Swap, crowdsourcing, David Brooks, Dissolution of the Soviet Union, diversification, diversified portfolio, en.wikipedia.org, financial engineering, financial innovation, financial intermediation, fixed income, Flash crash, Glass-Steagall Act, income inequality, index fund, information asymmetry, invisible hand, John Bogle, Kenneth Arrow, Kickstarter, light touch regulation, London Whale, Long Term Capital Management, moral hazard, Myron Scholes, Northern Rock, passive investing, Paul Volcker talking about ATMs, payment for order flow, performance metric, Ponzi scheme, post-work, principal–agent problem, rent-seeking, Ronald Coase, seminal paper, shareholder value, Silicon Valley, South Sea Bubble, sovereign wealth fund, statistical model, Steve Jobs, the market place, The Wealth of Nations by Adam Smith, transaction costs, Upton Sinclair, value at risk, WikiLeaks

For example, during the passage of the Dodd-Frank Act (the keystone regulation passed in the United States to regulate banks following the 2008 crisis), it was reported that six thousand lobbyists were employed to make sure it did not cut off lucrative revenue streams to the finance industry. See http//:thenation.com/article/174113/how-wall-street-defanged-dodd-frank. 48. See Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, 2nd ed. (Random House, 2010), 284. 6 The Queen’s Question 1. “The Queen Asks Why No One Saw the Credit Crunch Coming,” The Telegraph, November 5, 2008. 2. Sky News, December 14, 2012, www.youtube.com/watch?v=wADO zwSTJGQ. 3. See Higher Education Statistics Agency, www.hesa.ac.uk/content/view/1897/239. 4.

En.wikipedia.org/wiki/There_are_known_knowns. 35. Some economists, notably Frank Knight at the University of Chicago, have written extensively about the dichotomy between predictable risk and uncertainty, which cannot be calculated. But many continue to focus only on risk. 36. Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (Random House, 2010), xxxix. 37. Andrew G. Haldane, “Tails of the Unexpected,” speech given at University of Edinburgh, June 8–9, 2012, p. 20, http://www.bankofengland.co.uk/publications/Documents/speeches/2012/speech582.pdf. 38. From Haldane, “Tails of the Unexpected.”

There are too many possibilities, and too many uncertainties.35 The second point has to do with whether the normal curve and its variants describe the distribution of real world phenomena. Even if we set aside the problem of “unknown unknowns,” evidence suggests that economic phenomena are not normally distributed, because extreme events are much more likely than the Gaussian bell curve predicts. Nassim Taleb concludes that analyses based on bell curves tell you “close to nothing” because “they ignore large deviations, cannot handle them, yet make us confident that we have tamed uncertainty.”36 Andy Haldane, director of the Bank of England, opined that although “normality has been an accepted wisdom in economics and finance for a century or more … in real world systems, nothing could be less normal than normality.”37 Part of the problem is that Gauss never intended his distributions to be used in economics.


The Myth of Artificial Intelligence: Why Computers Can't Think the Way We Do by Erik J. Larson

AI winter, Alan Turing: On Computable Numbers, with an Application to the Entscheidungsproblem, Albert Einstein, Alignment Problem, AlphaGo, Amazon Mechanical Turk, artificial general intelligence, autonomous vehicles, Big Tech, Black Swan, Bletchley Park, Boeing 737 MAX, business intelligence, Charles Babbage, Claude Shannon: information theory, Computing Machinery and Intelligence, conceptual framework, correlation does not imply causation, data science, deep learning, DeepMind, driverless car, Elon Musk, Ernest Rutherford, Filter Bubble, Geoffrey Hinton, Georg Cantor, Higgs boson, hive mind, ImageNet competition, information retrieval, invention of the printing press, invention of the wheel, Isaac Newton, Jaron Lanier, Jeff Hawkins, John von Neumann, Kevin Kelly, Large Hadron Collider, Law of Accelerating Returns, Lewis Mumford, Loebner Prize, machine readable, machine translation, Nate Silver, natural language processing, Nick Bostrom, Norbert Wiener, PageRank, PalmPilot, paperclip maximiser, pattern recognition, Peter Thiel, public intellectual, Ray Kurzweil, retrograde motion, self-driving car, semantic web, Silicon Valley, social intelligence, speech recognition, statistical model, Stephen Hawking, superintelligent machines, tacit knowledge, technological singularity, TED Talk, The Coming Technological Singularity, the long tail, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, theory of mind, Turing machine, Turing test, Vernor Vinge, Watson beat the top human players on Jeopardy!, Yochai Benkler

They involve complex decisions coupled with fat-­tailed probability distributions, and high-­impact consequences. Think stock market crashes. Taleb fin­gers overconfidence in induction as a key ­factor in exacerbating the impact of t­hese events. It’s not just that our inductive methods d­ on’t work, it’s that when we rely on them we fail to make use of better approaches, with potentially catastrophic consequences. In effect, we get locked into machine thinking, when analyzing the past is of no help. This is one reason that inductive superintelligence 130 T he P rob­lem of I nference ­ ill generate stupid outcomes. As Taleb quips, it is impor­tant to know w how “not to become a turkey.”10 ­There are, of course, other limits to prediction that cannot be neatly summed up by exposing the blind spots in induction.

Rules are made to be broken, and expectations, too. Our predictions are constantly frustrated b­ ecause the knowledge we need to augment induction is often lacking or unavailable. I might see a thousand white swans in ­England and conclude All swans are white. That same year, on a trip to Australia, I see a black swan—­ induction be damned. Much of what we think we know is actually tentative, awaiting further review, and it’s overreliance on induction that makes changes seem surprising. In large cities in the western United States like Seattle, d­ rivers typically slow or stop at a yellow light, instead of gunning it to get through.

As Taleb quips, it is impor­tant to know w how “not to become a turkey.”10 ­There are, of course, other limits to prediction that cannot be neatly summed up by exposing the blind spots in induction. Black swans are rare, a­ fter all, as are stock market crashes and major wars (and innovations). We can be forgiven for using induction to help illuminate what are opaque and largely unpredictable possibilities anyway, but not for attempts to replace our understanding with data and statistics alone. In some cases, like chaotic natu­ral systems (say, systems with turbulence) we now know that ­there are inherent limitations to predictability, using any known type of inferential methods.


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The Everything Store: Jeff Bezos and the Age of Amazon by Brad Stone

airport security, Amazon Mechanical Turk, Amazon Web Services, AOL-Time Warner, Apollo 11, bank run, Bear Stearns, Bernie Madoff, big-box store, Black Swan, book scanning, Brewster Kahle, buy and hold, call centre, centre right, Chuck Templeton: OpenTable:, Clayton Christensen, cloud computing, collapse of Lehman Brothers, crowdsourcing, cuban missile crisis, Danny Hillis, deal flow, Douglas Hofstadter, drop ship, Elon Musk, facts on the ground, fulfillment center, game design, housing crisis, invention of movable type, inventory management, James Dyson, Jeff Bezos, John Markoff, junk bonds, Kevin Kelly, Kiva Systems, Kodak vs Instagram, Larry Ellison, late fees, loose coupling, low skilled workers, Maui Hawaii, Menlo Park, Neal Stephenson, Network effects, new economy, off-the-grid, optical character recognition, PalmPilot, pets.com, Ponzi scheme, proprietary trading, quantitative hedge fund, reality distortion field, recommendation engine, Renaissance Technologies, RFID, Rodney Brooks, search inside the book, shareholder value, Silicon Valley, Silicon Valley startup, six sigma, skunkworks, Skype, SoftBank, statistical arbitrage, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, the long tail, Thomas L Friedman, Tony Hsieh, two-pizza team, Virgin Galactic, Whole Earth Catalog, why are manhole covers round?, zero-sum game

For a moment, I experienced the same sweaty surge of panic every Amazon employee over the past two decades has felt when confronted with an unanticipated question from the hyperintelligent boss. The narrative fallacy, Bezos explained, was a term coined by Nassim Nicholas Taleb in his 2007 book The Black Swan to describe how humans are biologically inclined to turn complex realities into soothing but oversimplified stories. Taleb argued that the limitations of the human brain resulted in our species’ tendency to squeeze unrelated facts and events into cause-and-effect equations and then convert them into easily understandable narratives. These stories, Taleb wrote, shield humanity from the true randomness of the world, the chaos of human experience, and, to some extent, the unnerving element of luck that plays into all successes and failures.

Data-Driven Marketing: The 15 Metrics Everyone in Marketing Should Know, by Mark Jeffery (2010). A guide to using data to measure everything from customer satisfaction to the effectiveness of marketing. Amazon employees must support all assertions with data, and if the data has a weakness, they must point it out or their colleagues will do it for them. The Black Swan: The Impact of the Highly Improbable, by Nassim Nicholas Taleb (2007). The scholar argues that people are wired to see patterns in chaos while remaining blind to unpredictable events, with massive consequences. Experimentation and empiricism trumps the easy and obvious narrative. Notes Prologue 1 Jeff Bezos, keynote address at Tepper School of Business graduation, Carnegie Mellon University, May 18, 2008.

There was no easy explanation for how certain products were invented, such as Amazon Web Services, its pioneering cloud business that so many other Internet companies now use to run their operations. “When a company comes up with an idea, it’s a messy process. There’s no aha moment,” Bezos said. Reducing Amazon’s history to a simple narrative, he worried, could give the impression of clarity rather than the real thing. In Taleb’s book—which, incidentally, all Amazon senior executives had to read—the author stated that the way to avoid the narrative fallacy was to favor experimentation and clinical knowledge over storytelling and memory. Perhaps a more practical solution, at least for the aspiring author, is to acknowledge its potential influence and then plunge ahead anyway.


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The Black Box Society: The Secret Algorithms That Control Money and Information by Frank Pasquale

Adam Curtis, Affordable Care Act / Obamacare, Alan Greenspan, algorithmic trading, Amazon Mechanical Turk, American Legislative Exchange Council, asset-backed security, Atul Gawande, bank run, barriers to entry, basic income, Bear Stearns, Berlin Wall, Bernie Madoff, Black Swan, bonus culture, Brian Krebs, business cycle, business logic, call centre, Capital in the Twenty-First Century by Thomas Piketty, Chelsea Manning, Chuck Templeton: OpenTable:, cloud computing, collateralized debt obligation, computerized markets, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crowdsourcing, cryptocurrency, data science, Debian, digital rights, don't be evil, drone strike, Edward Snowden, en.wikipedia.org, Evgeny Morozov, Fall of the Berlin Wall, Filter Bubble, financial engineering, financial innovation, financial thriller, fixed income, Flash crash, folksonomy, full employment, Gabriella Coleman, Goldman Sachs: Vampire Squid, Google Earth, Hernando de Soto, High speed trading, hiring and firing, housing crisis, Ian Bogost, informal economy, information asymmetry, information retrieval, information security, interest rate swap, Internet of things, invisible hand, Jaron Lanier, Jeff Bezos, job automation, John Bogle, Julian Assange, Kevin Kelly, Kevin Roose, knowledge worker, Kodak vs Instagram, kremlinology, late fees, London Interbank Offered Rate, London Whale, machine readable, Marc Andreessen, Mark Zuckerberg, Michael Milken, mobile money, moral hazard, new economy, Nicholas Carr, offshore financial centre, PageRank, pattern recognition, Philip Mirowski, precariat, profit maximization, profit motive, public intellectual, quantitative easing, race to the bottom, reality distortion field, recommendation engine, regulatory arbitrage, risk-adjusted returns, Satyajit Das, Savings and loan crisis, search engine result page, shareholder value, Silicon Valley, Snapchat, social intelligence, Spread Networks laid a new fibre optics cable between New York and Chicago, statistical arbitrage, statistical model, Steven Levy, technological solutionism, the scientific method, too big to fail, transaction costs, two-sided market, universal basic income, Upton Sinclair, value at risk, vertical integration, WikiLeaks, Yochai Benkler, zero-sum game

Bankers were adopting complexly structured finance that hid their risk taking from the last backdrop of restraint: the market.152 Obligations would remain on balance sheets for some purposes, and off them for others. Byzantine agreements obscured who would be left holding the bag when a “credit event,” triggering massive payments, occurred.153 Derivatives slipped through numerous regulatory nets.154 The iconoclastic investor Nassim Taleb came to prominence by calling the financial crisis a “black swan,” a freakish event both unpredicted and unpredictable.155 But as more details emerge, it becomes apparent that it was less an unpredictable outcome of an unforeseen confluence of events than it was the natural consequence of a black box fi nance system. Even conscientious buyers of what turned out to be “toxic assets” couldn’t understand their true nature.

Alireza Gharagozlou, “Unregulable: Why Derivatives May Never Be Regulated,” Brooklyn Journal of Corporate, Financial and Commercial Law 4 (2010): 269–295 (exploring “various methods of regulating fi nancial derivative contracts, including (a) regulation by judicially created case law, (b) regulation as gambling, (c) regulation as insurance, (d) regulation as securities, (e) regulation via a clearinghouse and (f ) oversight by a super fi nancial regulator”). 155. Nassim Nicholas Taleb, Black Swan (New York: Random House, 2007). 156. Nomi Prins, Other People’s Money: The Corporate Mugging of America (New York: New Press, 2004). Nomi Prins, It Takes a Pillage: Behind the Bailouts, Bonuses and Backroom Deals from Washington to Wall Street (Hoboken, NJ: Wiley, 2009). 157. For example, Yves Smith describes a structure that catalyzed $533 in funding for subprime mortgages for every dollar invested in it.

At their best, these works also tell us why such inquiry matters.2 But efforts like these are only as good as the information available. We cannot understand, or even investigate, a subject about which nothing is known. Amateur epistemologists have many names for this problem. “Unknown unknowns,” “black swans,” and “deep secrets” are popular catchphrases for our many areas of social blankness.3 There is even an emerging field of “agnotology” that studies the “structural production of ignorance, its diverse causes and conformations, whether brought about by neglect, forgetfulness, myopia, extinction, secrecy, or suppression.” 4 2 THE BLACK BOX SOCIETY Gaps in knowledge, putative and real, have powerful implications, as do the uses that are made of them.


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Tools of Titans: The Tactics, Routines, and Habits of Billionaires, Icons, and World-Class Performers by Timothy Ferriss

Abraham Maslow, Adam Curtis, Airbnb, Alexander Shulgin, Alvin Toffler, An Inconvenient Truth, artificial general intelligence, asset allocation, Atul Gawande, augmented reality, back-to-the-land, Ben Horowitz, Bernie Madoff, Bertrand Russell: In Praise of Idleness, Beryl Markham, billion-dollar mistake, Black Swan, Blue Bottle Coffee, Blue Ocean Strategy, blue-collar work, book value, Boris Johnson, Buckminster Fuller, business process, Cal Newport, call centre, caloric restriction, caloric restriction, Carl Icahn, Charles Lindbergh, Checklist Manifesto, cognitive bias, cognitive dissonance, Colonization of Mars, Columbine, commoditize, correlation does not imply causation, CRISPR, David Brooks, David Graeber, deal flow, digital rights, diversification, diversified portfolio, do what you love, Donald Trump, effective altruism, Elon Musk, fail fast, fake it until you make it, fault tolerance, fear of failure, Firefox, follow your passion, fulfillment center, future of work, Future Shock, Girl Boss, Google X / Alphabet X, growth hacking, Howard Zinn, Hugh Fearnley-Whittingstall, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, John Markoff, Kevin Kelly, Kickstarter, Lao Tzu, lateral thinking, life extension, lifelogging, Mahatma Gandhi, Marc Andreessen, Mark Zuckerberg, Mason jar, Menlo Park, microdosing, Mikhail Gorbachev, MITM: man-in-the-middle, Neal Stephenson, Nelson Mandela, Nicholas Carr, Nick Bostrom, off-the-grid, optical character recognition, PageRank, Paradox of Choice, passive income, pattern recognition, Paul Graham, peer-to-peer, Peter H. Diamandis: Planetary Resources, Peter Singer: altruism, Peter Thiel, phenotype, PIHKAL and TIHKAL, post scarcity, post-work, power law, premature optimization, private spaceflight, QWERTY keyboard, Ralph Waldo Emerson, Ray Kurzweil, recommendation engine, rent-seeking, Richard Feynman, risk tolerance, Ronald Reagan, Salesforce, selection bias, sharing economy, side project, Silicon Valley, skunkworks, Skype, Snapchat, Snow Crash, social graph, software as a service, software is eating the world, stem cell, Stephen Hawking, Steve Jobs, Stewart Brand, superintelligent machines, TED Talk, Tesla Model S, The future is already here, the long tail, The Wisdom of Crowds, Thomas L Friedman, traumatic brain injury, trolley problem, vertical integration, Wall-E, Washington Consensus, We are as Gods, Whole Earth Catalog, Y Combinator, zero-sum game

Phillips), The Hard Thing About Hard Things (Ben Horowitz), Zero to One (Peter Thiel), The Art of the Start 2.0 (Guy Kawasaki), the works of Nassim Nicholas Taleb Neistat, Casey: It’s Not How Good You Are, It’s How Good You Want to Be (Paul Arden), The Second World War (John Keegan), The Autobiography of Malcolm X (Malcolm X and Alex Haley) Nemer, Jason: The Prophet (Kahlil Gibran), Tao Te Ching (Lao Tzu) Norton, Edward: Wind, Sand and Stars (Antoine de Saint-Exupéry), Buddhism Without Beliefs (Stephen Batchelor), Shōgun (James Clavell), The Search for Modern China; The Death of Woman Wang (Jonathan Spence), “The Catastrophe of Success” (essay by Tennessee Williams), The Black Swan (Nassim Nicholas Taleb) Novak, B.J.: The Oxford Book of Aphorisms (John Gross), Daily Rituals: How Artists Work (Mason Currey), Easy Riders, Raging Bulls: How the Sex-Drugs-and-Rock ’N’ Roll Generation Saved Hollywood (Peter Biskind), The Big Book of New American Humor; The Big Book of Jewish Humor (William Novak and Moshe Waldoks) Ohanian, Alexis: Founders at Work: Stories of Startups’ Early Days (Jessica Livingston), Masters of Doom: How Two Guys Created an Empire and Transformed Pop Culture (David Kushner) Palmer, Amanda: Dropping Ashes on the Buddha: The Teachings of Zen Master Seung Sahn; Only Don’t Know: Selected Teaching Letters of Zen Master Seung Sahn (Seung Sahn), A Short History of Nearly Everything (Bill Bryson) Paul, Caroline: The Things They Carried (Tim O’Brien), The Dog Stars (Peter Heller) Polanco, Martin: The Journey Home (Radhanath Swami), Ibogaine Explained (Peter Frank), Tryptamine Palace: 5-MeO-DMT and the Sonoran Desert Toad (James Oroc) Poliquin, Charles: The ONE Thing (Gary Keller and Jay Papasan), 59 Seconds: Change Your Life in Under a Minute (Richard Wiseman), The Checklist Manifesto (Atul Gawande), Bad Science (Ben Goldacre), Life 101: Everything We Wish We Had Learned about Life in School—But Didn’t (Peter McWilliams) Popova, Maria: Still Writing (Dani Shapiro), On the Shortness of Life (Seneca), The Republic (Plato), On the Move: A Life (Oliver Sacks), The Journal of Henry David Thoreau, 1837–1861 (Henry David Thoreau), A Rap on Race (Margaret Mead and James Baldwin), On Science, Necessity and the Love of God: Essays (Simone Weil), Stumbling on Happiness (Daniel Gilbert), Desert Solitaire: A Season in the Wilderness (Edward Abbey), Gathering Moss (Robin Wall Kimmerer), The Essential Scratch & Sniff Guide to Becoming a Wine Expert (Richard Betts) Potts, Rolf: Leaves of Grass (Walt Whitman), Writing Tools: 50 Essential Strategies for Every Writer (Roy Peter Clark), To Show and to Tell: The Craft of Literary Nonfiction (Phillip Lopate), Screenplay: The Foundations of Screenwriting (Syd Field), Story (Robert McKee), Alien vs.

If the prospective financial loss drives you to even mild desperation or depression, you shouldn’t do it. You have started and/or managed successful businesses in the past. You limit angel investment funds to 10 to 15% or less of your liquid assets. I subscribe to the Nassim Taleb “barbell” school of investment, which I implement as 90% in conservative asset classes like cash-like equivalents and the remaining 10% in speculative investments that can capitalize on positive “black swans.” Even if the above criteria are met, people overestimate their risk tolerance. Even if you have only $100 to invest, this is important to explore. In 2007, I had one wealth manager ask me, “What is your risk tolerance?”

To do anything remotely interesting, you need to train yourself to handle—or even enjoy—criticism. I regularly and deliberately “embarrass” myself for superficial reasons, much like Cato. This is an example of “fear-rehearsing” (page 474). #8—“Living well is the best revenge.”—George Herbert During a tough period several years ago, Nassim Taleb of The Black Swan fame sent me the following aphorism, which was perfect timing and perfectly put: “Robustness is when you care more about the few who like your work than the multitude who hates it (artists); fragility is when you care more about the few who hate your work than the multitude who loves it (politicians).”


pages: 401 words: 93,256

Alchemy: The Dark Art and Curious Science of Creating Magic in Brands, Business, and Life by Rory Sutherland

"World Economic Forum" Davos, 3D printing, Alfred Russel Wallace, barriers to entry, basic income, behavioural economics, Black Swan, Brexit referendum, butterfly effect, California gold rush, call centre, Captain Sullenberger Hudson, Cass Sunstein, cognitive dissonance, confounding variable, Daniel Kahneman / Amos Tversky, Dava Sobel, delayed gratification, Donald Trump, double helix, Downton Abbey, driverless car, Easter island, Edward Jenner, Elon Musk, Firefox, Ford Model T, General Magic , George Akerlof, gig economy, Google Chrome, Google X / Alphabet X, Grace Hopper, Hyperloop, Ignaz Semmelweis: hand washing, IKEA effect, information asymmetry, it is difficult to get a man to understand something, when his salary depends on his not understanding it, James Dyson, John Harrison: Longitude, loss aversion, low cost airline, Mason jar, Murray Gell-Mann, nudge theory, Peter Thiel, placebo effect, race to the bottom, Richard Feynman, Richard Thaler, Rory Sutherland, shareholder value, Silicon Valley, social intelligence, Steve Jobs, supply-chain management, systems thinking, TED Talk, the map is not the territory, The Market for Lemons, The Wealth of Nations by Adam Smith, ultimatum game, universal basic income, Upton Sinclair, US Airways Flight 1549, Veblen good, work culture

A Pall Mall club in London is typically full of rich, right-wing people, yet everyone pays equal membership fees, even though they use the club in wildly different ways. Goldman Sachs, as the author and philosopher Nassim Nicholas Taleb points out, is surprisingly socialistic internally: people distribute their gains among a partnership. However, no one there proposes a profit share with JP Morgan; in one context people are happy to share and redistribute wealth, but in another, they definitely aren’t. Why is this? In his book Skin in the Game (2018), Taleb includes what might be the most interesting quotation on an individual’s politics I have ever read. Someone* explains how, depending on context, he has entirely different political preferences: ‘At the federal level I am a Libertarian.

The need to rely on data can also blind you to important facts that lie outside your model. It was surely relevant that Trump was filling sports halls wherever he campaigned, while Clinton was drawing sparse crowds. It’s important to remember that big data all comes from the same place – the past. A new campaigning style, a single rogue variable or a ‘black swan’ event can throw the most perfectly calibrated model into chaos. However, the losing sides in both these campaigns have never once considered that their reliance on logic might been the cause of their defeats, and the blame was pinned on anyone from ‘Russians’ to ‘Facebook’. Maybe they were blameworthy in part, but no one has spent enough time asking whether an overreliance on mathematical models of decision-making might be to blame for the fact that in each case the clear favourite blew it.

What’s interesting is that we adopted the behaviour many thousands of years before we knew the reasons for it. There is a good reason why evolution worked this way. Instincts are heritable, whereas reasons have to be taught; what is important is how you behave, not knowing why you do. As Nassim Nicholas Taleb remarks, ‘There is no such thing as a rational or irrational belief – there is only rational or irrational behaviour.’ And the best way for evolution to encourage or prevent a behaviour is to attach an emotion to it. Sometimes the emotion is not appropriate – for instance, there is no reason for Brits to be afraid of spiders, since there are no poisonous spiders in the UK – but it’s still there, just in case.


pages: 504 words: 126,835

The Innovation Illusion: How So Little Is Created by So Many Working So Hard by Fredrik Erixon, Bjorn Weigel

Airbnb, Alan Greenspan, Albert Einstein, American ideology, asset allocation, autonomous vehicles, barriers to entry, Basel III, Bernie Madoff, bitcoin, Black Swan, blockchain, Blue Ocean Strategy, BRICs, Burning Man, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Cass Sunstein, classic study, Clayton Christensen, Colonization of Mars, commoditize, commodity super cycle, corporate governance, corporate social responsibility, creative destruction, crony capitalism, dark matter, David Graeber, David Ricardo: comparative advantage, discounted cash flows, distributed ledger, Donald Trump, Dr. Strangelove, driverless car, Elon Musk, Erik Brynjolfsson, Fairchild Semiconductor, fear of failure, financial engineering, first square of the chessboard / second half of the chessboard, Francis Fukuyama: the end of history, general purpose technology, George Gilder, global supply chain, global value chain, Google Glasses, Google X / Alphabet X, Gordon Gekko, Greenspan put, Herman Kahn, high net worth, hiring and firing, hockey-stick growth, Hyman Minsky, income inequality, income per capita, index fund, industrial robot, Internet of things, Jeff Bezos, job automation, job satisfaction, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Maynard Keynes: technological unemployment, joint-stock company, Joseph Schumpeter, Just-in-time delivery, Kevin Kelly, knowledge economy, laissez-faire capitalism, low interest rates, Lyft, manufacturing employment, Mark Zuckerberg, market design, Martin Wolf, mass affluent, means of production, middle-income trap, Mont Pelerin Society, Network effects, new economy, offshore financial centre, pensions crisis, Peter Thiel, Potemkin village, precautionary principle, price mechanism, principal–agent problem, Productivity paradox, QWERTY keyboard, RAND corporation, Ray Kurzweil, rent-seeking, risk tolerance, risk/return, Robert Gordon, Robert Solow, Ronald Coase, Ronald Reagan, savings glut, Second Machine Age, secular stagnation, Silicon Valley, Silicon Valley startup, Skype, sovereign wealth fund, Steve Ballmer, Steve Jobs, Steve Wozniak, subprime mortgage crisis, technological determinism, technological singularity, TED Talk, telemarketer, The Chicago School, The Future of Employment, The Nature of the Firm, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, total factor productivity, transaction costs, transportation-network company, tulip mania, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, University of East Anglia, unpaid internship, Vanguard fund, vertical integration, Yogi Berra

In their view, it is technology, not the economy, that fails. The idea of the planning machine connects with old thinking rooted in Descartes’ and Francis Bacon’s scientific civilization, with an unobstructed path from science to innovation, or from technology to the economy. Nassim Nicholas Taleb, the New York University professor and author of The Black Swan, calls it the “Soviet–Harvard illusion”: the superiority, or primacy, of scientific knowledge and the religious belief in rationalism as a way to understand and change society.19 Technological shifts are embraced for their revolutionary character or their unyielding ability to crush existing social and economic orders in their march through society.

(i)n17 savings aggregate (i) corporate (cash hoarding) (i), (ii), (iii), (iv), (v) retirement (i), (ii), (iii), (iv), (v), (vi), (vii) Schmidt, Eric (i) Schumpeter, Joseph (i), (ii), (iii), (iv) Schumpeterian innovation (i), (ii) “scientific civilization” thinking, and planning (i) scientific research (i) see also R&D; research Scrooge character (i) “second half of the chessboard” (Ray Kurzweil) (i) Second Machine Age, The (Brynjolfsson and McAfee) (i), (ii) Second World countries, and globalization (i) Seinfeld (TV series) Art Vandelay and “importer-exporter” conversation (i), (ii) “Art Vandelay logistics operation” (i) self-driving vehicles see driverless vehicles self-regulation (i) Sellers, Peter (i) Servan-Schreiber, Jean-Jacques, Le Défi américain (The American Challenge) (i) services and globalization (i) and market contestability (i), (ii) and second unbundling of production (i) see also online services “servicification” (or “servitization”) (i), (ii) SetPoint nerve stimulator (i) shale gas, and regulation in Europe (i) shareholders (i), (ii), (iii), (iv), (v), (vi), (vii) shares buybacks (i), (ii), (iii), (iv) share/stock structures (i) see also stock markets Shelley, Percy Bysshe, Prometheus Unbound (i) shipping containers (i) short-termism (i) Sidecar (i) SIFIs (systemically important financial institutions) (i) Silicon Valley (i), (ii), (iii) silo curse (i) Silvia, John (i) Simons, Bright (i) Simphal, Thibaud (i) Sinclair, Clive (i) Sinn, Hans-Werner, “bazaar economy” (i) size see corporate size skill deficiencies, and productivity (i) Skype (i), (ii) Slyngstad, Yngve (i) smartphones (i), (ii), (iii), (iv) Smith, Adam economy of specialization (i) labor and wealth (i) “man of system” (i) The Wealth of Nations (i), (ii) Smiths, The (rock band), “hang the DJ” lyric (i) social democratic vision (i) social regulation (i), (ii) socialism and bureaucracy (i) and community-generated content (i) corporate socialism (i), (ii) and Cybersyn project (i) and death of capitalism utopia (i) and labor vs. work (i) market socialism (i) and open source technology (i) socialist planning (i) and Swedish hybrid economy (i) Söderberg, Hjalmar (i) software technology, and regulation (i) Sombart, Werner (i) Sony (i), (ii), (iii), (iv), (v) sourdough production, history of (i) South Africa, taxi services and regulation (i) South Korea “Asian Tiger” (i) R&D spending (i) Sovereign Wealth Fund Institute (i) sovereign wealth funds (SWFs) (i), (ii), (iii) “Soviet–Harvard illusion” (Nassim Nicholas Taleb) (i) space flights, commercial (i) SpaceX (i) Spain biofuels regulation (i) and diffusion of innovations (i) and globalization (i) left-wing populism (i) lesser dependence on larger enterprises (i) pensions (i) public debt (i) taxi services and regulation (i) specialization and corporate control (i) and creative destruction (i) and deregulation (i) and firm boundaries (i), (ii), (iii), (iv), (v) and globalization (i), (ii), (iii), (iv), (v), (vi), (vii) and innovation (i), (ii), (iii), (iv) and organization (i) and sunk costs (i), (ii) vertical (i), (ii) speech codes, in universities (i) staff turnover rates, and economic dynamism (i) Stanford University (i), (ii) Star Trek (TV series) (i) start-ups (i), (ii), (iii), (iv), (v) Startup Genome Report (i) statistics see recorded data (national accounts) Statoil (i) Stein, Gertrude, “there is no there there” quote (i) Stern, Ariel Dora (i) stock markets changing role of (i) and corporate politics (i) post-financial crisis growth (i) and sovereign wealth funds (i) see also shareholders; shares stockholding periods (i), (ii), (iii) strategic management (i) strategic planning (i) strategy, and managerialism (i) Stratos pacemaker (i) subprime mortgage crisis (US) (i) see also financial crisis (2007) subsidies domestic companies (i) US firms (i) sunk costs (i), (ii), (iii), (iv) Sunstein, Cass (i) supply chains fragmentation of (i), (ii), (iii), (iv), (v), (vi), (vii) German-Central European supply chain (i), (ii) globalization of (i), (ii) and market concentration (i) marketization of (i) and multinationals (i) and Nokia (i) outsourcing of (i) and private standards (i) see also value chains Sweden corporate renewal levels (i) economic situation: 1970s–1980s (i); globalization and post-financial crisis (i) productivity and incomes (i) services and globalization (i) sourdough hotel (Stockholm) (i) state telecommunication monopoly and mobile technology (i) SWFs (sovereign wealth funds) (i), (ii), (iii) SWOT analyses (i) systemically important financial institutions (SIFIs) (i) Tabarrok, Alex (i) tablets (i), (ii) Taibbi, Matt, “Why Isn’t Wall Street in Jail?” (i) Taleb, Nassim Nicholas, “Soviet–Harvard illusion” (The Black Swan) (i) tax havens (i) taxes and debt vs. equity financing (i), (ii) and labor (i) and policy uncertainty (i) in Sweden (i) taxi services and driverless cars debate (i) and regulation (i) tech entrepreneurs (i) tech incubators (i) technofeudal society (i) technological platforms, and regulation (i) technological singularity (i) technological unemployment (i), (ii) technology and capitalism (i) dystopian visions of (i) and economy (i), (ii), (iii) and employment (i) and French dirigisme (i) and innovation success (i), (ii), (iii), (iv) and “scientific civilization” thinking (i) technology angst vs. technology frustration (i) technology blitz theory (i), (ii), (iii), (iv) and vertical specialization (i) see also artificial intelligence; automation; diffusion; innovation; New Machine Age thesis; robotics/robots technostructure (i), (ii), (iii), (iv) telecommunications and deregulation (i) and globalization (i) and investment (i) see also Ericsson telephone (i), (ii) see also mobile phones/technology; smartphones Teles, Steven (i) Teller, Astro (i) 1066 and All That (Sellar and Yeatman) (i) Tesla (i) Texas, Special/Permanent School Fund (i) TFP (total factor productivity) growth (i), (ii), (iii) Thiel, Peter (i), (ii) Thomson, George (i) Tiberius (i) Time magazine, “The Committee to Save the World” (i) TNT, attempted acquisition of by UPS (i) total factor productivity (TFP) growth (i), (ii), (iii) Toynbee, Arnold (i), (ii) trade interfirm vs. intrafirm trade (i) see also global trade; mercantilism; protectionism transaction costs (i), (ii), (iii), (iv), (v), (vi) transmission costs (i), (ii), (iii) transparency Linaburg Maduell Transparency Index (LMTI) (i) and regulation (i), (ii) and sovereign wealth funds (i), (ii) Transparency International (i) “triple helix” models (i) “triple revolution” (i) trucking industry (US), shortages of drivers (i) Trump, Donald (i), (ii) Tufts Center for the Study of Drug Development (i), (ii) Tullock, Gordon (i) Twitter, and Nobel Peace Prize (i) Uber (i), (ii), (iii) unbundling of production first (i) second (i), (ii), (iii), (iv) uncertainty and compliance officers (i), (ii) and entrepreneurship (i) and financial regulation (i) and globalist worldview (i), (ii) market uncertainty (i), (ii) policy uncertainty (i), (ii) and probabilistic approach (i), (ii) and risk (i), (ii) and strategy (i) see also predictability; regulatory complexity/uncertainty; volatility unemployment and decoupling (productivity/wages) thesis (i) and Great Recession (i) and New Machine Age hype (i) and productivity (i) technological unemployment (i), (ii) see also labor unicorns (firms) (i) United Kingdom (UK) “boom and bust” and Gordon Brown (i) business investment: declining trend (i); as a proportion of GDP (i) corporate net lending (i), (ii) corporate profit margins (1948–2014) (i), (ii) dependence on larger enterprises (i) EU Leave campaign and older generation (i) exports to China (i) financialization of real economy (i) and globalization (i), (ii), (iii) income inequality and generations (i) “Independent Review of UK Economic Statistics” (Charles Bean) (i) London Stock Exchange and sovereign wealth funds (i) managerialism (i) Middle Ages economy (i) pension deficits (i) pensioners vs. working-age households incomes (i) productivity and incomes (i) productivity puzzle (i) R&D spending (i) retirement savings (i) United States (US) academia and speech codes (i) American Financial Stability Oversight Council (i) banks: and compliance officers (i); and financial regulations (i) Blue Ribbon Commission (i) Burning Man festival (Nevada) (i) capital expenditure (capex) (i)n39 car industry: driverless cars (i); and environment-related regulations (i); and lean production (i) Code of Federal Regulations (i) Consumer Protection Act (i) corporate cash hoarding (i) corporate net lending (i), (ii) corporate profit margins (1948–2014) (i), (ii) corporate renewal levels (i) corporate retained earnings figures (i) corporations’ decline (1980s) (i) debt vs. equity (i) diffusion of innovations (i) dockers and containerization (i) Dodd–Frank Act (i), (ii), (iii), (iv) Energy Policy and Conservation Act (EPCA) (i) Federal Register (i) Federal Reserve (i) financial governance (1990s) (i) financialization of real economy (i) firm entry-and-exit rates (i), (ii), (iii) Food and Drug Administration (FDA) (i), (ii), (iii) GDP figures (i), (ii) and globalization (i), (ii), (iii) high-tech sector (i) Inc 500 ranking (i) incomes: and benefits (i); inequality and generations (i); inequality and productivity (i); and productivity (i), (ii), (iii), (iv), (v) information and communications technology: hardware investment as share of GDP (i), (ii); intensity and productivity (i); sector (i), (ii) investment: business investment declining trend (i), (ii); corporate borrowing and low investment levels (i); corporate investment and shareholders (i), (ii); institutional investors (i); private investment (i) labor: ATMs and teller jobs (i); farming occupation statistics (i); job creation and destruction trends (i), (ii), (iii); labor market flexibility, low rates of (i); occupational licenses (i), (ii); staff turnover rates (i); truck drivers, shortages of (i) market concentration (1997–2012) (i), (ii) Memphis International Airport and FedEx hub (i) mergers and acquisitions (i) New York Stock Exchange (i), (ii), (iii), (iv), (v) North American Free Trade Agreement (i) Organization Man (i) pessimism and capitalist decline (i) policy uncertainty (i), (ii) productivity: downward trend (i), (ii), (iii); via foreign operations (i)n46; and ICT intensity (i); and income inequality (i); and incomes (i), (ii), (iii), (iv), (v); total factor productivity (TFP) growth (i), (ii)n11; and un/employment (i) profit margins (i) public debt (i) public pensions (i) R&D spending (i), (ii), (iii) regulation/deregulation: air cargo services deregulation (i); car industry and environment-related regulations (i); Code of Federal Regulations (i); compliance officers and Dodd–Frank rules (i); drone aircraft rules (i); green building codes (i); index of regulatory freedom (i), (ii); index of regulatory trade barriers (i), (ii); medical devices (i); taxi services (i), (ii) retirement savings (i) robots, fear of (i) Silicon Valley (i), (ii), (iii) start-ups and entrepreneurship (i), (ii) stock market crash and modern portfolio theory (i) subprime mortgage crisis (i) subsidies to firms (i) Texas Special/Permanent School Fund (i) trade: and big business (i); index of regulatory trade barriers (i), (ii) Wall Street (i), (ii), (iii), (iv) universities, and erosion of dissent (i) University of Chicago (i) University of Oxford, Future of Humanity Institute (i) UPS, attempted acquisition of TNT (i) urbanization, and diffusion of innovations (i) value vs. numbers (i) value innovation (i) value chains fragmentation of (i), (ii), (iii) and German corporations (i) globalization of (i), (ii) and market concentration (i) marketization of (i) and outsourcing of supply chains (i) “slicing up” of (i), (ii) and specialization (i), (ii) see also supply chains Van Reenen, John (i) Vanguard Group (i) Vernon, John A.

At the sixty-fourth square, the pile of rise equaled the size of Mount Everest. 10.Nietzsche, Thus Spoke Zarathustra, 41. 11.Levy, Love and Sex with Robots. 12.Holley, “Apple Co-founder on Artificial Intelligence.” 13.Romm, “Americans Are More Afraid of Robots Than Death.” 14.Smith and Anderson, “AI, Robotics, and the Future of Jobs.” 15.This section on Stafford Beer and Project Cybersyn builds on Medina, Cybernetic Revolutionaries. 16.Medina, Cybernetic Revolutionaries, 25. 17.Morozov, “The Planning Machine.” 18.Huebner, “A Possible Declining Trend for Worldwide Innovation,” 985. 19.Taleb, Antifragile. 20.Kelly, “The New Socialism.” 21.Mason, Postcapitalism. 22.The Economist, “Caught in the Net.” 23.Gilder, Microcosm. 24.Carswell, The End of Politics and the Birth of iDemocracy. 25.Fukuyama, The End of History, 98–108. 26.Kaminsky, “Iran’s Twitter Revolution.” 27.Nixon, “Lack of Innovation Leaves EU Trailing.” 28.OECD, “Territorial Review: Stockholm, Sweden 2006.” 29.Legrain, European Spring, 367. 30.Gordon, “Secular Stagnation.” 31.Gage, “The Venture Capital Secret.” 32.Marmer et al., “Startup Genome Report Extra,” 10. 33.Schumpeter’s vision of capitalism is explained in Schumpeter, The Theory of Economic Development and, in a different way, in Schumpeter, Capitalism, Socialism, and Democracy. 34.For a discerning analysis of the similarities between Marx and Schumpeter, see Elliott, “Marx and Schumpeter on Capitalism’s Creative Destruction.” 35.Schumpeter, Capitalism, Socialism, and Democracy (1992), 61. 36.To avoid repetition in the book we will use terms like contestable innovation, big innovation, radical innovation, or game-changing innovation to describe the same phenomenon: innovation that contests markets. 37.Mokyr, “Long-Term Economic Growth and the History of Technology,” 4. 38.Broadberry et al., British Economic Growth. 39.Clark, A Farewell to Alms, 1. 40.Phelps, Mass Flourishing. 41.Our version of modern capitalism and its birth draws on several scholars such as Gregory Clark, David Landes, Joel Mokyr, and Edmund Phelps.


pages: 624 words: 127,987

The Personal MBA: A World-Class Business Education in a Single Volume by Josh Kaufman

Albert Einstein, Alvin Toffler, Atul Gawande, Black Swan, Blue Ocean Strategy, business cycle, business process, buy low sell high, capital asset pricing model, Checklist Manifesto, cognitive bias, correlation does not imply causation, Credit Default Swap, Daniel Kahneman / Amos Tversky, David Heinemeier Hansson, David Ricardo: comparative advantage, Dean Kamen, delayed gratification, discounted cash flows, Donald Knuth, double entry bookkeeping, Douglas Hofstadter, Dunning–Kruger effect, en.wikipedia.org, Frederick Winslow Taylor, George Santayana, Gödel, Escher, Bach, high net worth, hindsight bias, index card, inventory management, iterative process, job satisfaction, Johann Wolfgang von Goethe, Kaizen: continuous improvement, Kevin Kelly, Kickstarter, Lao Tzu, lateral thinking, loose coupling, loss aversion, Marc Andreessen, market bubble, Network effects, Parkinson's law, Paul Buchheit, Paul Graham, place-making, premature optimization, Ralph Waldo Emerson, rent control, scientific management, side project, statistical model, stealth mode startup, Steve Jobs, Steve Wozniak, subscription business, systems thinking, telemarketer, the scientific method, time value of money, Toyota Production System, tulip mania, Upton Sinclair, Vilfredo Pareto, Walter Mischel, Y Combinator, Yogi Berra

You can’t reliably predict the future based on past events in the face of Uncertainty. Unexpected or random events can occur suddenly, which can have major impacts on your goals and plans. In The Black Swan, Nassim Nicholas Taleb, a former hedge fund manager, describes the perils of Uncertainty. No matter how stable or predictable things seem, unpredictable “black swan events” can change everything in an instant. The term “black swan” was a common expression in sixteenth-century London for something that was impossible or didn’t exist—everyone knew that all swans were white. The problem with the term is what eighteenth-century philosopher David Hume called the “problem of induction”: until you see every swan that exists, you can never assume the statement “all swans are white” is true.

The problem with the term is what eighteenth-century philosopher David Hume called the “problem of induction”: until you see every swan that exists, you can never assume the statement “all swans are white” is true. All it takes is one black swan to completely invalidate the hypothesis, which happened when black swans were documented in Australia in 1697 by Dutch sea captain Willem de Vlamingh. The moment before they happen, the probability of “black swan” events occurring is essentially zero. In the wake of a black swan event, the probability of its occurring is a moot point: the event changes the Environment in which the system operates, sometimes drastically changing Selection Tests without warning. You can’t know in advance if (or which) black swan events will occur: all you can do is be flexible, prepared, and Resilient (discussed later) enough to react appropriately if and when they do.

Psychologically, it’s very difficult to internalize that some things are random: there’s no rhyme or reason to many of the things that happen in the world. Because of our natural Pattern Matching abilities, we tend to see patterns where none exist and tend to attribute random Changes to skill if the Changes are good or misfortune if they’re bad. As a result, we’re Fooled by Randomness—the title of Nassim Nicholas Taleb’s first book. You will never develop your business to the point that everything is perfect and unchanging. Many business owners and managers share an unexamined belief that by moving a business from “good to great,” it’ll be “built to last,” continuing to outperform competitors for decades to come.


pages: 161 words: 44,488

The Business Blockchain: Promise, Practice, and Application of the Next Internet Technology by William Mougayar

Airbnb, airport security, Albert Einstein, altcoin, Amazon Web Services, bitcoin, Black Swan, blockchain, business logic, business process, centralized clearinghouse, Clayton Christensen, cloud computing, cryptocurrency, decentralized internet, disintermediation, distributed ledger, Edward Snowden, en.wikipedia.org, Ethereum, ethereum blockchain, fault tolerance, fiat currency, fixed income, Ford Model T, global value chain, Innovator's Dilemma, Internet of things, Kevin Kelly, Kickstarter, market clearing, Network effects, new economy, peer-to-peer, peer-to-peer lending, prediction markets, pull request, QR code, ride hailing / ride sharing, Satoshi Nakamoto, sharing economy, smart contracts, social web, software as a service, too big to fail, Turing complete, Vitalik Buterin, web application, Yochai Benkler

The Dodd-Frank’s3 mandatory central counterparty clearing provisions were a heavy-handed policy that actually amplified systemic risk, instead of reducing it. As a result, central counterparty clearinghouses have become a new class of “too big to fail” institutions, whereas, ironically, they were previously more widely distributed. In a 2012 New York Times article titled “Stabilization Will not Save Us,” Nassim Nicholas Taleb, author of Antifragile and The Black Swan, opined: “In decentralized systems, problems can be solved early and when they are small.”4 Indeed, not only was the Web hijacked with too many central choke points, regulators supposedly continue to centralize controls in order to lower risk, whereas the opposite should be done.

Hayek, http://www.kysq.org/docs/Hayek_45.pdf, 1945. 2. Web We Want, https://webwewant.org. 3. Dodd–Frank Wall Street Reform and Consumer Protection Act, Wikipedia, https://en.wikipedia.org/wiki/Dodd%E2%80%93Frank_Wall_Street_Reform_and_Consumer_Protection_Act. 4. “Stablization Will not Save Us,” Nassim Nicholas Taleb, New York Times, http://www.nytimes.com/2012/12/24/opinion/stabilization-wont-save-us.html?_r=0. 5. Michael Spence, Wikipedia, https://en.wikipedia.org/wiki/Michael_Spence. 6. Carlota Perez, Technological Revolutions and Financial Capital: The Dynamics of Bubbles and Golden Ages, Elgar Online, 2002.

Bush, President global Google governance government Grid Singularity H healthcare I identity infrastructure innovation intermediary Internet IPFS xii, Ira Magaziner IT J James Champy Javascript J. Christopher Giancarlo John Hagel Juan Llanos xiv K KYC L land registry law La’ZooZ M marketplace marriage Michael Hammer Michael Spence Microsoft microtransactions money multisignature N narrative Nassim Nicholas Taleb Nicholas G. Carr Nick Dodson Nick Szabo O Open Assets open source oracle smart oracle Otonomos over-the-counter ownership P PayPal Peer-to-Peer P2P policy makers post-trade privacy private blockchain productivity programming 10, proof in a service proof of – authority existence ownership provenance receipt stake work R R3 CEV reengineering regulation repurchase market reputation Ricardian contracts Ripple risk Robert Sams S Satoshi Nakamoto security settlement smart contract smart property society standard startups supply chain swaps SWIFT T Tierion Tim Berners-Lee token TPS transactions TransActive Grid trust U Ukraine unbundling V VISA Vitalik Buterin W wallets warehouse receipts web3 work World Wide Web ADDITIONAL RESOURCES Executive Presentations by William Mougayar, Explaining the Impact of the Blockchain and Decentralization As a trained professional consultant and analyst, William starts by understanding the context and unique requirements of each audience he addresses.


pages: 578 words: 168,350

Scale: The Universal Laws of Growth, Innovation, Sustainability, and the Pace of Life in Organisms, Cities, Economies, and Companies by Geoffrey West

"World Economic Forum" Davos, Alfred Russel Wallace, Anthropocene, Anton Chekhov, Benoit Mandelbrot, Black Swan, British Empire, butterfly effect, caloric restriction, caloric restriction, carbon footprint, Cesare Marchetti: Marchetti’s constant, clean water, coastline paradox / Richardson effect, complexity theory, computer age, conceptual framework, continuous integration, corporate social responsibility, correlation does not imply causation, cotton gin, creative destruction, dark matter, Deng Xiaoping, double helix, driverless car, Dunbar number, Edward Glaeser, endogenous growth, Ernest Rutherford, first square of the chessboard, first square of the chessboard / second half of the chessboard, Frank Gehry, Geoffrey West, Santa Fe Institute, Great Leap Forward, Guggenheim Bilbao, housing crisis, Index librorum prohibitorum, invention of agriculture, invention of the telephone, Isaac Newton, Jane Jacobs, Jeff Bezos, Johann Wolfgang von Goethe, John von Neumann, Kenneth Arrow, laissez-faire capitalism, Large Hadron Collider, Larry Ellison, Lewis Mumford, life extension, Mahatma Gandhi, mandelbrot fractal, Marc Benioff, Marchetti’s constant, Masdar, megacity, Murano, Venice glass, Murray Gell-Mann, New Urbanism, Oklahoma City bombing, Peter Thiel, power law, profit motive, publish or perish, Ray Kurzweil, Richard Feynman, Richard Florida, Salesforce, seminal paper, Silicon Valley, smart cities, Stephen Hawking, Steve Jobs, Stewart Brand, Suez canal 1869, systematic bias, systems thinking, technological singularity, The Coming Technological Singularity, The Death and Life of Great American Cities, the scientific method, the strength of weak ties, time dilation, too big to fail, transaction costs, urban planning, urban renewal, Vernor Vinge, Vilfredo Pareto, Von Neumann architecture, Whole Earth Catalog, Whole Earth Review, wikimedia commons, working poor

Traditional economic theory relies heavily on the economy remaining in an approximately equilibrium state. The serious challenge is to be able to predict outlying events, major transitions, critical points, and devastating economic hurricanes and tornadoes where their record has mostly been pretty dismal. Nassim Taleb, author of the best-selling, highly influential book The Black Swan, has been particularly harsh on economists despite, or maybe because of, having been trained in business and finance.5 He has held positions at several distinguished universities including New York University and Oxford and has focused on the importance of coming to terms with outlying events and developing a deeper understanding of risk.

See, for instance, J. H. Miller and S. E. Page, Complex Adaptive Systems: An Introduction to Computational Models of Social Life (Princeton, NJ: Princeton University Press, 2007). 4. J. D. Farmer and D. Foley, “The Economy Needs Agent-Based Modeling,” Nature 460 (2009): 685–86. 5. N. N. Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 6. M.I.G. Daepp, et al., “The Mortality of Companies,” Journal of the Royal Society Interface, 12:20150120. 7. E. L. Kaplan and P. Meier, “Nonparametric Estimation from Incomplete Observations,” Journal of American Statistical Association 53 (1958): 457–81; R.

., 179 bacteria, 1, 79 metabolic rate of, 93, 94, 96 bacterial colonies, 220–22, 290–91, 291 Bank of Korea, 406 bankruptcies, 33, 396 survivorship curves, 396–97, 398 Barber, Benjamin, 262 Bartholomew, John, 330 basal metabolic rate, 18–19, 90–93, 160 Batty, Michael, 291, 294–95 Bavinger House, 259 beam experiment, 42 Beckham, David, 63 bell curve, 56, 314 Bergman, Ingmar, 178, 179–80 Bettencourt, Luis, 274–75, 341, 356, 364 Big Bang, 16, 198, 339, 429 big data, 57, 270, 325, 338, 439–48 Big Data Institute (BDI), 442–43 Big Picture, 1–33 cities and global sustainability, 28–32 companies and businesses, 32–33 energy, metabolism, and entropy, 12–15 exponentially expanding socioeconomic urbanized world, 8–10 growth from cells to whales, 25–28 introduction, overview, and summary, 1–8 matter of life and death, 10–12 scaling and complexity, 19–25 scaling and nonlinear behavior, 15–19 big-picture theory of cities, 6, 269–71, 325–26, 338 biological metabolic rate, 13, 373 biological networks, 103–5, 104, 111–18, 153–54, 284–85 biological time, 327 biology, 7, 10, 11, 13 mathematics and, 85–86, 87 physics and, 83–84, 105–11 biomechanical constraints, 122, 158–63 biophysics, 83–84 birth control, 227, 229 Black Swan, The (Taleb), 383 blood flow, 74, 118–20, 124–26, 128–29, 155 blood pressure, 51, 89, 125–26, 162 blue whales, 1, 18, 91, 119, 158, 159–60, 234 body functions, decline by age, 195, 197, 201, 202 body mass, 18–19 life spans scale, 195–96 metabolic rate of animals, 2, 2n, 3, 13, 18–19, 25–26, 91–92, 285–86 body-mass index (BMI), 55–56, 57–59 body temperature, 51, 173–78 extending life span and, 203–4 body weight and drug dosages, 53–55 Boltzmann, Ludwig, 109 Bombay, growth curve, 375 border paradox, 135, 136–40, 138, 152 Boston, 261, 278 movement in, 348–49, 349–50, 353–54 Boulding, Kenneth, 229 bounded growth, 31, 173, 391 Bragg, Lawrence, 437 Bragg, William, 437 brain matter, 93, 94, 96, 104 brain size and social groups, 308–9 branching, 151–52, 154, 155, 157 area-preserving, 120–22, 154, 157 branching ratio, 306–7 Brand, Stewart, 211–12 Brasilia, 257–58, 267, 268 Brenner, Sydney, 111, 443 bridges, 60–62, 298–300 British Classical Association, 86 British Meteorological Office, 132 broccoli, 126–27, 127 Brown, James, 105–7, 110 Brown, Jim, 174, 386 Brownsville, Texas, 358 Brunel, Isambard Kingdom, 63–68, 65, 70–71, 86, 177 Brunel, Marc, 64 Bryson, Bill, 266 budget, U.S., 233–34 Burundi, 9 business diversity, 363–71 business ecosystem, 249–50 businesses.


pages: 385 words: 101,761

Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire by Bruce Nussbaum

"World Economic Forum" Davos, 3D printing, Airbnb, Albert Einstein, Berlin Wall, Black Swan, Chuck Templeton: OpenTable:, clean water, collapse of Lehman Brothers, creative destruction, Credit Default Swap, crony capitalism, crowdsourcing, Danny Hillis, declining real wages, demographic dividend, disruptive innovation, Elon Musk, en.wikipedia.org, Eugene Fama: efficient market hypothesis, fail fast, Fall of the Berlin Wall, follow your passion, game design, gamification, gentrification, housing crisis, Hyman Minsky, industrial robot, invisible hand, James Dyson, Jane Jacobs, Jeff Bezos, jimmy wales, John Gruber, John Markoff, Joseph Schumpeter, Kevin Roose, Kickstarter, Larry Ellison, lone genius, longitudinal study, manufacturing employment, Marc Andreessen, Mark Zuckerberg, Martin Wolf, Max Levchin, Minsky moment, new economy, Paul Graham, Peter Thiel, QR code, race to the bottom, reality distortion field, reshoring, Richard Florida, Ronald Reagan, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley ideology, Silicon Valley startup, SimCity, six sigma, Skype, SoftBank, Steve Ballmer, Steve Jobs, Steve Wozniak, supply-chain management, Tesla Model S, The Chicago School, The Design of Experiments, the High Line, The Myth of the Rational Market, thinkpad, TikTok, Tim Cook: Apple, too big to fail, tulip mania, Tyler Cowen, We are the 99%, Y Combinator, young professional, Zipcar

University of Chicago, Journal of Applied Corporate Finance, vol. 21, no. 4, 2009; Siegel, “Efficient Market Theory and the Crisis”; Roger Lowenstein, “Book Review: The Myth of the Rational Market by Justin Fox,” Washington Post, June 7, 2009, accessed September 13, 2012, http://www.washingtonpost.com/wp-dyn/ content/article/2009/06/05/AR2009060502053.html. 228 “black swans”: Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007). 228 By excluding uncertainty: Frank H. Knight, Risk, Uncertainty and Profit (New York: Sentry Press, 1921). 229 In the 1960s and 1970s, as EMT: John Cassidy, “The Minsky Moment,” New Yorker, February 4, 2008, accessed September 13, 2012, http://www.newyorker.com/talk/comment/2008/ 02/04/080204taco_talk_cassidy. 229 Charles Kindleberger’s: Charles P.

Measurement: only what can be measured should be included in the model. Of course, what was missing from the efficient market theory was as important as what was included: uncertainty. Because the theory constituted extreme and unpredictable occurrences of the kind economist Nassim Nicholas Taleb called “black swans” in his 2007 book of that name, the Chicago economists viewed uncertainty as an “exogenous” variable. By excluding uncertainty and focusing on measurable risk (it was Chicago economist Frank Knight who introduced the distinction between risk and uncertainty), the efficient market theory model of economics assumed and reinforced a culture of control.

But even if you’ve yet to amass experience in a particular field, you can still improve your chances of spotting the surprises you may not be expecting. For birders, it can mean going to strange and sometimes unsavory places. When I was in Singapore for a design conference, I went birding at a municipal waste treatment facility and found a number of birds—including one black swan. It was a rarity in Singapore and a good find. I was surprised, but not shocked. I was, after all, looking for what was not supposed to be there. Just as good detectives are trained to hear the dog that did not bark—so too are good scientists trained to look, and listen, for what’s not there. In 2012, Jeremy Feinberg, a Rutgers doctoral candidate, was doing fieldwork in the marshes and ponds surrounding New York City when he noticed something strange.


pages: 292 words: 85,151

Exponential Organizations: Why New Organizations Are Ten Times Better, Faster, and Cheaper Than Yours (And What to Do About It) by Salim Ismail, Yuri van Geest

23andMe, 3D printing, Airbnb, Amazon Mechanical Turk, Amazon Web Services, anti-fragile, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, behavioural economics, Ben Horowitz, bike sharing, bioinformatics, bitcoin, Black Swan, blockchain, Blue Ocean Strategy, book value, Burning Man, business intelligence, business process, call centre, chief data officer, Chris Wanstrath, circular economy, Clayton Christensen, clean water, cloud computing, cognitive bias, collaborative consumption, collaborative economy, commoditize, corporate social responsibility, cross-subsidies, crowdsourcing, cryptocurrency, dark matter, data science, Dean Kamen, deep learning, DeepMind, dematerialisation, discounted cash flows, disruptive innovation, distributed ledger, driverless car, Edward Snowden, Elon Musk, en.wikipedia.org, Ethereum, ethereum blockchain, fail fast, game design, gamification, Google Glasses, Google Hangouts, Google X / Alphabet X, gravity well, hiring and firing, holacracy, Hyperloop, industrial robot, Innovator's Dilemma, intangible asset, Internet of things, Iridium satellite, Isaac Newton, Jeff Bezos, Joi Ito, Kevin Kelly, Kickstarter, knowledge worker, Kodak vs Instagram, Law of Accelerating Returns, Lean Startup, life extension, lifelogging, loose coupling, loss aversion, low earth orbit, Lyft, Marc Andreessen, Mark Zuckerberg, market design, Max Levchin, means of production, Michael Milken, minimum viable product, natural language processing, Netflix Prize, NetJets, Network effects, new economy, Oculus Rift, offshore financial centre, PageRank, pattern recognition, Paul Graham, paypal mafia, peer-to-peer, peer-to-peer model, Peter H. Diamandis: Planetary Resources, Peter Thiel, Planet Labs, prediction markets, profit motive, publish or perish, radical decentralization, Ray Kurzweil, recommendation engine, RFID, ride hailing / ride sharing, risk tolerance, Ronald Coase, Rutger Bregman, Salesforce, Second Machine Age, self-driving car, sharing economy, Silicon Valley, skunkworks, Skype, smart contracts, Snapchat, social software, software is eating the world, SpaceShipOne, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Jurvetson, subscription business, supply-chain management, synthetic biology, TaskRabbit, TED Talk, telepresence, telepresence robot, the long tail, Tony Hsieh, transaction costs, Travis Kalanick, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, urban planning, Virgin Galactic, WikiLeaks, winner-take-all economy, X Prize, Y Combinator, zero-sum game

Portfolio Hardcover. Solis, B. (2013). What’s the Future of Business: Changing the Way Businesses Create Experiences. Wiley. Spear, S. J. (2010). The High-Velocity Edge: How Market Leaders Leverage Operational Excellence to Beat the Competition. Mcgraw-Hill. Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House. Taleb, N. N. (2012). Antifragile: Things That Gain from Disorder. Random House. Thiel, P. & Masters, B. (2014). Zero to One: Notes on Startups or How to Build the Future. Crown Business. Tracy, B. (2010). How the Best Leaders Lead: Proven Secrets to Getting the Most Out of Yourself and Others.

Only enterprises that plan for this new reality will have a chance at long-term success. Now that we have finished describing the characteristics of ExOs and their implications, we can look at the how an ExO maps onto other constructs. The following table compares ExO Attributes with Joi Ito’s MIT Media Lab Principles and the heuristics in Nassim Taleb’s Anti-Fragile theory. Joi Ito (MIT Medialab) Nassim Taleb (Anti-Fragile Theory) MTP Pull over push Compasses over maps Focus on the long term, not just the financials and short term Staff on Demand Resilience over strength Stay small and flexible Community & Crowd Systems (ecosystems) over objects Resilience over strength Build in options Stay small and flexible Algorithms - Build in stressors > Simplify and Automate Heuristics (skin in the game, orthogonal) Leased Assets Resilience over strength Reduce dependency and IT; stay small and flexible Invest in R&D Invest in data and social infrastructure Engagement (IC, gamify) Pull over push Build in options Heuristics: skin in the game Interfaces - Simplify and Automate Overcome cognitive biases Dashboard Learning over financial Simplify and Automate Short feedback loops Rewards only after project completion Experimentation Practice over theory Risk over safety Learning over education Diversify Build in hacking and stressors by yourself (fail fast and often; Netflix case w/ Chaos Monkey), especially in good times Build in options Risk over safety (not risk insensitivity) Avoid too much focus on efficiency, control and optimization Autonomy Emergence over authority Disobedience over compliance Decentralization Do not overregulate Challenge senior management Compartmentalize Share ownership within ExO on the edges (skin in the game) Social Technologies Emergence (peer-to-peer learning) over authority Build in stressors How Exponential is Your Organization?

Inevitably, even more time and money is spent adapting the product to fit the customer, a process that once again takes too long as the market moves on. In the end, of course, the product fails. In sum, NPD has become a process in which thinking and doing are separated for a long time period and where data-driven and behavioral customer feedback is delivered too late in the development process. As Nassim Taleb explains, “Knowledge gives you a little bit of an edge, but tinkering (trial and error) is the equivalent of 1,000 IQ points. It is tinkering that allowed the Industrial Revolution.” By comparison, consider the same scenario using the Lean Startup method: The company first researches the needs of the customer, then conducts an experiment to see if a proposed product matches those needs.


Capitalism, Alone: The Future of the System That Rules the World by Branko Milanovic

affirmative action, Asian financial crisis, assortative mating, barriers to entry, basic income, Berlin Wall, bilateral investment treaty, Black Swan, Branko Milanovic, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carried interest, colonial rule, corporate governance, creative destruction, crony capitalism, deindustrialization, dematerialisation, Deng Xiaoping, discovery of the americas, European colonialism, Fall of the Berlin Wall, financial deregulation, Francis Fukuyama: the end of history, full employment, ghettoisation, gig economy, Gini coefficient, global supply chain, global value chain, Great Leap Forward, high net worth, household responsibility system, income inequality, income per capita, invention of the wheel, invisible hand, job automation, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, labor-force participation, laissez-faire capitalism, land reform, liberal capitalism, low skilled workers, Lyft, means of production, new economy, offshore financial centre, Paul Samuelson, plutocrats, post-materialism, purchasing power parity, remote working, rent-seeking, ride hailing / ride sharing, Robert Solow, Silicon Valley, single-payer health, special economic zone, Tax Reform Act of 1986, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, uber lyft, universal basic income, Vilfredo Pareto, Washington Consensus, women in the workforce, working-age population, Xiaogang Anhui farmers

(Published with the title “The Birth of a New American Aristocracy.”) Swedberg, Richard, ed. 1991. The Economics and Sociology of Capitalism. Princeton, NJ: Princeton University Press. Sweezy, Paul. 1953. The Present as History. New York: Monthly Review Press. Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. Taleb, Nassim Nicholas. 2018. Skin in the Game: Hidden Asymmetries in Daily Life. New York: Random House. Thomas, Vinod, Yan Wang, and Xibo Fan. 2001. “Measuring Education Inequality—Gini Coefficients of Education.” Policy Research Working Paper No.

I saw the effect of wealth on commodification first hand when I worked on African household surveys, where a number of activities that are routinely monetized in rich economies are performed “for free” at home and had to have their values imputed; otherwise we would grossly underestimate the consumption level of households in many African countries. 25. In Nassim Taleb’s words: “If you are a Stone Age historical thinker called on to predict the future in a comprehensive report for your chief tribal planner, you must project the invention of the wheel or you will miss pretty much all of the action. Now, if you can prophesy the invention of the wheel, you already know what a wheel looks like, and thus you already know how to build a wheel” (Taleb 2007, 172). 26. World Bank (2019, p. 22, fig. 1.1). Jobs are classified as “at risk” if the probability of being automated is estimated at more than 0.7. 27.

Once the referee, not having seen how the goal was scored, has accepted it, the goal is as legal as can be, and there is no shame in celebrating it. Or even bragging about it. The conflict between what is legal and what is ethical is nicely illustrated in a story told by Cicero, and recently retold by Nassim Taleb in Skin in the Game (2018). It concerns Diogenes of Babylon and his pupil Antipater of Tarsus, who disagreed on the following matter: Should the merchant who is bringing grain to Rhodes at a time of scarcity and high prices reveal that another ship from Alexandria, also carrying grain, is just about to arrive in Rhodes?


pages: 831 words: 98,409

SUPERHUBS: How the Financial Elite and Their Networks Rule Our World by Sandra Navidi

"World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Alan Greenspan, Anthropocene, assortative mating, bank run, barriers to entry, Bear Stearns, Bernie Sanders, Black Swan, Blythe Masters, Bretton Woods, butterfly effect, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, central bank independence, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, commoditize, conceptual framework, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, digital divide, diversification, Dunbar number, East Village, eat what you kill, Elon Musk, eurozone crisis, fake it until you make it, family office, financial engineering, financial repression, Gini coefficient, glass ceiling, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Google bus, Gordon Gekko, haute cuisine, high net worth, hindsight bias, income inequality, index fund, intangible asset, Jaron Lanier, Jim Simons, John Meriwether, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kevin Roose, knowledge economy, London Whale, Long Term Capital Management, longitudinal study, Mark Zuckerberg, mass immigration, McMansion, mittelstand, Money creation, money market fund, Myron Scholes, NetJets, Network effects, no-fly zone, offshore financial centre, old-boy network, Parag Khanna, Paul Samuelson, peer-to-peer, performance metric, Peter Thiel, plutocrats, Ponzi scheme, power law, public intellectual, quantitative easing, Renaissance Technologies, rent-seeking, reserve currency, risk tolerance, Robert Gordon, Robert Shiller, rolodex, Satyajit Das, search costs, shareholder value, Sheryl Sandberg, Silicon Valley, social intelligence, sovereign wealth fund, Stephen Hawking, Steve Jobs, subprime mortgage crisis, systems thinking, tech billionaire, The Future of Employment, The Predators' Ball, The Rise and Fall of American Growth, too big to fail, Tyler Cowen, women in the workforce, young professional

Glattfelder, and Stefano Battiston, “The Network of Global Corporate Control,” PLoS ONE 6(10) (2011): e25995, doi: 10.1371/journal.pone .0025995. CHAPTER 1 1. Melanie Mitchell, Complexity: A Guided Tour (New York: Oxford University Press, 2009), Kindle location 3811. 2. Steven Johnson, Emergence (New York: Scribner, 2012), 39-40, 70, 78, Kindle edition. 3. For reference, see also: Nassim Nicholas Taleb, The Black Swan: Second Edition: The Impact of the Highly Improbable Fragility (New York: Random House, 2010), Kindle locations 4881-87, Kindle edition. 4. Steven H. Strogatz, Sync: How Order Emerges from Chaos in the Universe, Nature, and Daily Life (New York: Hachette, 2012), 231-232, Kindle edition. 5.

George Soros, The New Paradigm for Financial Markets: The Credit Crisis of 2008 and What It Means (New York: PublicAffairs, 2008), 102-105; George Soros, “Soros: General Theory of Reflexivity,” Financial Times, October 27, 2009, http://www.ft.com/intl/cms/s/2/0ca06172-bfe9-11de-aed2-00144feab49a.xhtml. 3. George Soros, Soros on Soros: Staying Ahead of the Curve (New York: Wiley, 1995), Kindle locations 1200-1204, Kindle edition. 4. For reference, see also: Taleb, The Black Swan, Kindle locations 4881-87. 5. Nicholas A. Christakis and James H. Fowler, Connected: The Surprising Power of Our Social Networks and How They Shape Our Lives (New York: Little, Brown and Company, 2009), 26, Kindle edition; Richard Koch and Greg Lockwood, Superconnect: Harnessing the Power of Networks and the Strength of Weak Links (New York: W.

Therefore, having top academic credentials, policy experience, and access to high-caliber networks provide thought leaders with distinct competitive advantages that propel them into the league of superhubs. Most thought leaders in finance are economists. A select few have become academic celebrities, such as Thomas Piketty, Nassim Taleb, and Paul Krugman, because they have touched the Zeitgeist. They are their own brands, with rock star status and almost cultlike followings. Inundated with media requests, exclusive invitations, and offers to join prestigious boards, their work surpasses the insular world of academia and becomes the center of public attention.


pages: 411 words: 98,128

Bezonomics: How Amazon Is Changing Our Lives and What the World's Best Companies Are Learning From It by Brian Dumaine

activist fund / activist shareholder / activist investor, AI winter, Airbnb, Amazon Robotics, Amazon Web Services, Atul Gawande, autonomous vehicles, basic income, Bernie Sanders, Big Tech, Black Swan, call centre, Cambridge Analytica, carbon tax, Carl Icahn, Chris Urmson, cloud computing, corporate raider, creative destruction, Danny Hillis, data science, deep learning, Donald Trump, Elon Musk, Erik Brynjolfsson, Fairchild Semiconductor, fake news, fulfillment center, future of work, gig economy, Glass-Steagall Act, Google Glasses, Google X / Alphabet X, income inequality, independent contractor, industrial robot, Internet of things, Jeff Bezos, job automation, Joseph Schumpeter, Kevin Kelly, Kevin Roose, Lyft, Marc Andreessen, Mark Zuckerberg, military-industrial complex, money market fund, natural language processing, no-fly zone, Ocado, pets.com, plutocrats, race to the bottom, ride hailing / ride sharing, Salesforce, Sand Hill Road, self-driving car, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Snapchat, speech recognition, Steve Jobs, Stewart Brand, supply-chain management, TED Talk, Tim Cook: Apple, too big to fail, Travis Kalanick, two-pizza team, Uber and Lyft, uber lyft, universal basic income, warehouse automation, warehouse robotics, wealth creators, web application, Whole Earth Catalog, work culture

When a person creates one of the most valuable companies in the world and has more money than every other human on earth, their life doesn’t lend itself to a tidy story line. Bezos himself believes in the narrative fallacy, a term popularized by Nassim Nicholas Taleb in his 2007 book, The Black Swan, a work that Bezos requires his top executives to read. Taleb argues that humans are biologically wired to turn complex situations into oversimplified stories. By that line of thinking, Bezos likely is not bothered by the contradictions in his life. The narrative fallacy of Bezos’s life is that he is a hard-driving, brilliant executive who cares about pleasing his customers more than anything else.

See Amazon Web Services Bagnell, Drew, 175 Baidu search engine, 123, 176 Bain & Company, 201, 235, 236 Baker Center for Leadership, 15 banking industry, 231–36 Amazon’s entry into, 213, 219, 231–32 digitization of, 124 financial data from, 232–33 regulatory challenges for Amazon in, 235–36 robo-advisory services in, 235 Barnes & Noble, 170, 232 Barron’s, 77 Bell Labs, 107 Benson, April, 18–19 Benson, Eric and Susan, 74 Berkshire Hathaway, 27, 226–27, 241 Berners-Lee, Tim, 125 Best Buy, 9, 16, 204–5 Bezonomics AI flywheel and, 76, 80 business’s two camps about, 270 competitive advantage of, 125–26 customer obsession in, 207 disruption by, 8, 27, 125 example of use of wide range of products and, 13–14 expansion into other industries and, 217 global wealth gap and, 125 goal of becoming part of people’s lives and, 14–15 impact on society of, 271 manager selection for new businesses and, 226 new paradigm for business and, 124–25 retailing and, 207, 213 Bezos, Jacklyn (Gise) (Jorgensen) “Jackie,” 31–33, 37, 251 Bezos, Jeff, 29–42 BUSINESS LIFE ability for running large organizations, 33 AI flywheel model, 5–6, 40, 83–84, 88 Alexa and voice recognition and, 109, 110–11, 116 Amazon Prime launch, 95–96 Amazon Prime free shipping decision, 97 on Amazon’s possible failure, 2, 269 attitude on product failures, 65 Blue Origin project, 68–70, 251 business background, 28 challenges to managers by, 53–54 characteristics separating him from other entrepreneurs, 31 Chinese sellers on Amazon.com, 155 confrontational culture of Amazon, 54–57 corporate board member selection, 66–67 customer service focus, 219 delivery time focus, 22 early brick-and-mortar book business, 33, 39–40 expansion into other industries and creation of new businesses, 25, 31, 215, 216–17 finance industry focus, 232 grandfather Gise’s influence, 33–34, 36–37, 42 as hard-driving executive, 30–31 health-care industry changes, 223–24 hedge fund experience, 39 identification with Amazon as founder, 53 industry-disrupting technologies introduction, 8, 24, 27, 116, 124, 125, 139, 168, 217, 260, 267, 271 local politicians’ criticism, 253–55 long-term strategy for Amazon, 59, 61–66 love for technology, 33 making decisions on facts, 43–44 as man of contradictions, 29–30 minimum wage support, 245–47 narrative fallacy belief, 30 New York City headquarters proposal, 30, 57, 252–54 politicians’ criticism, 239 positive qualities as executive, 58–59 Prime Video launch, 25 profitability strategy, 61–62 public perception and criticism, 57 public relations talent, 41, 239, 246 reaction to critics’ attacks on Amazon, 239, 240, 245 search for truth approach, 49, 51, 54–55, 56–57, 59 shadow program, 51–53 six-pager memos, 44, 45–46, 50–51 S-team, 15, 52–53 succession planning, 53 10,000-year clock, 70–71 treatment of competitors, 41–42 trust in data, 44, 45–46, 57 universal basic income support, 248–49 work-life harmony, 82–83 PERSONAL LIFE birth name, 31 family background, 31–34 as family man, 30 first marriage and divorce, 30, 38, 39 grandfather Gise’s influence, 33–34, 36–37 laser focus on work, 37 later relationship after divorce, 30, 39 lesson about human relations, 36–37 move to Seattle, 40 as parent, 38–39 philanthropy, 30, 251–52 resourcefulness, 31, 33, 37–39, 42–43, 59 social consciousness, 67–68 as Star Trek aficionado, 109 university education, 38 wealth and lavish spending, 29, 35 Bezos, MacKenzie, 7, 30, 38–40 Bezos, Mike, 32–33, 251 Bezos Family Foundation, 251–52 Bharara, Vinit, 184 big data. See also customer data flywheel model and, 5, 88 societal and ethical challenges of, 90–91 black box phenomenon, 91, 147 Black Swan, The (Taleb), 30 Blodget, Henry, 62, 65 Bloodworth, James, 132–33 Bloomberg, 81, 167 Blue Moon space vehicle, 70 Blue Origin, 61, 68–70, 251 Bluetooth, 111 Bluhdorn, Charlie, 216 Blumenthal, Neil, 211, 212–13 board of trustees, 66–67 book industry Amazon’s invasion of, 217–18 Bezos’s early brick-and-mortar store in, 33, 39–40 customer data and buying decisions in, 87 early success of Amazon in, 40 Internet revolution and, 125 Boom, Steve, 26 Borders, 170 Bourne, Ryan, 244–45, 247 Brand, Stewart, 71 breakage model, 99 Brewer, Rosalind, 67 Bridgewater, 55 Brooks Brothers, 261–62 Brynjolfsson, Erik, 142 Buffett, Warren, 27, 227, 241 Business Insider, 62, 65, 171, 173 business models AI-driven, 4, 6, 86, 269–70 Amazon’s disruption of other companies’ plans, 260 Amazon’s use of, 208, 234–35, 247 Bezonomics for, 9 Bezos’s creation of, 4, 6, 125, 247 disruptive nature of, 260 influence of national trend of rising pay on, 247 Internet use as basis of, 125 social conscience and, 211 societal and ethical challenges of, 90–91 web as basis for, 125 buying model AI and, 85–87 customer data for predictions in, 87–88 Cainiao, 117–18 Canalys, 115 Cannon, Debra, 209 capitalism, 11, 240, 242–43, 260, 267 Capital One, 236 Carlson, Tucker, 243–44 Carnegie, Andrew, 264 Carney, Jay, 58, 252–53, 254, 263 Carrefour, 189 cars.

See retailing and retail stores shift to online from brick-and-mortar stores, 24, 33 shoppers’ desire for option to browse in, 24 streaming media, 33. See also Amazon Music; Prime Video streaming TV service, 236–37. See also Fire TV SunTrust Robinson Humphrey, 21 Super Saver Shipping, 95, 96 Susskind, Daniel, 127 Sylvester II, Pope, 107 Taleb, Nassim Nicholas, 30 talking dolls, 107 Talwar, Harit, 8 Target, 181, 206, 244 telemedicine, 27, 222–23, 229–31 television shows and series content costs with, 101–2 free with Prime, 4, 100, 101, 260 Temkin Experience Ratings, 171 Tencent, 123 AI-driven flywheel at, 88 AI Internet-connected devices from, 124 AI skills and customer knowledge of, 8, 270 Amazon’s competition with, 14, 266 brand value of, 16 customer data from, 89 Dreamwriter robot of, 143 number of employees at, 123 10,000-year clock, 70–71 Tesco, 189 Tesla, 53, 175, 248 Thielke, Vincent, 115 third-party merchants.


pages: 232 words: 70,835

A Wealth of Common Sense: Why Simplicity Trumps Complexity in Any Investment Plan by Ben Carlson

Albert Einstein, asset allocation, backtesting, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, book value, business cycle, buy and hold, buy low sell high, commodity super cycle, corporate governance, delayed gratification, discounted cash flows, diversification, diversified portfolio, do what you love, endowment effect, family office, financial independence, fixed income, Gordon Gekko, high net worth, index fund, John Bogle, junk bonds, loss aversion, market bubble, medical residency, Occam's razor, paper trading, passive investing, Ponzi scheme, price anchoring, Reminiscences of a Stock Operator, Richard Thaler, risk tolerance, Robert Shiller, robo advisor, South Sea Bubble, sovereign wealth fund, stocks for the long run, technology bubble, Ted Nelson, transaction costs, Vanguard fund, Vilfredo Pareto

Understanding Rule Number 1 of Investing The Risk Tolerance Questionnaire Risk versus Uncertainty Risk Aversion The Cycle of Fear and Greed Key Takeaways from Chapter 3 Notes CHAPTER 4 Market Myths and Market History Myth 1: You Have to Time the Market to Earn Respectable Returns Myth 2: You Have to Wait until Things Get Better Before You Invest Myth 3: If Only You Can Time the Next Recession, You Can Time the Stock Market Myth 4: There's a Precise Pattern in Historical Market Cycles Myth 5: Stocks and Bonds Always Move in Different Directions Myth 6: You Need to Use Fancy Black Swan Hedges in a Time of Crisis Myth 7: Stocks Are Riskier Than Bonds Myth 7a: Bonds Are Riskier Than Stocks Myth 8: The 2000s Were a Lost Decade for the Stock Market Myth 9: New All-Time Highs in the Stock Market Mean It's Going to Crash Myth 10: A Yield on an Investment Makes It Safer Myth 11: Commodities Are a Good Long-Term Investment Myth 12: Housing Is a Good Long-Term Investment Myth 13: Investing in the Stock Market Is Like Gambling at a Casino Key Takeaways from Chapter 4 Notes CHAPTER 5 Defining Your Investment Philosophy Degrees of Active and Passive Management The Benefits of Doing Nothing Exercising Your Willpower Simplicity Leads to Purity Defining Yourself as an Investor Key Takeaways from Chapter 5 Notes CHAPTER 6 Behavior on Wall Street Threading the Needle So Never Invest in Active Funds?

Figure 4.1 Three-Year Rolling Correlation between Stocks and Bonds The true diversification benefit of owning both stocks and bonds comes during the down years. Going back to 1928, there have only been three times that both finished down in the same calendar year. (1931, 1941, and 1969). Myth 6: You Need to Use Fancy Black Swan Hedges in a Time of Crisis Following the 2007 to 2009 stock market crash investors were scrambling for answers: How can I protect against a future collapse? What kinds of funds do I need to protect myself? As usual, Wall Street was more than willing to step in with a plethora of complex strategies to fill this void including bear market funds, double and triple leveraged inverse ETFs, market neutral funds, long/short funds and a host of other fund structures that promised to protect investors on the downside.

Index 401(k) retirement plans 60/40 portfolio 80/20 rule active mutual funds Adams, John Quincy Affleck, Ben Alabama Crimson Tide all-time highs Annaly Capital Management Apple AQR Capital Management Asness, Cliff asset allocation asset allocation quilt Back to the Future Part II Barber, Brad Barton, Harris beating the market behavior gap benchmarking Benke, Alex Berkshire Hathaway Bernanke, Ben Bernstein, Peter Bernstein, William betterment Black Monday black swans Bogle, John Boiler Room bonds Bryant, Bear Bryant, Kobe Buffett, Warren BusinessWeek buy and hold Caesar, Julius Candy, John Case-Shiller Index CFA CFP Charles Schwab chasing performance Churchill, Winston Cincinnati Bengals commodities compensation Confucius correlation currency fluctuations “The Death of Equities” degrees of active and passive management Descartes, Rene diversification dividends doing nothing dollar cost averaging Dow Jones Industrial Average Dunn, Elizabeth eBay Efficient Market Hypothesis (EMH) eight symptoms of group think Einstein, Albert Ellis, Charles xv emerging markets emotional intelligence empathy endowment funds envy exchange-traded funds (ETFs) Farley, Chris fear and greed Federal Reserve Ferri, Rick Fidelity Investments financial advice financial advisors questions to ask financial pundits Gekko, Gordon Gleason, Jackie Glenn, Joshua globalization Goleman, Daniel Graham, Benjamin Great Depression Greenspan, Stephen growth stocks Harvard Endowment Fund herd mentality home country bias Housel, Morgan housing how to be a good client Hsu, Jason Ibbotson, Roger illusion of control incentives independence index funds inflation institutional investors The Intelligent Investor (Graham) international equity diversification invert investment plan investment policy statement (IPS) Japan JP Morgan junk bonds Kahneman, Daniel Kaplan, Paul Keynes, John Maynard Kinnel, Russ Klarman, Seth Lehman Brothers Les Amants life cycle investing liftoff Livermore, Jesse lollapalooza effects longevity risk loss aversion lost decade LSU Tigers Madoff, Bernie margin of safety market cycles market Timing Marks, Howard Mauboussin, Michael McFly, Marty mean reversion Jordan, Michael Michelin star ratings midcaps millennials momentum Montana, Joe Monte Carlo Simulation Morning star motivation Mr.


What We Cannot Know: Explorations at the Edge of Knowledge by Marcus Du Sautoy

Albert Michelson, Andrew Wiles, Antoine Gombaud: Chevalier de Méré, Arthur Eddington, banking crisis, bet made by Stephen Hawking and Kip Thorne, Black Swan, Brownian motion, clockwork universe, cosmic microwave background, cosmological constant, dark matter, Dmitri Mendeleev, Eddington experiment, Edmond Halley, Edward Lorenz: Chaos theory, Ernest Rutherford, Georg Cantor, Hans Lippershey, Harvard Computers: women astronomers, heat death of the universe, Henri Poincaré, Higgs boson, invention of the telescope, Isaac Newton, Johannes Kepler, Large Hadron Collider, Magellanic Cloud, mandelbrot fractal, MITM: man-in-the-middle, Murray Gell-Mann, music of the spheres, Necker cube, Paul Erdős, Pierre-Simon Laplace, quantum entanglement, Richard Feynman, seminal paper, Skype, Slavoj Žižek, stem cell, Stephen Hawking, technological singularity, Thales of Miletus, Turing test, wikimedia commons

As the philosopher Slavoj Zizek argues, these are possibly the most dangerous, especially when held by those with political power. This is the domain of delusion. Repressed thoughts. The Freudian unconscious. I would love to tell you about the unknown unknowns, but then they’d be known! Nassim Taleb, author of The Black Swan, believes that it is the emergence of these that are responsible for the biggest changes in society. For Kelvin it was relativity and quantum physics that turned out to be the unknown unknown that he was unable to conceive of. So in this book I can at best try to articulate the known unknowns and ask whether any will remain forever unknown.

Oxford University Press, 2014. Stewart, Ian. Does God Play Dice? The New Mathematics of Chaos. Basil Blackwell, 1989. Stoppard, Tom. Arcadia. Faber & Faber, 1993. Sudbery, Anthony. Quantum Mechanics and the Particles of Nature: An Outline for Mathematicians. Cambridge University Press, 1986. Taleb, Nassim. The Black Swan: The Impact of the Highly Improbable. Allen Lane, 2007. Tegmark, Max. ‘The Mathematical Universe’, Found.Phys. 38: 101–150, 2008. Tegmark, Max. Our Mathematical Universe: My Quest for the Ultimate Nature of Reality. Knopf, 2014. Tononi, Giulio and Sporns, Olaf. ‘Measuring information integration’, BMC Neuroscience 4, 2003.

415–18; certainty and 364–6; consciousness and see consciousness; conjectures as lifeblood of 420; cracking of great unsolved problems 375–8; dice and see dice; God and see God; infinity and see infinity; limit of senses and 417–18; mathematical universe hypothesis (MUH) 297–8; proof and 6, 366–73, 377–8, 401, 405–6, 417; proves that certain things are beyond knowledge 369–73, 401, 405–6, 417; quantum physics and see quantum physics; science vs. 364–6; theorems see under individual theorem name; timeless nature of 297–8; unknowns in see under individual area of mathematics; ‘unreasonable effectiveness of mathematics’ 298 see also individual area of mathematics Maxwell, James Clerk 34, 136, 142, 143, 419; Matter and Motion 47 May, Robert M. 51–3, 72; chaos theory and 48–54, 55, 56, 57, 72; ‘Simple Mathematical Models with Very Complicated Dynamics’ 48–51, 56 McCabe, Herbert 15, 181 McGurk effect 328 Mendeleev, Dmitri 89–90, 91, 106, 108, 116 Mercury 63–4, 190, 194 Méré, Chevalier de 24–5, 26 Mermin, David 154, 155 Messiaen, Olivier 305 MET office 46–7, 61–2 Michell, John 275 Michelson, Albert Abraham 10–11, 253, 254, 255, 275 microscopes 78–9, 88, 93, 126, 305, 307, 416 Milky Way 203, 204, 227 Millikan, Robert Andrews 142–3 mind-body problem 330–2 Minkowski, Hermann 261–2, 270 Mittag-Leffler, Gösta 39–41, 204, 399 Moon 20, 34, 37, 38, 189, 190, 198, 206, 250, 251, 267 Moore’s law 8, 281 Mora, Patricia 280 Morley, Edward 253, 254, 255, 275 Mount Wilson, California 105–6, 204 multiverse 227–35, 238, 242, 298, 382, 404–5 muon 104, 105, 106, 258–9 Museum of the History of Science 188 music 77, 78, 79, 80–1, 82, 85, 88, 89, 90, 101, 121, 122, 126, 127, 137, 138, 139, 140, 177, 191, 195, 308, 314, 369, 419 mysterianism 349–50, 351 National Physical Laboratory, London 252, 254 Nature 8, 48, 53 Navier–Stokes equations 34 Ne’eman, Yuval 115 Necker cube 321, 323, 328 Neddermeyer, Seth 104 negative curvature 210 negative numbers 371–2 Neptune 197, 227 neurons: ageing and 258, 259; C. elegans worm complete neuronal network published 4, 345, 349; consciousness and 5, 309, 311–14, 323–9, 340, 341, 342, 343–6, 347, 348, 349, 350, 351, 353, 359, 376–7; Jennifer Aniston neuron 4, 324–7, 347, 359; Ramón y Cajal discoveries 311–13, 348 neutrinos 105, 221, 407 neutron 79, 90, 95, 100–1, 103, 105, 106, 107, 110, 116, 119, 125, 126, 165, 166 New Scientist 2, 4 Newlands, John 90 Newton, Sir Isaac 5, 6, 28–9, 53, 86, 131, 141, 156, 168, 176, 179, 262, 272; calculus and 30–2, 87; dice and 35–6, 154; God and 71; gravity and 29, 30, 32, 33–4, 37, 38, 72, 88, 196, 278–9; laws of motion and 29, 32–7, 38, 67, 72, 78, 87–8, 97, 133, 143, 153, 154, 159, 278–9, 280; life of 29–30; Opticks 88, 134; Philosophiae Naturalis Principia Mathematica 29, 32–5, 88, 252, 257; planetary motion and 33–41, 72, 280; relativity and 257; space and time, view of absolute nature of 252, 253, 262; Theory of Everything and 35; theory of light 88, 134, 135, 141 Nishijima, Kazuhiko 109–10 Nobel Prize 5, 106, 143, 204, 236, 321 non-commutativity 164 novae 204 nuclear fusion 274 nucleons 107–8 number theory 378, 384–8, 401–2, 403, 404 observation, quantum physics and 148–58, 168–70, 173, 178 Occam’s razor 233 Old Babylonian Period 83 omega particle 115–16 ontology 70, 170, 177, 178, 179, 418 Oppenheimer, Robert 117 Oresme, Nicolas 190–1, 218, 235, 391–2, 393, 394 Oscar II of Norway and Sweden, King 37–8, 62 out-of-body experiences 328–30 Owen, Adrian 333–4 Pais, Abraham 109 Papplewick Pumping Station 137–8, 139 paradox of unknowability 413–14 parallax 200–1, 202 parallel postulate 378–80, 401 Paris, Jeff 388 Parkinson’s UK Brain Bank 307–8, 313–14 Pascal, Blaise 24–5, 26–8, 36; Pascal’s wager 26–8, 241, 242; Pensées 389 Penrose, Roger 277–8, 290, 291–6, 387 pentaquark 120, 124 Pepys, Samuel 35–6 perceptronium 356 Perelman, Grigori 375–6 periodic paths 38–9 periodic table 86–7, 89–92, 95, 97, 101, 103, 106, 116, 125, 274 Perrin, Jean Baptiste: Les Atomes 94 photoelectric effect 140–3, 147 photons 10, 108, 141, 147, 148, 149, 150, 155, 156, 163, 168–9, 207, 208, 220–1, 227–8, 284, 287, 291, 292 physics: limits of discoveries 10–11, 12, 20, 123, 405, 418; many worlds’ interpretation of 155–6; no mechanism to explain 230; tension between mathematics and 404–5; unification of general relativity and quantum physics 7, 168, 219, 220 see also under individual area of physics pions 106, 107, 108, 109, 110–11, 115, 118 Planck, Max: Planck constant 138–9, 141, 163, 407; Planck length 167–8, 407 Planck spacecraft 226 planets: detecting new 195–8, 200–1, 227; distances between 193–5; measuring time and 251, 259, 267, 269, 278–9, 280; modelling of future trajectories 63–4, 72; motion of 29, 33–41, 62–4, 72, 88, 193, 279, 280; multiverse and 231; music of the spheres and 81; new habitable 3; singularities and 280 Plato 81–2, 113, 188, 208–9, 304, 368, 373, 409–10, 412 Pleiades 20, 250 Plough or Big Dipper 190, 191, 213 Podolsky, Boris 172 Poincaré, Henri 4, 36–41, 42, 44, 62, 64, 375 Poisson, Siméon-Denis 34 Polaris star 188 Polkinghorne, John 69–70, 174–9, 240, 355 Popper, Karl 233, 239, 415 population dynamics 1–2, 48–51, 56, 62, 65, 176, 280–1 PORC conjecture 376–7, 388, 420 Preskill, John 289–90 prime numbers 8, 157, 404, 415 probability 21–2, 23–8, 35, 37, 60, 92, 94, 146–8, 153, 154, 155, 157, 158, 159, 162, 178, 308, 349, 403, 405, 408 proof: birth of idea 366–9; by contradiction 83–4, 243; certain knowledge and mistakes in mathematical 39–41, 377, 383–8, 402–3, 412–16; chance to establish more permanent state of knowledge and 6, 366–7; false 412–13 proprioception 416–17 proton 79, 90, 95, 98–9, 100, 101, 103, 105, 106, 107, 108, 109, 110, 116, 117, 119–20, 123, 125, 126, 166 Proxima Centauri 188, 201, 202 punctuated equilibria 61 Pythagoras 80, 81, 82, 83, 84, 89, 117, 127, 206, 243, 255, 256, 262, 324, 325, 326, 359, 363, 370, 374 qualia 325, 350, 357 quantum physics 11, 12, 28, 69, 70, 104, 126, 127, 131, 132, 133, 143–58, 159–83, 219, 220, 228–9, 231, 241, 274, 284, 288, 289, 297, 338, 354, 355, 402, 407, 408–9; black holes and 274, 284, 288, 289, 355; chaos theory and see chaos theory; Copenhagen interpretation of 178; counterintuitive nature of 132, 159, 164, 284; density of electron and 126; double-slit light experiment 134–6, 143, 144–7, 148, 149, 150, 151, 152–3, 154, 157, 161–2, 163, 165, 166, 169, 170, 171, 173; electromagnetism, attempt to unify with 104; general relativity, unifying with theory of 7, 168, 219, 220; inflation and 229; language and 408–9; observation and 148–58, 168–70, 173, 178; particle nature of light and 88, 134–49; quantum entanglement 172; quantum fluctuations 182, 183, 228–9, 231, 288; quantum gravity 7, 168, 183; quantum microscopes 79; quantum tunnelling 165–6; quantum Zeno effect 150–1; radioactive uranium emission of radiation and 131–3, 143–4, 150, 151, 158, 159, 160, 166–7, 171–2, 173–4, 176, 177, 178, 179, 180, 183; repeating an experiment in 408; reversible laws of 284–5, 355; trusting the maths of 165; uncertainty principle and 133, 159–60, 162–3, 164, 165, 166–7, 168–70, 180, 181–3, 243, 266, 274–5, 288, 290; wave function 5, 146–9, 153–8, 165, 169, 173, 177, 178–9, 402 quark 3, 79, 116–21, 122, 123, 124, 125, 126, 127, 175, 187, 298, 335, 407 quidditism 298 Rabi, Isidor 105 radioactivity 98–9, 107, 131, 132–3, 171, 173 Ramón y Cajal, Santiago 311–13, 348 randomness 70, 131, 133, 143–4, 153, 154–5, 171–2, 174, 230, 338 redshift 214–16, 220, 222, 224 Rees, Martin 418 Reiss, Diana 318 relativity, theories of 5, 6, 7–8, 12, 72, 105, 115, 141, 143, 168, 219, 220, 248, 252, 253–72, 273, 275, 277, 278, 281, 282, 285, 288, 291, 293, 296, 299, 359 religion 13–15, 68–71, 174–8, 179, 181, 235–40, 320, 348–9, 355, 393, 399, 401–2, 410, 411 see also God rhetoric, art of 368, 369 Riemann, Bernhard 261–2, 376, 377, 388, 402, 404, 413, 420 Robertson, Howard 163 Robinson, Julia 401 Rømer, Ole 199 Rosen, Nathan 172 Rosetta Stone 113 Rovelli, Carlo 300 Royal Academy of Sciences, Paris 199 Royal Institution Christmas Lectures 2–3 Royal Observatory 197 Royal Society 90, 326–7 Royal Swedish Academy of Science 39 Rufus of Ephesus 306 Rumsfeld, Donald 11 Rushdie, Salman: Midnight’s Children 247, 264 Russell, Bertrand 380–1, 412 Rutherford, Ernest 98, 99, 100, 119, 120 Saint Augustine 22, 296; City of God 391; Confessions 249 Sartre, Jean-Paul 337 Saturn 63, 64, 190, 196 Schopenhauer, Arthur 77, 78 Schrödinger, Erwin 5, 131, 132, 146, 154, 177 Schumacher, Heinrich Christian 392 science/scientific discovery: constantly evolving nature of 364–6; dominance of 1–2; exponential growth in 3–4, 8–9; laws of nature, search for ultimate 9; mathematics vs. 364–6; only appears to describe reality 418; questions that can never be resolved 9–13, 295, 347, 349–50, 353, 355–60, 405–6, 407–20; success rate of and production of true knowledge 416 Scientific American 2 Searle, John 338–9 self-recognition test, animals and 317–19 sense of self 317, 319–20, 331, 342, 343 senses: limit of 416–18; out-of-body experiences and 328–30, 416 Serber, Robert 117, 119 S4 (group of symmetries) 112 Shakespeare, William 219, 399 Shapely, Harlow 204 Shull, Clifford 165 Sigma baryons 107, 108, 109, 110, 115, 119 singularity 8–9, 219, 220, 238, 248, 278–82, 283, 284, 289, 290, 293, 294 61 Cygni 201, 202 sleep, consciousness and 315–16, 339–41, 342, 343, 344, 346 Small Magellanic Cloud 203 Socrates 412 space-time: black holes and 276–8, 283, 284, 285; God and 296–8; origin of concept 262–4; shape of 264–72, 275–8, 283; singularities and 283, 284, 293 special relativity, theory of 105, 141, 143, 248, 252, 253–64, 275, 296, 359 Sphinx observatory, Switzerland 213–14, 223 square number 392, 394 ‘squaring the circle’ 373–4 Stanford University 229, 401; Stanford Linear Accelerator Center 119 stars: Andromeda nebula 203, 204; Big Bang and 220; black holes and 274–7, 284; chemical composition of 10; collapse of 222, 275, 276, 277; Comte predicts we will never know constituents of 10, 202, 243, 347, 409; creation of a 274; curved space-time and 271–2; death of 222; expanding universe and 214–18, 220, 222–3, 224, 227; fusion of atoms in 274; general theory of relativity and 271, 272; luminous matter and 238; measuring distance/brightness of 202–5, 214–16; paper star globe 187–8, 190, 195, 200, 201, 225, 227, 244; red giant 63; redshift and 214–16, 220, 222, 224; shape of universe and 187–8, 208–9; size of universe/infinity and 187–8, 190–2, 202–7; speed of light and 253; stellar parallax 200–1, 202; supernova and 222; white dwarf 274–5 see also under individual star and constellation name stellar parallax 200–1, 202 Stoppard, Tom: Arcadia 19, 53 strange quark 117, 118, 119, 120, 121 strangeness 108, 109–11, 115–16 string theory 127, 168, 234 strong nuclear force 107, 108, 109–10 Strzalko, Jaroslaw 67 SU(3) (symmetrical object) 5, 111–12, 113, 114, 115, 116–17, 120, 125 SU(6) (symmetrical object) 121 Sun 188, 189, 190, 193, 196, 199–200, 201, 203, 275; black holes and 276, 277; as centre of universe 193, 227, 413; Cepheid stars and 203, 204; chemical composition of 10; creation of 274; curved space-time and 271; distance of Earth from 193–5, 201, 206; entropy and 287; gravity and creation of 274; mass of 34, 275; measuring time and 251, 253, 271; pattern of movement 20, 188, 227, 251, 253, 271; planets orbit of 176, 193–6, 227; red giant, evolution into 63; size of 189; speed of light and 198, 199–200, 201, 253; time measurement and 251, 253, 271; trigonometry and 189, 201 supernova 222, 275 symmetry 103, 110, 111–17, 120, 121, 125, 269–72, 273, 327, 342, 344, 374, 376 synesthesia 325–6 Taleb, Nassim: The Black Swan 12 Tartaglia, Niccolò Fontana 25 technology: brain studies and 306, 314, 329–30, 336; singularity 281; rate of change/growth in 8, 281 Tegmark, Max 297–8 telescope: Andromeda and 204; discovery of new planets and 3, 195–8; invention of 189, 190, 192, 193–5, 200, 296, 305, 416; measuring distance of planets and 193–5; name 193; neural 305, 314–16, 323; paper 322–3, 325–6, 328; speed of light and 198–9, 200; stellar parallax and 201; trigonometry as 189–90 telomeres 5 Templeton Foundation 236, 237 Templeton, Sir John/Templeton prize 235–6, 237 Thales of Miletus 366–7 ‘The Great Debate’, Smithsonian Museum of Natural History, 1920 203–4 theory of abduction 233 Theory of Everything 9, 34–5 thermal time hypothesis 300 thermodynamics, second law of 285–6, 287, 290, 293 Thomson, J.


pages: 283 words: 81,376

The Doomsday Calculation: How an Equation That Predicts the Future Is Transforming Everything We Know About Life and the Universe by William Poundstone

Albert Einstein, anthropic principle, Any sufficiently advanced technology is indistinguishable from magic, Arthur Eddington, Bayesian statistics, behavioural economics, Benoit Mandelbrot, Berlin Wall, bitcoin, Black Swan, conceptual framework, cosmic microwave background, cosmological constant, cosmological principle, CRISPR, cuban missile crisis, dark matter, DeepMind, digital map, discounted cash flows, Donald Trump, Doomsday Clock, double helix, Dr. Strangelove, Eddington experiment, Elon Musk, Geoffrey Hinton, Gerolamo Cardano, Hans Moravec, heat death of the universe, Higgs boson, if you see hoof prints, think horses—not zebras, index fund, Isaac Newton, Jaron Lanier, Jeff Bezos, John Markoff, John von Neumann, Large Hadron Collider, mandelbrot fractal, Mark Zuckerberg, Mars Rover, Neil Armstrong, Nick Bostrom, OpenAI, paperclip maximiser, Peter Thiel, Pierre-Simon Laplace, Plato's cave, probability theory / Blaise Pascal / Pierre de Fermat, RAND corporation, random walk, Richard Feynman, ride hailing / ride sharing, Rodney Brooks, Ronald Reagan, Ronald Reagan: Tear down this wall, Sam Altman, Schrödinger's Cat, Search for Extraterrestrial Intelligence, self-driving car, Silicon Valley, Skype, Stanislav Petrov, Stephen Hawking, strong AI, tech billionaire, Thomas Bayes, Thomas Malthus, time value of money, Turing test

We have no reason to be surprised at the absence of ETs. We may well be alone in the galaxy or even the universe, and it’s not out of line with what scholars currently believe. Where is everybody? The Oxford group’s answer is “probably extremely far away, and quite possibly beyond the cosmological horizon and forever unreachable.” Lemmings and Black Swans There are optimists who say that the past is no guide to the future. They speak of a singularity. This can be raised as an objection to Gott’s analysis. If most ET civilizations are not too different from our own, then they will experience rapid technological advancement. Assume only that some ETs are a few millennia ahead of us (which is nothing in cosmic time), and they already could have experienced a transformation in which technologic power zoomed abruptly upward.

What exponentially advanced technology means for population and survival is an open question. Today many worry that our accelerating digital technology will be the agent of our destruction. As Gott wryly puts it, Einstein was a smart guy, but he didn’t live any longer than a lot of people who weren’t so smart. In Ulam and von Neumann’s original sense, the singularity is the ultimate black swan event, not to be predicted from anything that came before, and “beyond which human affairs… could not continue.” The singularity could be another name for doomsday. Gott told me that, if he ever met an extraterrestrial, he would immediately want to ask two things. One, How long has your civilization lasted?

There is not the same risk of someone inventing a “better” soft drink tomorrow. Thousands of soft drinks have been invented in the past century, and for whatever reason none has been able to dethrone Coke. This is worth heeding, even if you’ve never understood the appeal of bubbly brown sugar-water. Investor-philosopher Nassim Taleb said of Lindy’s law: “If there’s something in the culture—say, a practice or a religion that you don’t understand—yet has been done for a long time—don’t call it ‘irrational.’ And: Don’t expect the practice to discontinue.” The Purloined Harry Potters The survival curves we see for companies and plays are deeply ingrained in our world.


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When to Rob a Bank: ...And 131 More Warped Suggestions and Well-Intended Rants by Steven D. Levitt, Stephen J. Dubner

Affordable Care Act / Obamacare, Airbus A320, airport security, augmented reality, barriers to entry, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, Broken windows theory, Captain Sullenberger Hudson, carbon tax, creative destruction, Daniel Kahneman / Amos Tversky, deliberate practice, feminist movement, food miles, George Akerlof, global pandemic, information asymmetry, invisible hand, loss aversion, mental accounting, Netflix Prize, obamacare, oil shale / tar sands, Pareto efficiency, peak oil, pre–internet, price anchoring, price discrimination, principal–agent problem, profit maximization, Richard Thaler, Sam Peltzman, security theater, sugar pill, Ted Kaczynski, the built environment, The Chicago School, the High Line, Thorstein Veblen, transaction costs, Tyler Cowen, US Airways Flight 1549

The participants are: Arthur Brooks, who teaches business and government at Syracuse and is the author of Who Really Cares: The Surprising Truth About Compassionate Conservatism; Tyler Cowen, an economist at George Mason who writes books and maintains the Marginal Revolution blog; Mark Cuban, the multifaceted entrepreneur and Dallas Mavericks owner; Barbara Ehrenreich, author of the low-rent classic Nickel and Dimed and many other works; and Nassim Nicholas Taleb, the noted flâneur and author of The Black Swan and Fooled by Randomness. Here is the question we put to each of them: You are walking down the street in New York City with ten dollars of disposable income in your pocket. You come to a corner with a hot-dog vendor on one side and a beggar on the other. The beggar looks like he’s been drinking; the hot-dog vendor looks like an upstanding citizen.

That’s a larger question than I can answer here (not that I’m capable anyway), but it probably has to do with the heuristics—the shortcut guesses—our brains use to solve problems, and the fact that these heuristics rely on the information already stored in our memories. And what gets stored away? Anomalies—the big, rare, “black swan” events that are so dramatic, so unpredictable, and perhaps world-changing, that they imprint themselves on our memories and con us into thinking of them as typical, or at least likely, whereas in fact they are extraordinarily rare. Which brings us back to Bruce Pardo and Atif Irfan. The people who didn’t seem to fear Pardo were friends and relatives.

And before anyone virtuously offers him a hot dog, they should reflect on the possibility that the beggar is a vegetarian or only eats kosher or halal meat. So if the beggar approaches me and puts out his hand, and if I only have a ten-dollar bill, I have to give it to him. It’s none of my business whether he plans to spend it on infant formula for his starving baby or a pint of Thunderbird. NASSIM NICHOLAS TALEB This question is invalid and answers to it would not provide useful information. Let me explain: When I recently had drinks and cheese with Stephen Dubner (I ate 100 percent of the cheese), he asked me why economics bothers me so much as a discipline, to the point of causing allergic reactions when I encounter some academic economists.


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The Complacent Class: The Self-Defeating Quest for the American Dream by Tyler Cowen

affirmative action, Affordable Care Act / Obamacare, Airbnb, Alvin Roth, assortative mating, behavioural economics, Bernie Sanders, bike sharing, Black Lives Matter, Black Swan, business climate, business cycle, circulation of elites, classic study, clean water, David Graeber, declining real wages, deindustrialization, desegregation, digital divide, Donald Trump, driverless car, drone strike, East Village, Elon Musk, Ferguson, Missouri, Francis Fukuyama: the end of history, gentrification, gig economy, Google Glasses, Hyman Minsky, Hyperloop, income inequality, intangible asset, Internet of things, inventory management, knowledge worker, labor-force participation, low interest rates, low skilled workers, Marc Andreessen, Mark Zuckerberg, medical residency, meta-analysis, obamacare, offshore financial centre, Paradox of Choice, Paul Samuelson, Peter Thiel, public intellectual, purchasing power parity, Richard Florida, security theater, sharing economy, Silicon Valley, Silicon Valley ideology, Skype, South China Sea, Steven Pinker, Stuxnet, The Great Moderation, The Rise and Fall of American Growth, total factor productivity, Tyler Cowen, Tyler Cowen: Great Stagnation, upwardly mobile, Vilfredo Pareto, working-age population, World Values Survey

Of course, that is just an example. I don’t know what this crisis will be or when it will come. If not a foreign policy problem from a two- or three-front conflict, it could be an environmental catastrophe requiring immediate attention, a major terrorist attack, or perhaps something entirely unexpected, a true “Black Swan,” so to speak, in Nassim Taleb’s use of that term. Ramping up government spending to respond to that crisis won’t be so simple. It could require higher tax rates and higher government spending—and bigger cutbacks elsewhere—than the American economy could sustain or the American people would be willing to support.

Richard Florida coined the term “the Great Reset” in a book of the same name, mostly about the evolution of North American cities. Greg Ip, an economic reporter at the Wall Street Journal, wrote a book called Foolproof: Why Safety Can Be Dangerous and How Danger Makes Us Safe, about how the obsessive quest for safety can be self-defeating, because risk does eventually accumulate. Nassim Taleb titled his 2015 essay with Gregory F. Treverton “The Calm Before the Storm: Why Volatility Signals Stability, and Vice Versa.” So these ideas are in the air, but they haven’t burst forth to dominate the discourse. Therefore, I wish to say it again: The biggest story of the last fifteen years, both nationally and globally, is the growing likelihood that a cyclical model of history will be a better predictor than a model of ongoing progress.

Swanson, Ana. “These Are the Jobs Where People Are Most Likely to Marry One Another.” The Washington Post, September 21, 2015. Syverson, Chad. “Challenges to Mismeasurement Explanations for the U.S. Productivity Slowdown.” National Bureau of Economic Research Working Paper 21974, February 2016. Taleb, Nassim Nicholas, and Gregory F. Treverton. “The Calm Before the Storm: Why Volatility Signals Stability, and Vice Versa.” Foreign Affairs (January/February 2015). Tanner, Adam. “How Ads Follow You from Phone to Desktop to Tablet.” MIT Technology Review, July 1, 2015. Taylor, Kate. “Race and Class Collide in a Plan for Two Brooklyn Schools.”


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Bourgeois Dignity: Why Economics Can't Explain the Modern World by Deirdre N. McCloskey

"Friedman doctrine" OR "shareholder theory", Airbnb, Akira Okazaki, antiwork, behavioural economics, big-box store, Black Swan, book scanning, British Empire, business cycle, buy low sell high, Capital in the Twenty-First Century by Thomas Piketty, classic study, clean water, Columbian Exchange, conceptual framework, correlation does not imply causation, Costa Concordia, creative destruction, critique of consumerism, crony capitalism, dark matter, Dava Sobel, David Graeber, David Ricardo: comparative advantage, deindustrialization, demographic transition, Deng Xiaoping, do well by doing good, Donald Trump, double entry bookkeeping, electricity market, en.wikipedia.org, epigenetics, Erik Brynjolfsson, experimental economics, Ferguson, Missouri, food desert, Ford Model T, fundamental attribution error, Garrett Hardin, Georg Cantor, George Akerlof, George Gilder, germ theory of disease, Gini coefficient, God and Mammon, Great Leap Forward, greed is good, Gunnar Myrdal, Hans Rosling, Henry Ford's grandson gave labor union leader Walter Reuther a tour of the company’s new, automated factory…, Hernando de Soto, immigration reform, income inequality, interchangeable parts, invention of agriculture, invention of writing, invisible hand, Isaac Newton, Islamic Golden Age, James Watt: steam engine, Jane Jacobs, John Harrison: Longitude, John Maynard Keynes: technological unemployment, Joseph Schumpeter, Kenneth Arrow, knowledge economy, labor-force participation, lake wobegon effect, land reform, liberation theology, lone genius, Lyft, Mahatma Gandhi, Mark Zuckerberg, market fundamentalism, means of production, middle-income trap, military-industrial complex, Naomi Klein, new economy, Nick Bostrom, North Sea oil, Occupy movement, open economy, out of africa, Pareto efficiency, Paul Samuelson, Pax Mongolica, Peace of Westphalia, peak oil, Peter Singer: altruism, Philip Mirowski, Pier Paolo Pasolini, pink-collar, plutocrats, positional goods, profit maximization, profit motive, public intellectual, purchasing power parity, race to the bottom, refrigerator car, rent control, rent-seeking, Republic of Letters, road to serfdom, Robert Gordon, Robert Shiller, Ronald Coase, Scientific racism, Scramble for Africa, Second Machine Age, secular stagnation, seminal paper, Simon Kuznets, Social Responsibility of Business Is to Increase Its Profits, spinning jenny, stakhanovite, Steve Jobs, tacit knowledge, TED Talk, the Cathedral and the Bazaar, The Chicago School, The Market for Lemons, the rule of 72, The Spirit Level, The Wealth of Nations by Adam Smith, Thomas Malthus, Thorstein Veblen, total factor productivity, Toyota Production System, Tragedy of the Commons, transaction costs, transatlantic slave trade, Tyler Cowen, Tyler Cowen: Great Stagnation, uber lyft, union organizing, very high income, wage slave, Washington Consensus, working poor, Yogi Berra

Mill 1859 (2001), pp. 86–87. 43. MacLeod 1998, 2007. The statue ended up in St. Paul’s. 44. Kelly and Ó Gráda (2014) seem to have put paid to one of the older claims about the sources of the turmoil, China to Europe: the Little Ice Age. “Black swan” refers to Nassim Nicholas Taleb’s notion of a highly improbable, and unpredictable, event (Taleb 2007). 45. On perspective, see the astonishing book by Lepenies 2013. Acknowledgments 1. Cavell 2002, p. xvii. Chapter 1 1. When I use the phrase “pretty good” here, as I will often do again, I am referring to the Ohio State political scientist John Mueller’s important book Capitalism, Democracy, and Ralph’s Pretty Good Grocery (1999), which in turn refers to the comically modest marketing in Garrison Keillor’s hometown of Lake Wobegon.

When Wilhelm von Humboldt founded in 1810 the University of Berlin he had no idea that his invention of the modern research university would spread to the masses. What is strange about the modern world, in other words, is its utter economic unpredictability. As Nassim Nicholas Taleb puts it, the Great Enrichment was a “black-swan” event, deeply unpredictable, not to be reduced to a probability distribution with finite variance.6 The premodern world, by contrast, was highly predictable in economic shape. Dukes would go on collecting rents, merchants would go on making modest fortunes from trade, peasants would expect to earn what their fathers and grandfathers and great-grandfathers had earned—unless they could pull ahead a bit by tricking neighbor Nat, the fool, into selling the Nether Field for less than it was worth

Germania. Ed. D. R. Stuart. New York: Macmillan, 1916. Tacitus, Cornelius. 98 CE. The Agricola and the Germania. Trans. H. Mattingly and S. A. Handford. Harmondsworth: Penguin, 1948, 1970. Tacitus, Cornelius. c. 113 CE. Annales. Ed. C. D. Fisher. At http://perseus.tufts.edu/hopper/. Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. Tallis, Raymond. 2011. Review of Terrence Deacon, Incomplete Nature, and Michael S. Gazzanga, Who’s in Charge? Wall Street Journal, November 12. Tanner, Kathryn. 2005. Economy of Grace. Minneapolis: Fortress. Taylor, A.


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Not Working: Where Have All the Good Jobs Gone? by David G. Blanchflower

90 percent rule, active measures, affirmative action, Affordable Care Act / Obamacare, Albert Einstein, bank run, banking crisis, basic income, Bear Stearns, behavioural economics, Berlin Wall, Bernie Madoff, Bernie Sanders, Black Lives Matter, Black Swan, Boris Johnson, Brexit referendum, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Clapham omnibus, collective bargaining, correlation does not imply causation, credit crunch, declining real wages, deindustrialization, Donald Trump, driverless car, estate planning, fake news, Fall of the Berlin Wall, full employment, George Akerlof, gig economy, Gini coefficient, Growth in a Time of Debt, high-speed rail, illegal immigration, income inequality, independent contractor, indoor plumbing, inflation targeting, Jeremy Corbyn, job satisfaction, John Bercow, Kenneth Rogoff, labor-force participation, liquidationism / Banker’s doctrine / the Treasury view, longitudinal study, low interest rates, low skilled workers, manufacturing employment, Mark Zuckerberg, market clearing, Martin Wolf, mass incarceration, meta-analysis, moral hazard, Nate Silver, negative equity, new economy, Northern Rock, obamacare, oil shock, open borders, opioid epidemic / opioid crisis, Own Your Own Home, p-value, Panamax, pension reform, Phillips curve, plutocrats, post-materialism, price stability, prisoner's dilemma, quantitative easing, rent control, Richard Thaler, Robert Shiller, Ronald Coase, selection bias, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, South Sea Bubble, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, trade liberalization, universal basic income, University of East Anglia, urban planning, working poor, working-age population, yield curve

I decided to give a speech to the David Hume Institute at the Royal Society in Edinburgh on April 29, 2008, setting out my thoughts. In the speech I essentially said that recession had arrived in the United States and the UK using the economics of walking about. At the dinner afterward in Edinburgh participants from various financial firms wanted to talk about the possibility that one of Nicholas Taleb’s black swan events was coming to the United States, the UK, and globally. The discussion was prescient. Lots of people, including members of the MPC, said, who could have known recession was coming? The speech is still downloadable from the Bank of England’s website.30 At the start of the speech I said that I am a strong believer in Hume’s own view that we should not seek to solely explain events and behavior with theoretical models; rather, as Hume wrote in 1738 in his Treatise of Human Nature , we should use “experience and observation,” that is, the empirical method.

David Blanchflower, “Pity the Lost Generation,” New Statesman, September 24, 2009. 21. Mark Carney, “The Spectre of Monetarism” (Roscoe Lecture, Liverpool John Moores University, December 5, 2016). 22. Quoted in Susan Page, “10 Years Later We May Not Be Ready for Another Fiscal Crisis,” USA Today, July 18, 2018. 23. Nassim Nicholas Taleb, he of Black Swan fame, has argued that what we have seen is a rebellion against the inner circle of policymakers who are telling us (1) what to do, (2) what to eat, (3) how to speak, (4) how to think, and (5) whom to vote for. He calls them the Intellectual Yet Idiot (IYI). See “The Intellectual Yet Idiot,” Medium.com, September 16, 2016.

Monthly Labor Review 133 (11): 3–15. Summers, L. H. 1991. “The Scientific Illusion in Empirical Macroeconomics.” Scandinavian Journal of Economics 93 (2): 129–48. ———. 2018. “Why the Fed Needs a New Monetary Policy.” Report from the Hutchins Center on Fiscal and Monetary Policy, Brookings, June. Taleb, N. N. 2007. The Black Swan. New York: Random House. Tang, N. K., P. M. Salkovskis, A. Hodges, et al. 2008. “Effects of Mood on Pain Responses and Pain Tolerance: An Experimental Study in Chronic Back Pain Patients.” Pain 138 (2): 392–401. Teater, D. 2014. “Evidence for the Efficiency of Pain Medications.” National Safety Council, Washington, D C . https://www.nsc.org/Portals/0/Documents/RxDrugOverdoseDocuments/Evidence-Efficacy-PainMedications.pdf.


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Nothing But Net by Mark Mahaney

Airbnb, AltaVista, Amazon Web Services, AOL-Time Warner, augmented reality, autonomous vehicles, Big Tech, Black Swan, Burning Man, buy and hold, Cambridge Analytica, Chuck Templeton: OpenTable:, cloud computing, COVID-19, cryptocurrency, discounted cash flows, disintermediation, diversification, don't be evil, Donald Trump, Elon Musk, financial engineering, gamification, gig economy, global pandemic, Google Glasses, Jeff Bezos, John Zimmer (Lyft cofounder), knowledge economy, lockdown, low interest rates, Lyft, Marc Andreessen, Mark Zuckerberg, Mary Meeker, medical malpractice, meme stock, Network effects, PageRank, pets.com, ride hailing / ride sharing, Salesforce, Saturday Night Live, shareholder value, short squeeze, Silicon Valley, Skype, Snapchat, social graph, Steve Jobs, stocks for the long run, subscription business, super pumped, the rule of 72, TikTok, Travis Kalanick, Uber and Lyft, uber lyft

Even stocks that eventually emerged as clear pandemic winners—as great work from home (WFH) plays—including Amazon, Etsy, Netflix, and Shopify—all traded off in that one-month period, with those four stocks correcting as follows: 12%, 39%, 7%, and 30%. The point is that investors can quite easily lose money on their stocks picks—even if they are fundamentally and valuationally sound—because of major market moves. And those moves can be driven by rare, unpredictable shock events. Black swan events, to use the vernacular. Nassim Nicholas Taleb crystalized this phenomenon in his book by the same name. The basic thrust of that book is that the future can’t be predicted. And those who rely on confident forecasts of the future will eventually be cruelly disappointed. It’s a good idea to keep in mind. So there will be blood.

This created issues for investors looking for consistent revenue growth rates in 2020 and in 2021. The “Covid-19 losers” will report impressive revenue recovery or acceleration in 2021, while the “Covid-19 winners” will report alarming revenue deceleration. The key in both circumstances will be to normalize results. The Covid-19 crisis was a black swan event. Just as one should back out one-time unusual expenses and gains from EPS results to get an accurate view of profitability trends, one should normalize for the dramatic impact on growth rates that the pandemic has wrought. There are two ways to do this. One is to look at a two-year stack for revenue growth—add the year-over-year revenue growth of any one quarter to the year-over-year revenue growth of the prior year’s similar quarter, and then track this over a period of time to see if there are any major changes.

Companies with sharply decelerating revenue growth—for example, revenue growth rates that get cut in half over three or four quarters—are likely to work poorly as Longs, especially if that deceleration is driven by market share losses, market saturation, or management mis-execution. When that deceleration is driven by major black swan events like the Covid-19 crisis, it’s a different matter. Conversely, stocks of companies that are successfully executing GCIs (growth curve initiatives) and generating revenue growth acceleration can be good outperformers. Growth curve initiatives in particular are useful for investors because they can provide great catalysts for stock price appreciation.


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The 4-Hour Body: An Uncommon Guide to Rapid Fat-Loss, Incredible Sex, and Becoming Superhuman by Timothy Ferriss

23andMe, airport security, Albert Einstein, Black Swan, Buckminster Fuller, caloric restriction, caloric restriction, carbon footprint, cognitive dissonance, Columbine, confounding variable, correlation does not imply causation, Dean Kamen, game design, Gary Taubes, Gregor Mendel, index card, Kevin Kelly, knowledge economy, language acquisition, life extension, lifelogging, Mahatma Gandhi, messenger bag, microbiome, microdosing, p-value, Paradox of Choice, Parkinson's law, Paul Buchheit, placebo effect, Productivity paradox, publish or perish, radical life extension, Ralph Waldo Emerson, Ray Kurzweil, Recombinant DNA, Richard Feynman, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, Silicon Valley startup, Skype, stem cell, Steve Jobs, sugar pill, survivorship bias, TED Talk, The future is already here, The Theory of the Leisure Class by Thorstein Veblen, Thorstein Veblen, Vilfredo Pareto, wage slave, William of Occam

If something appears to produce a 300% change, you don’t need that many people to show significance, assuming you’re controlling variables. • It is not kosher to combine p-values from multiple experiments to make something more or less believable. That’s another trick of bad scientists and mistake of uninformed journalists. TOOLS AND TRICKS The Black Swan by Nassim Taleb (www.fourhourbody.com/blackswan) Taleb, also author of the bestseller Fooled by Randomness, is the reigning king when it comes to explaining how we fool ourselves and how we can limit the damage. Our instinct to underestimate the occurrence of some events, while overestimating others, is a principal cause of enormous pain.

But it should make you look closely at the studies themselves before accepting the headlines and making behavioral changes in your life. The Goal of this Chapter vs. the Goal of this Book Understanding how to act under conditions of incomplete information is the highest and most urgent human pursuit. —Nassim Taleb, The Black Swan Are the experiments in this book bulletproof? Far from it. All studies are flawed in some respect, often for legitimate cost or ethical considerations. I use myself as a single subject, and (with a few exceptions) I neither randomize nor create a control. Some scientists will, no doubt, have a field day picking these self-experiments apart.

I have absolutely no financial interest in any of the supplements I recommend in this book. If you purchase any supplement from a link in this book, an affiliate commission is sent directly to the nonprofit DonorsChoose.org, which helps public schools in the United States. 5. Philosopher Nassim N. Taleb noted an important difference between language and biology that I’d like to underscore: the former is largely known and the latter is largely unknown. Thus, our 2.5% is not 2.5% of a perfect finite body of knowledge, but the most empirically valuable 2.5% of what we know now. FUNDAMENTALS— FIRST AND FOREMOST THE MINIMUM EFFECTIVE DOSE From Microwaves to Fat-Loss Perfection is achieved, not when there is nothing more to add, but when there is nothing left to take away.


Evidence-Based Technical Analysis: Applying the Scientific Method and Statistical Inference to Trading Signals by David Aronson

Albert Einstein, Andrew Wiles, asset allocation, availability heuristic, backtesting, Black Swan, book value, butter production in bangladesh, buy and hold, capital asset pricing model, cognitive dissonance, compound rate of return, computerized trading, Daniel Kahneman / Amos Tversky, distributed generation, Elliott wave, en.wikipedia.org, equity risk premium, feminist movement, Great Leap Forward, hindsight bias, index fund, invention of the telescope, invisible hand, Long Term Capital Management, managed futures, mental accounting, meta-analysis, p-value, pattern recognition, Paul Samuelson, Ponzi scheme, price anchoring, price stability, quantitative trading / quantitative finance, Ralph Nelson Elliott, random walk, retrograde motion, revision control, risk free rate, risk tolerance, risk-adjusted returns, riskless arbitrage, Robert Shiller, Sharpe ratio, short selling, source of truth, statistical model, stocks for the long run, sugar pill, systematic trading, the scientific method, transfer pricing, unbiased observer, yield curve, Yogi Berra

One final example may help clarify the power of falsifying evidence and the weakness of confirmatory evidence. It is the famous problem of the black swan posed by philosopher John Stuart Mill (1806–1873). Suppose we wish to ascertain the truth of the proposition: ‘All swans are white.’ Mill said, and Popper concurred, that no matter how many white swans have been observed—that is, no matter how voluminous the confirmatory evidence—the proposition’s truth is never proven. A black swan may lurk just around the next corner. This is the limitation of induction that so upset Hume. However, by merely observing a single non-white swan, one may declare with certitude that the proposition is false.

Shleifer in Inefficient Markets: An Introduction to Behavioral Finance (Oxford, UK: Oxford University Press, 2000), 1. A. Shleifer, Inefficient Markets: An Introduction to Behavioral Finance (Oxford, UK: Oxford University Press, 2000), 1. N.N. Taleb, Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life (New York: Texere, 2001). A money manager with no skill whatsoever has a 0.5 probability of beating the market in any given time period (e.g., 1 year). In this experiment, Taleb assumed a universe of money managers with a 0.50 probability of beating the market in a given year. Actually there are three forms of EMH—strong, semistrong, and weak. The strong form contends that no information, including inside information, can be used to beat the market on a risk-adjusted basis.

If the 136 METHODOLOGICAL, PSYCHOLOGICAL, PHILOSOPHICAL, STATISTICAL FOUNDATIONS drives on copper-bracelet days are less than 25 yards better, evidence refuting the claim would be in hand. Limitations of Popper’s Method. As important as Popper’s method of falsification is to modern science, it has been criticized on a number of grounds. Critics assert that Popper’s contention that hypotheses can be definitively falsified overstates matters. Although the observation of a black swan can neatly and logically falsify the universal generalization that all swans are white, the hypotheses of real science are far more complex30 and probabilistic (nonuniversal). They are complex in the sense that a newly proposed hypothesis rests on numerous auxiliary hypotheses that are assumed to be true.


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How to Speak Money: What the Money People Say--And What It Really Means by John Lanchester

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, asset allocation, Basel III, behavioural economics, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Swan, blood diamond, Bretton Woods, BRICs, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Celtic Tiger, central bank independence, collapse of Lehman Brothers, collective bargaining, commoditize, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Dava Sobel, David Graeber, disintermediation, double entry bookkeeping, en.wikipedia.org, estate planning, fear index, financial engineering, financial innovation, Flash crash, forward guidance, Garrett Hardin, Gini coefficient, Glass-Steagall Act, global reserve currency, high net worth, High speed trading, hindsight bias, hype cycle, income inequality, inflation targeting, interest rate swap, inverted yield curve, Isaac Newton, Jaron Lanier, John Perry Barlow, joint-stock company, joint-stock limited liability company, junk bonds, Kodak vs Instagram, Kondratiev cycle, Large Hadron Collider, liquidity trap, London Interbank Offered Rate, London Whale, loss aversion, low interest rates, margin call, McJob, means of production, microcredit, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, negative equity, neoliberal agenda, New Urbanism, Nick Leeson, Nikolai Kondratiev, Nixon shock, Nixon triggered the end of the Bretton Woods system, Northern Rock, offshore financial centre, oil shock, open economy, paradox of thrift, plutocrats, Ponzi scheme, precautionary principle, proprietary trading, purchasing power parity, pushing on a string, quantitative easing, random walk, rent-seeking, reserve currency, Richard Feynman, Right to Buy, road to serfdom, Ronald Reagan, Satoshi Nakamoto, security theater, shareholder value, Silicon Valley, six sigma, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Jobs, survivorship bias, The Chicago School, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, trickle-down economics, two and twenty, Two Sigma, Tyler Cowen, Washington Consensus, wealth creators, working poor, yield curve

.† Black-Scholes The name of the formula that made it possible to create prices in the derivatives markets; before the equation was discovered (or invented, depending on your view of what mathematics does), uncertainties about how probabilities changed made it impossible to create accurate prices for an option over time. Black-Scholes gave a way of mathematically modeling the price of the options, and led to a huge boom in the global market for derivatives. The equation is named after the two men who created it, Fischer Black and Myron Scholes. Black Swan A term coined by the philospher-investor Naseem Nicholas Taleb for an event so rare it doesn’t fit in normal models of statistical probability. As a result, institutions such as banks are grievously unprepared for this kind of very rare event. It is possible that humans are hardwired not to have a good intuitive understanding of these kinds of risks.

(Allen Lane: London, 2013), p. xii. 47See www.gartner.com/technology/research/methodologies/hype-cycle.jsp. 48See cdn.budgetresponsibility.independent.gov.uk/2013-FSR_OBR_web.pdf. 49John Maynard Keynes, The Economic Consequences of the Peace (London: Macmillan, 1919), p. 118. 50See www.forbes.com/sites/luisakroll/2011/04/22/just-how-rich-is-queen-elizabeth-and-her-family/ and www.guardian.co.uk/artanddesign/2006/apr/20/art.monarchy. 51Here’s the actual napkin: web.archive.org/web/20110503200219/http://www.polyconomics.com/gallery/Napkin003.jpg. 52See www.cdc.gov/nchs/data/hus/hus12.pdf#017. 53See media.bloomberg.com/bb/avfile/rJ5Q_k_NsIk8. 54Available at www.marxists.org/archive/marx/works/1852/18th-brumaire/. 55The study, called “When Choice Is Demotivating,” is available at www.columbia.edu/~ss957/articles/Choice_is_Demotivating.pdf. 56See www.theguardian.com/commentisfree/2013/jul/30/obama-grand-bargain-speech-middle-class. 57At www.un.org/millenniumgoals/poverty.shtml. 58See www.businessinsider.com/most-miserable-countries-in-the-world-2013-2?op=1. 59Graham, The Intelligent Investor, p. 108. 60Nassim Nicholas Taleb, http://www.bloomberg.com/news/2010-10-08/taleb-says-crisis-makes-nobel-panel-liable-for-legitimizing-economists.html. 61See www.oecd-berlin.de/charts/PIAAC/. 62See www.ft.com/cms/s/0/cb2bfb08-0e06-11e0-86e9-00144feabdc0.html#axzz2acmNJdUy. 63Burton Malkiel, A Random Walk Down Wall Street (New York: Norton, 2007), p. 119. 64Joseph Stiglitz, “A Tax System Stacked against the 99 Percent,” New York Times, 14 April 2013, available at opinionator.blogs.nytimes.com/2013/04/14/a-tax-system-stacked-against-the-99-percent/?

It was awarded both to the person who created the theory of efficient markets, Eugene Fama, and the man who has mounted the most sustained empirical critique of the theory, Robert Schiller. It’s like awarding a prize both to Galileo, for saying that Earth isn’t the center of the universe, and to Pope Paul V, for saying that it is. Nassim Nicholas Taleb, a particularly trenchant critic of the prize, has argued that investors who lost money in the credit crunch should sue the prize for giving credibility to mistaken mathematical theories of how things should be priced. “I want to make the Nobel accountable. . . . Citizens should sue if they lost their job or business owing to the breakdown in the financial system.” 60 This is a bit like Richard Dawkins’s idea that astrologers should be sued for fraud, in that it’s unlikely to happen but fun to think about.


pages: 529 words: 150,263

The Pandemic Century: One Hundred Years of Panic, Hysteria, and Hubris by Mark Honigsbaum

"World Economic Forum" Davos, Asian financial crisis, biofilm, Black Swan, Boeing 747, clean water, coronavirus, disinformation, Donald Trump, Easter island, en.wikipedia.org, germ theory of disease, global pandemic, indoor plumbing, Louis Pasteur, Mark Zuckerberg, megacity, moral panic, Pearl River Delta, Ronald Reagan, Skype, the built environment, the long tail, trade route, urban renewal, urban sprawl, zoonotic diseases

“Discussing Global Health at Davos,” Wellcome Trust Blog, accessed June 11, 2015, http://blog.wellcome.ac.uk/2015/01/21/discussing-global-health-at-davos/. Black Swan is the title of a 2010 best-selling book by the Lebanese-American essayist Nassim Nicholas Taleb, and refers to an event for which past experience has not prepared us and which, until it occurs, is widely considered to be an impossibility—the paradigm example being that before the discovery of Australia, people in the Old World were convinced that all swans were white because no one had seen a black one before. According to Taleb, a Black Swan has three key elements: “rarity, extreme impact, and retrospective (though not prospective) predictability.” 314 had been 57 percent: Muyembe-Tamfum, “Ebola Virus Outbreaks in Africa.” 314 more than four hundred deaths: WHO, “Ebola virus disease, fact sheet 103, updated August 2015.

No one could have imagined that it would be what we have now.” Peter Piot, director and professor of global health at the London School of Hygiene & Tropical Medicine and a veteran of the original 1976 Yambuku outbreak, was similarly humbled by the experience. “Together with the Swiss Franc this was probably the Black Swan event of the last 12 months,” Piot informed global health policy makers gathered at the World Economic Forum in Davos on January 21, 2015, two weeks after Switzerland’s surprise announcement that it was abandoning the cap on the franc to allow the Swiss currency to float against the Euro. “It was totally unanticipated and we could not have predicted what would happen based on the experience of the previous thirty-seven years.”

See also specific drugs and kinds of drugs drug use, 217–18 Dubos, René, 9, 12, 149, 234, 317, 365 Duesberg, Peter, 225, 226, 403n Dugas, Gaetan, 215–16, 218–20, 233 Duncan, Thomas, 311–12, 413n Duvalier, François, 232 Dylan, Bob, 170, 394–95n East Coast Fever, 129 Ebola, 3, 10, 11–13, 191, 222–23, 226, 232, 257, 277–316, 282, 328, 335, 361, 363–64 airlifting of health care workers and, 299 as Black Swan event, 313 climate and, 316 contagiousness of, 280, 305 control measures for, 289, 290–92, 295–96, 301, 306, 308–10, 313, 314–15 cultural causes and factors, 14, 287–89, 293–94, 296, 308–10, 314 declared a pheic, 297, 304 diagnostic tests for, 282, 301, 314 disparity in treatment of, 299, 300, 302 distrust of foreign medical aid and, 290–92, 364 as EID, 234, 305 evolution of, 315 globalization and, 311–12 identified strains of, 286–87, 301, 314 index case for, 315 late detection of, 315 panic about, 303, 304–5 pharmaceutical companies and, 299, 300, 314–15, 414n population mobility and, 314 possible mutation to aerosol, 305, 314 as potential biowarfare agent, 305, 305n public health campaigns and, 310–11 rumors about, 290–92, 297, 306, 309–10 as security risk rather than urgent public health threat, 314 skewed case data about, 292–93, 301–2, 314 slow response to, 366 social causes, 287–89, 296, 308–10, 314 spillover mechanisms and, 315 symptoms of, 305 transmission of, 8, 284, 290, 290n, 315–16, 364, 364n treatment for, 299, 300, 314–15, 414n vaccines against, 281, 314–15, 414n WHO and, 283–84, 293, 296–97, 299, 301–2, 303–5, 307–9, 311–12, 335–36, 365, 414n Ebola Treatment Units (ETU), 288, 291–93, 300, 306–7, 364 EcoHealth Alliance, 364n ecological equilibriums, 12–13, 143–44 ecological factors, 8–9 ecology, of pathogens, 12 economic factors, 199, 199–200, 227–28, 230–32.


pages: 121 words: 31,813

The Art of Execution: How the World's Best Investors Get It Wrong and Still Make Millions by Lee Freeman-Shor

Alan Greenspan, behavioural economics, Black Swan, buy and hold, Carl Icahn, cognitive bias, collapse of Lehman Brothers, credit crunch, Daniel Kahneman / Amos Tversky, diversified portfolio, family office, I think there is a world market for maybe five computers, index fund, Isaac Newton, Jeff Bezos, Long Term Capital Management, loss aversion, Market Wizards by Jack D. Schwager, Pershing Square Capital Management, Richard Thaler, Robert Shiller, rolodex, Skype, South Sea Bubble, Stanford marshmallow experiment, Steve Jobs, technology bubble, The Wisdom of Crowds, too big to fail, tulip mania, world market for maybe five computers, zero-sum game

Whenever the Rabbits found themselves in a losing position, NaFF-Bee tended to kick in and made them think: “Okay, I have lost money – but my thesis, the story as to why I have invested, is not broken. The share price will turn around and I will still make a lot of money from here.” They were capable of constantly adjusting their mental story and time frame so that the stock always looked attractive. The Rabbits are a great example of how professional investors often react to a black-swan event – an event they did not anticipate and which has negatively impacted their investment story. They tend to dismiss it. There were problems at Vyke – serious ones, as it turned out. By 2011, the firm was delisted. Soon after, it went bust. The investor was lucky to get out at all. 2. I’m in love Primacy error was another issue.

One of my investors bought shares in Cape on 28 September 2007 for £2.79 per share. Cape is considered a global leader in the provision of essential services for the energy and natural resources sectors, ranging from industrial cleaning to painting and coating. It has operations throughout Europe, Africa and Asia. Unfortunately for this investor, a black swan hit in 2008 in the form of the global financial crisis. This led to cyclical companies with debt on their balance sheets being sold off. Cape, being a company with a small market capitalisation, suffered as investors headed for the doors, and lack of liquidity compounded the problem. He eventually sold on 10 March 2009 with the share price standing at just £0.18 per share, representing a loss of 94%.

Many professional investors I know are, deep down, the same. Whenever a Rabbit defended a losing investment it reminded me of Warren Buffett’s famous saying: “forecasts tell you little about the future but a lot about the forecaster.” The Rabbits all carried false passports – they actually originated from that fictitious country that Nassim Taleb calls Extremistan. They were never going to accept their views were wrong. The fact is, the greatest minds on the planet can be wrong. My findings suggest you should expect to be wrong at least half of the time. The very best investment minds are! 7. It’s not my fault Behavioural psychologists have a term for when we blame others or external factors for our misfortunes but take full credit when things go well.


pages: 420 words: 94,064

The Revolution That Wasn't: GameStop, Reddit, and the Fleecing of Small Investors by Spencer Jakab

4chan, activist fund / activist shareholder / activist investor, barriers to entry, behavioural economics, Bernie Madoff, Bernie Sanders, Big Tech, bitcoin, Black Swan, book value, buy and hold, classic study, cloud computing, coronavirus, COVID-19, crowdsourcing, cryptocurrency, data science, deal flow, democratizing finance, diversified portfolio, Dogecoin, Donald Trump, Elon Musk, Everybody Ought to Be Rich, fake news, family office, financial innovation, gamification, global macro, global pandemic, Google Glasses, Google Hangouts, Gordon Gekko, Hacker News, income inequality, index fund, invisible hand, Jeff Bezos, Jim Simons, John Bogle, lockdown, Long Term Capital Management, loss aversion, Marc Andreessen, margin call, Mark Zuckerberg, market bubble, Masayoshi Son, meme stock, Menlo Park, move fast and break things, Myron Scholes, PalmPilot, passive investing, payment for order flow, Pershing Square Capital Management, pets.com, plutocrats, profit maximization, profit motive, race to the bottom, random walk, Reminiscences of a Stock Operator, Renaissance Technologies, Richard Thaler, ride hailing / ride sharing, risk tolerance, road to serfdom, Robinhood: mobile stock trading app, Saturday Night Live, short selling, short squeeze, Silicon Valley, Silicon Valley billionaire, SoftBank, Steve Jobs, TikTok, Tony Hsieh, trickle-down economics, Vanguard fund, Vision Fund, WeWork, zero-sum game

“There is an innate tension in your business model, between democratizing finance, which is a noble calling, and being a conduit to feed fish to sharks.” Another member asked Tenev if he should have seen the trading frenzy coming. Tenev called the meme-stock short squeeze a “black swan” event that had a one in 3.5 million chance of occurring. Maybe the former mathematics PhD student’s numbers were accurate, but a black swan, a term popularized by bestselling author and risk analyst Nassim Nicholas Taleb, is something one simply didn’t anticipate, not just a rarity. Tenev wasn’t a passive observer of the increasingly wild and risky behavior by novices over the past year. His firm and its imitators enabled them by making trading with borrowed money and derivatives free, easy, and even fun—a bit too much fun.

., 133 bear markets, 52, 59, 69, 70, 72, 255 Bear Traps Report, The, 99 Bed Bath & Beyond, 115, 133, 188 behavioral economics, 51, 62, 255 Belfort, Jordan, 118, 148, 217 Benchmark Company, 128 Berkshire Hathaway, 240, 259 Bernanke, Ben, 10 Bessembinder, Hendrik, 243 Best Buy, 130 Betterment, 27, 54, 183, 193, 242, 257, 258, 261 Bezos, Jeff, 89, 160 Bhagavad Gita, 83 Bhatt, Baiju, 23–25, 49, 90, 219 Biden, Joe, 192 big banks, 202, 219–20 Big Money Thinks Small (Tillinghast), 222 Big Short, The (Lewis), 16, 88 Billions, 218 Black, Fischer, 101, 102, 108 BlackBerry, 93, 115, 133, 169, 178, 188, 224 black swan events, 5 blank check firms (SPACs; special purpose acquisition companies), 64–65, 155, 158, 164, 178, 194, 246, 247 Blankfein, Lloyd, 9 Block, Carson, 158 Blockbuster Video, x–xi, 15, 93, 133, 178 Blodget, Henry, 90, 156 Bloomberg, 126, 181 Bloomberg Intelligence, 159 Bloomberg News, 208 Bogle, John, 4, 37, 254 Bolton, Michael, 196, 207 bonds, 58 bots, 163–66, 229–30 Box, 26 Broderick, John, 223 Bronte Capital, 181 Buckingham Strategic Wealth, 62 Buffet, Warren, x, 52–53, 57, 88, 96, 174–75, 183, 236, 240–41, 245, 259 bull markets, 27, 28, 41, 52, 59, 62, 156, 159, 175, 179, 183, 185, 217, 234, 252, 256 Burry, Michael, 16–17, 52, 88–89, 91, 93, 153, 185, 222 Business Insider, 220 ByteDance, 162 C call options, 15–16, 43–44, 68, 99–101, 104–8, 138, 147, 169–70, 216, 227–28 covered calls, 102 Robinhood and, 97–98 Tesla, 103 Carlson, Tucker, 189 Cashin, Art, 240 Casten, Sean, 5, 6 Cato Institute, 14 CBS News, 165 Cecchini, Peter, 103, 228 Center for Monetary and Financial Alternatives, 14 Center for Responsive Politics, 239 Change.org, 120 Chanos, Jim, 77, 84–86, 105, 119, 125, 148, 186, 236 Charles Schwab, 24, 25, 33–35, 49, 50, 59, 66, 70, 139, 200, 202, 234, 236, 245, 257, 259 Charlotte Hornets, 8, 111, 246 Chartered Financial Analyst designation, 18 Chen, Steve, 162 Chewy, 89, 114, 128 Chu, Sandra, 37, 165, 166 Chukumba, Anthony, 128, 147 Churchill Capital IV, 164 Ciara, 64 Cihlar, Rachael, 142–43 Citadel, 8–11, 33, 35, 49, 55, 104, 106–8, 140–41, 146, 178, 189, 198, 202, 206–8, 218, 231 Citron Research, 118, 120, 121, 123, 124 clearinghouses, 187, 203–5 Clubhouse (app), 60, 161–62 Clubhouse Media Group, 60, 161–62 CNBC, 98, 111, 117, 119, 128, 152, 156, 157, 170, 180, 191–92, 240 CNN, 104 Coates, Ta-Nehisi, 160 Code, The (O’Mara), 38 Cohen, Abby Joseph, 254 Cohen, Ryan, 89–90, 154, 221, 222 GameStop and, 90–95, 112–14, 128, 130, 133, 148, 154, 223–24 Cohen, Steven A., 7–9, 110, 146, 161, 197, 218 Cohen, Ted, 89 Colbert, Stephen, 197 college endowments, 77, 245 Comeau, F.

., 118 student loans, xi, 62 Summer, Donna, 9 Sundheim, Daniel, 8 Super Bowl, 19 Super Bowl ads Reddit, 12 Robinhood, 28, 30, 200 Supreme Court, 26 Survey of Consumer Finances, 252 Swedroe, Larry, 62, 66, 238, 247 Szymczak, Kayana, 171–72 T Tabb, Larry, 33–34 Taleb, Nassim Nicholas, 5 taxes, 66–67 TD Ameritrade, 25, 51, 139, 188 technologies, 155 defense of, 40–41 tech stocks, 59, 76, 84, 92, 104–5 Tenev, Vladimir, 30, 49, 67, 89, 161, 183, 187, 194, 197, 200, 201, 204–6, 210, 219, 234, 240 at congressional hearing, 3–6, 11, 14, 32, 40, 65, 206 Robinhood cofounded by, 3, 23–25, 90 Tesla, Nikola, 64 Tesla Motors, 15, 50, 52, 64, 81–82, 91, 92, 98, 103, 105–7, 120, 124, 149, 152, 164, 259 Thaler, Richard, 31 TheStreet, 128 3Com, 84 TikTok, 18, 37, 107, 131, 162–63 Tillinghast, Joel, 221–22 Tinder, 24, 122 Tongji Medical, 60, 161–62 TopStonks.com, 94 trading apps, see smartphone trading apps trading commissions, see commissions “Trading Is Hazardous to Your Wealth” (Barber and Odean), 235 Trading Places, xiv, xv “trading sardines” parable, 184–85 Treasury notes, 58 Trump, Donald, 13, 70 Trump, Donald, Jr., 197 Trust Index, 143 Twitter, 11, 19, 24, 37, 39, 57, 88, 135, 152–54, 157–58, 161–63, 166, 172, 177, 187, 202 Gill’s Forrest Gump post on, 212 Musk’s use of, x, 60, 82, 83, 124, 144, 152–54, 161, 170 SEC and, 167–68 two-day period to settle trades, 204 U Uber, 105 unemployment, 71, 151 Ursus, 85 utilitarian products, 51 V Valeant Pharmaceuticals, 116–17, 120, 125 Van Bavel, Jay, 20, 36 VandaTrack, 139 VanEck, 158–59 Vanguard Group, 8, 32, 254, 257, 259 venture capitalists, 24 Vergara, Salvador, 172–73 Verlaine, Julia-Ambra, 171 Versailles, 9 Virtu Financial, 49, 55, 178, 202, 207, 218 Vision Fund, 105 Volcker Rule, 42 Volkswagen, 77–78, 81 Vrabeck, Kathy, 114, 223 W WallStreetBets, ix–x, xii, xiv, 2, 4, 8, 11, 14, 15, 16, 19, 22–23, 36, 38–40, 43–47, 55, 57, 67, 69, 75–77, 88, 92–95, 97–99, 107, 111, 113, 115, 120, 122, 127–32, 135, 138, 145, 147–49, 152, 157, 159–61, 170–72, 181–82, 188, 190, 192, 193, 205, 213, 216–17, 220–22, 227, 229–31, 238, 243, 255, 259 AMC and, 225–26 “apes together strong” and, 135–36 bots on, 163–66 BTFD on, 69 DeepFuckingValue on, see Gill, Keith as hedge fund, 139 Jeffamazon on, 107–9 Kronos_415 on, 103, 107 Left and, 121–23, 126, 129, 130, 133, 136, 238 membership demographics of, 57 MoonYachts on, 97–98 number of members of, xi, 46, 136–38, 190, 199, 213, 229 Player896 on, 93, 109 proof of trade on, 47 racial slurs on, 190 Robinhood and, 22–23 Senior_Hedgehog on, 72, 73, 76, 79, 92 sharing of losses on, 144 Stonksflyingup on, 95, 109 taken off-line, 190 WeLikeTheStock and, 126, 242 see also GameStop, GameStop short squeeze Wall Street Journal, ix, 30, 50, 52, 61, 84, 118, 128–29, 132, 136, 152, 171, 179, 180, 210, 211, 223, 250, 253 Wall Street Week, 156 Walmart, 26 Wanda, Dalian, 225 Wang Jianlin, 225 warrants, 101 Washington Post, The, 161 Waters, Maxine, 3, 13, 64–65, 76 Wealthfront, 27, 257 wealthiest Americans, 234 wealth inequality, xi, 14, 71–72, 160, 182 Webull, 178, 200 Weissmann, Jordan, 175–76 WeLikeTheStock, 126, 242 West, Jack, 172 Western Digital, 46 WeWork, 105 When Genius Failed (Lowenstein), 260 Where Are the Customers’ Yachts?


pages: 342 words: 72,927

Transport for Humans: Are We Nearly There Yet? by Pete Dyson, Rory Sutherland

Abraham Maslow, Alan Greenspan, autonomous vehicles, barriers to entry, behavioural economics, bitcoin, Black Swan, Boeing 747, BRICs, butterfly effect, car-free, carbon footprint, Charles Babbage, choice architecture, cognitive bias, cognitive load, coronavirus, COVID-19, Crossrail, Daniel Kahneman / Amos Tversky, decarbonisation, demand response, Diane Coyle, digital map, driverless car, Dunning–Kruger effect, Elon Musk, fake news, functional fixedness, gender pay gap, George Akerlof, gig economy, global supply chain, Goodhart's law, Greta Thunberg, Gödel, Escher, Bach, high-speed rail, hive mind, Hyperloop, Induced demand, informal economy, Isaac Newton, Jane Jacobs, lockdown, longitudinal study, loss aversion, low cost airline, Lyft, megaproject, meta-analysis, Network effects, nudge unit, Ocado, overview effect, Paul Samuelson, performance metric, pneumatic tube, RAND corporation, randomized controlled trial, remote working, ride hailing / ride sharing, risk tolerance, Rory Sutherland, Sapir-Whorf hypothesis, selection bias, Skype, smart transportation, social distancing, South Sea Bubble, systems thinking, TED Talk, the map is not the territory, The Market for Lemons, the scientific method, The Wisdom of Crowds, Thomas Malthus, Uber and Lyft, uber lyft, urban planning, Veblen good, When a measure becomes a target, yield management, zero-sum game

When operational data reports on average cycle counts, it gives poor insight into who the users are and no insight at all into why many people stayed home or travelled by other means.5 Figure 22 illustrates the difference between equality and equity. * * * 1 N. N. Taleb. 2007. The Black Swan: The Impact of the Highly Improbable, volume 2. New York: Random House. 2 An interesting thought experiment. Should car parks run by councils discount parking charges for locals? While someone might not mind paying £5 to park in a town they visit just occasionally, being charged £5 on each of your 100 annual visits becomes a great annoyance and imposition.

We learn at school that there are many ways to do this, with the mean, the median and the mode being the three most common. This process of aggregation and averaging means we can make sense of a lot of data, but it also means that a lot of potentially useful information is thrown away. Take the river crossing in this chapter’s epigraph as an example. Taleb is pointing out that while some statistics look appealing, they conceal vital information that really matters to people making real-world decisions. Average depth might be useful for comparing different rivers, but it’s not that helpful if you’re the person stood on the bank deciding whether to cross.

Report, July, Reach Solutions (https://bit.ly/2SGBidw). 20 See Flvyberg on critical realism and the role that social science plays sitting alongside physical and natural sciences. B. Flyvbjerg. 2001. Making Social Science Matter: Why Social Inquiry Fails and How It Can Succeed Again. Cambridge University Press. 21 J. Knobe. 2003. Intentional action and side effects in ordinary language. Analysis 63(3), 190–194. 22 Vincent Graham quoted in N. N. Taleb. 2018. Skin in the Game: Hidden Asymmetries in Daily Life. London: Random House. Table 8. Three examples of counter-intuitive transport (CIT). Smart motorways ‘Stand on both sides’ escalators Low Traffic Neighbourhoods Policy details Variable speed limits (often 50–60 miles per hour) and use of hard shoulder At peak times, requiring standing on both sides; no walking allowed ‘Filtered streets’ reducing through-traffic on residential streets Counter-intuitiveness Go slower to go faster?


pages: 543 words: 153,550

Model Thinker: What You Need to Know to Make Data Work for You by Scott E. Page

Airbnb, Albert Einstein, Alfred Russel Wallace, algorithmic trading, Alvin Roth, assortative mating, behavioural economics, Bernie Madoff, bitcoin, Black Swan, blockchain, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Checklist Manifesto, computer age, corporate governance, correlation does not imply causation, cuban missile crisis, data science, deep learning, deliberate practice, discrete time, distributed ledger, Easter island, en.wikipedia.org, Estimating the Reproducibility of Psychological Science, Everything should be made as simple as possible, experimental economics, first-price auction, Flash crash, Ford Model T, Geoffrey West, Santa Fe Institute, germ theory of disease, Gini coefficient, Higgs boson, High speed trading, impulse control, income inequality, Isaac Newton, John von Neumann, Kenneth Rogoff, knowledge economy, knowledge worker, Long Term Capital Management, loss aversion, low skilled workers, Mark Zuckerberg, market design, meta-analysis, money market fund, multi-armed bandit, Nash equilibrium, natural language processing, Network effects, opioid epidemic / opioid crisis, p-value, Pareto efficiency, pattern recognition, Paul Erdős, Paul Samuelson, phenotype, Phillips curve, power law, pre–internet, prisoner's dilemma, race to the bottom, random walk, randomized controlled trial, Richard Feynman, Richard Thaler, Robert Solow, school choice, scientific management, sealed-bid auction, second-price auction, selection bias, six sigma, social graph, spectrum auction, statistical model, Stephen Hawking, Supply of New York City Cabdrivers, systems thinking, tacit knowledge, The Bell Curve by Richard Herrnstein and Charles Murray, The Great Moderation, the long tail, The Rise and Fall of American Growth, the rule of 72, the scientific method, The Spirit Level, the strength of weak ties, The Wisdom of Crowds, Thomas Malthus, Thorstein Veblen, Tragedy of the Commons, urban sprawl, value at risk, web application, winner-take-all economy, zero-sum game

Suroweicki, James. 2006. The Wisdom of Crowds. New York: Anchor Press. Syverson, Chad. 2007. “Prices, Spatial Competition, and Heterogeneous Producers: An Empirical Test.” Journal of Industrial Economics 55, no. 2: 197–222. Taleb, Nassim. 2001. Fooled by Randomness. New York: Random House. Taleb, Nassim. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. Taleb, Nassim. 2012. Antifragile: Things That Gain from Disorder. New York: Random House. Tassier, Troy. 2013. The Economics of Epidemiology. Amsterdam: Springer. Tetlock, Phillip. 2005. Expert Political Judgment: How Good Is It?

—Shizuo Kakutani In this chapter, we learn two classic models from probability and statistics: the Bernoulli urn model and the random walk model.1 Both models describe random processes even if it may appear that they are producing complex structures. Randomness can be hard to discern without gathering data. We often think we see patterns in election outcomes, stock prices, and scoring in sporting events, but instead, to borrow Nassim Taleb’s lovely phrase, we are being fooled by randomness.2 The Bernoulli urn model describes random processes that produce discrete outcomes, like the flip of a coin or the roll of a die. Developed centuries ago to explain the odds of winning at gambling, it now occupies a central position in probability theory.

His ideas are presented along with beautiful photographs in four self-published books: The Nature of Order, Book 1: The Phenomenon of Life (2002), The Nature of Order, Book 2: The Process of Creating Life (2002), The Nature of Order, Book 3: A Vision of a Living World (2005), and The Nature of Order, Book 4: The Luminous Ground (2004). The second in this sequence is the most germane to the current discussion. Chapter 13: Random Walks 1 See Mlodinow 2009 for an engaging tour of random walks. 2 See Taleb 2001. 3 See Turchin 1998 and Suki and Frey 2017. 4 Note that the law of large numbers says that the mean proportion converges, whereas the central limit theorem tells us that the distribution over the proportion of white balls will be normal. 5 A player who makes 46% of his three-pointers has about a probability of making nine in a row (0.469).


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The Internet Is Not the Answer by Andrew Keen

"World Economic Forum" Davos, 3D printing, A Declaration of the Independence of Cyberspace, Airbnb, AltaVista, Andrew Keen, AOL-Time Warner, augmented reality, Bay Area Rapid Transit, Berlin Wall, Big Tech, bitcoin, Black Swan, Bob Geldof, Boston Dynamics, Burning Man, Cass Sunstein, Charles Babbage, citizen journalism, Clayton Christensen, clean water, cloud computing, collective bargaining, Colonization of Mars, computer age, connected car, creative destruction, cuban missile crisis, data science, David Brooks, decentralized internet, DeepMind, digital capitalism, disintermediation, disruptive innovation, Donald Davies, Downton Abbey, Dr. Strangelove, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, fail fast, Fall of the Berlin Wall, Filter Bubble, Francis Fukuyama: the end of history, Frank Gehry, Frederick Winslow Taylor, frictionless, fulfillment center, full employment, future of work, gentrification, gig economy, global village, Google bus, Google Glasses, Hacker Ethic, happiness index / gross national happiness, holacracy, income inequality, index card, informal economy, information trail, Innovator's Dilemma, Internet of things, Isaac Newton, Jaron Lanier, Jeff Bezos, job automation, John Perry Barlow, Joi Ito, Joseph Schumpeter, Julian Assange, Kevin Kelly, Kevin Roose, Kickstarter, Kiva Systems, Kodak vs Instagram, Lean Startup, libertarian paternalism, lifelogging, Lyft, Marc Andreessen, Mark Zuckerberg, Marshall McLuhan, Martin Wolf, Mary Meeker, Metcalfe’s law, military-industrial complex, move fast and break things, Nate Silver, Neil Armstrong, Nelson Mandela, Network effects, new economy, Nicholas Carr, nonsequential writing, Norbert Wiener, Norman Mailer, Occupy movement, packet switching, PageRank, Panopticon Jeremy Bentham, Patri Friedman, Paul Graham, peer-to-peer, peer-to-peer rental, Peter Thiel, plutocrats, Potemkin village, power law, precariat, pre–internet, printed gun, Project Xanadu, RAND corporation, Ray Kurzweil, reality distortion field, ride hailing / ride sharing, Robert Metcalfe, Robert Solow, San Francisco homelessness, scientific management, Second Machine Age, self-driving car, sharing economy, Sheryl Sandberg, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Skype, smart cities, Snapchat, social web, South of Market, San Francisco, Steve Jobs, Steve Wozniak, Steven Levy, Stewart Brand, subscription business, TaskRabbit, tech bro, tech worker, TechCrunch disrupt, Ted Nelson, telemarketer, The future is already here, The Future of Employment, the long tail, the medium is the message, the new new thing, Thomas L Friedman, Travis Kalanick, Twitter Arab Spring, Tyler Cowen, Tyler Cowen: Great Stagnation, Uber for X, uber lyft, urban planning, Vannevar Bush, warehouse robotics, Whole Earth Catalog, WikiLeaks, winner-take-all economy, work culture , working poor, Y Combinator

the Internet entrepreneur asked, leaning forward on his elbows and staring in his bug-eyed way at Stone.9 There was a nervous silence as Stone looked at Bezos blankly. The “narrative fallacy,” Bezos explained to Stone, is the tendency, particularly of authors, “to turn complex realities” into “easily understandable narratives.” As a fan of Nassim Nicholas Taleb’s The Black Swan, a book that introduced the concept, Jeff Bezos believes that the world—like that map on the wall of Ericsson’s Stockholm office—is so random and chaotic that it can’t be easily summarized (except, of course, as being randomly chaotic). The history of Amazon is too complicated and fortuitous to be squeezed into an understandable narrative, Bezos was warning Stone.

There is Mark Zuckerberg’s Harvard roommate, Chris Hughes, a cofounder of Facebook, who bought the venerable New Republic magazine in 2012. Then there’s Amazon right-libertarian CEO Jeff Bezos, who acquired the equally venerable Washington Post newspaper in 2013, no doubt giving all its reporters a required reading list including The Innovator’s Dilemma and The Black Swan. Meanwhile, multibillionaire eBay founder and chairman Pierre Omidyar has set up his own new Internet publishing empire, First Look Media, and used his massive wealth to hire superstar investigative journalists like Glenn Greenwald and Matt Taibbi to peddle Omidyar’s own left-libertarian agenda.


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How to Fix the Future: Staying Human in the Digital Age by Andrew Keen

"World Economic Forum" Davos, 23andMe, Ada Lovelace, Affordable Care Act / Obamacare, Airbnb, Albert Einstein, AlphaGo, Andrew Keen, Apple's 1984 Super Bowl advert, augmented reality, autonomous vehicles, basic income, Bernie Sanders, Big Tech, bitcoin, Black Swan, blockchain, Brewster Kahle, British Empire, carbon tax, Charles Babbage, computer age, Cornelius Vanderbilt, creative destruction, crowdsourcing, data is the new oil, death from overwork, DeepMind, Demis Hassabis, Didi Chuxing, digital capitalism, digital map, digital rights, disinformation, don't be evil, Donald Trump, driverless car, Edward Snowden, Elon Musk, Erik Brynjolfsson, European colonialism, fake news, Filter Bubble, Firefox, fulfillment center, full employment, future of work, gig economy, global village, income inequality, independent contractor, informal economy, Internet Archive, Internet of things, invisible hand, Isaac Newton, James Watt: steam engine, Jane Jacobs, Jaron Lanier, Jeff Bezos, jimmy wales, job automation, Joi Ito, Kevin Kelly, knowledge economy, Lyft, Marc Andreessen, Marc Benioff, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Mitch Kapor, move fast and break things, Network effects, new economy, Nicholas Carr, Norbert Wiener, OpenAI, Parag Khanna, peer-to-peer, Peter Thiel, plutocrats, post-truth, postindustrial economy, precariat, Ralph Nader, Ray Kurzweil, Recombinant DNA, rent-seeking, ride hailing / ride sharing, Rutger Bregman, Salesforce, Sam Altman, Sand Hill Road, Second Machine Age, self-driving car, sharing economy, Silicon Valley, Silicon Valley billionaire, Silicon Valley ideology, Silicon Valley startup, Skype, smart cities, Snapchat, social graph, software is eating the world, Stephen Hawking, Steve Jobs, Steve Wozniak, subscription business, surveillance capitalism, Susan Wojcicki, tech baron, tech billionaire, tech worker, technological determinism, technoutopianism, The Future of Employment, the High Line, the new new thing, Thomas L Friedman, Tim Cook: Apple, Travis Kalanick, Triangle Shirtwaist Factory, Uber and Lyft, Uber for X, uber lyft, universal basic income, Unsafe at Any Speed, Upton Sinclair, urban planning, WikiLeaks, winner-take-all economy, Y Combinator, Yogi Berra, Zipcar

“It must be the Irish or Scots in me.” Crazy, perhaps, but also smart. In 2006 Lowery—a math quant as well as a minor rock ’n’ roll star—was at a party in Chicago, where he met a guy called Brad Keywell, who was carrying around Nassim Nicholas Taleb’s The Black Swan, the bestselling book about the highly improbable. They got into conversation, and with a Black Swan–like improbability, Lowery ended up consulting for Keywell’s start-up, a special-deals e-commerce website that later become known as Groupon. Paid in stock for his work, Lowery made a million dollars after the Groupon public offering in 2011, which at the time was the biggest internet IPO since Google’s in 2004.


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Year's Best SF 15 by David G. Hartwell; Kathryn Cramer

air freight, Black Swan, disruptive innovation, experimental subject, Future Shock, Georg Cantor, gravity well, job automation, Kuiper Belt, phenotype, precautionary principle, quantum entanglement, semantic web

He is an American and citizen of the world, drawn to events and especially people tipping the present over into the future. His short fiction, now as likely to be fantasy as SF, is one of the finest bodies of work in the genre over the last three decades. “Black Swan” originally appeared in Italian as “Cigno Nero” in the Spring 2009 issue of ROBOT magazine. It was subsequently published in Interzone, which in spite of its small circulation continues to be a major venue for SF and fantasy. The title refers to the concept behind Nassim Nicholas Taleb’s book The Black Swan: The Impact of the Highly Improbable. The ethical journalist protects a confidential source. So I protected ‘Massimo Montaldo,’ although I knew that wasn’t his name.

Surely that was a great loss, but how could anybody guess the extent of that loss? A stroke of genius is a black swan, beyond prediction, beyond expectation. If a black swan never arrives, how on Earth could its absence be guessed? The chasm between Massimo’s version of Italy and my Italy was invisible—yet all encompassing. It was exactly like the stark difference between the man I was now, and the man I’d been one short hour ago. A black swan can never be predicted, expected, or categorized. A black swan, when it arrives, cannot even be recognized as a black swan. When the black swan assaults us, with the wingbeats of some rapist Jupiter, then we must rewrite history.

Ling Yun spared not a glance backwards, but sang a quiet little melody to herself as they headed for the stars. Black Swan BRUCE STERLING Bruce Sterling (www.wired.com/beyond_the_beyond/) lives usually in exotic places in Europe, from which he continues his lifelong habit of cultural commentary. He reports that he “is dividing his atemporal time-zones among Austin, Turin, and Belgrade, and his alternate global identities as Bruce Sterling, Bruno Argento, and Boris Srebro.” “Black Swan” is one of those “Bruno Argento” efforts, written in Torino and originally published in Italy. His most recent novel is SF, The Caryatids (2009).


pages: 571 words: 124,448

Building Habitats on the Moon: Engineering Approaches to Lunar Settlements by Haym Benaroya

3D printing, anti-fragile, Apollo 11, Apollo 13, biofilm, Black Swan, Brownian motion, Buckminster Fuller, carbon-based life, centre right, clean water, Colonization of Mars, Computer Numeric Control, conceptual framework, data acquisition, dual-use technology, Elon Musk, fault tolerance, Gene Kranz, gravity well, inventory management, Johannes Kepler, low earth orbit, Neil Armstrong, orbital mechanics / astrodynamics, performance metric, RAND corporation, restrictive zoning, risk tolerance, Ronald Reagan, stochastic process, tacit knowledge, telepresence, telerobotics, the scientific method, Two Sigma, urban planning, Virgin Galactic, X Prize, zero-sum game

There are many lessons to learn from this accident review: The Nimrod Review: An independent review into the broader issues surrounding the loss of the RAF Nimrod MR2 Aircraft XV230 in Afghanistan in 2006, C. Haddon-Cave, October 28, 2009. 6. Anti-Fragile: Things That Gain From Disorder, N.N. Taleb, Random House, 2012, 2016; See also: The Black Swan - The Impact of the Highly Improbable, N.N. Taleb, Random House 2007, 2016. 7. J. Downer: The Aviation Paradox: Why We Can ‘Know’ Jetliners But Not Reactors, Minerva (2017) 55, pp.229–248. Footnotes 1A heuristic (adjective) pertains to the process of gaining knowledge, enabling a person to discover or learn something

There are hundreds of thousands of plane flights every year, and a crash in one plane does not involve others, so errors remain confined and highly epistemic – whereas globalized economic systems operate as one: errors spread and compound.” Taleb considered the commercial airline industry to be a ‘good’ system since it learns from (small) mistakes, unlike the ‘bad’ economic system that cannot learn, and therefore each mistake leads to a bigger one later. Taleb emphasized the point that an antifragile system is different to a robust system. Antifragile systems learn from mistakes and become stronger. Robust systems, at best, survive mistakes, but remain as they were, no better than before.

They further suggest that this can conflict with the management of the ‘societal risks’ (such as passenger safety) that should be the primary concern of organizations like the FAA.” The two Space Shuttle accidents can be argued to be examples of failed institutions. Refer again to the Nimrod accident review, cited earlier. Taleb also mentioned the effectiveness of the airline industry: ( 6 ) “Every plane crash brings us closer to safety, improves the system, and makes the next flight safer ... these systems learn because they are antifragile and set up to exploit small errors; the same cannot be said of economic crashes, since the economic system is not antifragile the way it is presently built.


pages: 464 words: 139,088

The End of Alchemy: Money, Banking and the Future of the Global Economy by Mervyn King

Alan Greenspan, Andrei Shleifer, Asian financial crisis, asset-backed security, balance sheet recession, bank run, banking crisis, banks create money, behavioural economics, Berlin Wall, Bernie Madoff, Big bang: deregulation of the City of London, bitcoin, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, Bretton Woods, British Empire, business cycle, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, centre right, classic study, collapse of Lehman Brothers, creative destruction, Credit Default Swap, crowdsourcing, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, distributed generation, Doha Development Round, Edmond Halley, Fall of the Berlin Wall, falling living standards, fiat currency, financial engineering, financial innovation, financial intermediation, floating exchange rates, foreign exchange controls, forward guidance, Fractional reserve banking, Francis Fukuyama: the end of history, full employment, German hyperinflation, Glass-Steagall Act, Great Leap Forward, Hyman Minsky, inflation targeting, invisible hand, Japanese asset price bubble, John Maynard Keynes: Economic Possibilities for our Grandchildren, John Meriwether, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, labour market flexibility, large denomination, lateral thinking, liquidity trap, Long Term Capital Management, low interest rates, manufacturing employment, market clearing, Martin Wolf, Mexican peso crisis / tequila crisis, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, Myron Scholes, Nick Leeson, no-fly zone, North Sea oil, Northern Rock, oil shale / tar sands, oil shock, open economy, paradox of thrift, Paul Samuelson, Ponzi scheme, price mechanism, price stability, proprietary trading, purchasing power parity, quantitative easing, rent-seeking, reserve currency, Richard Thaler, rising living standards, Robert Shiller, Robert Solow, Satoshi Nakamoto, savings glut, secular stagnation, seigniorage, stem cell, Steve Jobs, The Great Moderation, the payments system, The Rise and Fall of American Growth, Thomas Malthus, too big to fail, transaction costs, Tyler Cowen: Great Stagnation, yield curve, Yom Kippur War, zero-sum game

. —— (2015), ‘Reflections on Secular Stagnation’, Speech at the Julius-Rabinowitz Center, Princeton University, 19 February 2015. Syed, Matthew (2011), Bounce: The Myth of Talent and the Power of Practice, Fourth Estate, London. Taleb, Nassim (2012), Antifragile: How to Live in a World We Don’t Understand, Allen Lane, London. Taleb, Nassim and M. Blyth (2011), ‘The Black Swan of Cairo’, Foreign Affairs, Vol. 90, No. 3. Tallentyre, S.G. (ed.) (1919), Voltaire in His Letters, G.P. Putnam’s Sons, New York. Taylor, Alan (2015), ‘Credit, Financial Stability, and the Macroeconomy’, Annual Review of Economics, Vol. 7, pp. 309–39.

For other problems, where past experience offers little guide, it is of less use. 22 Kahneman (2011). 23 Gigerenzer and Brighton (2009). 24 Tuckett (2011), p.13. 25 For an example of the latest research into heuristics applied to inter-temporal decisions – that is, decisions that have consequences at different points in time – see Ericson, White, Laibson and Cohen (2015). 26 Knight (1921), p. 227. 27 Gigerenzer and Brighton (2009); Gigerenzer (2014). 28 In his remarkably original (and long) book Antifragile, Nassim Taleb proposes a general approach to embracing the unexpected. The opposite of fragile, he argues, is not robust but antifragile, a system that learns from shocks. As Taleb puts it, ‘A complex system, contrary to what people believe, does not require complicated systems and regulations and intricate policies. On the contrary, the simpler, the better. Complications lead to multiplicative chains of unanticipated effects.’ 29 The standards are set by the so-called Basel Committee, comprising central bank governors and regulators of the group of G20 countries. 30 Aikman et al. (2014).

Their liabilities were known as asset-backed commercial paper (ABCP). 34 Bagehot (1873), p. 49. 35 Calomiris and Haber (2014). 36 The five banks are Royal Bank of Canada, Toronto Dominion Bank, Bank of Nova Scotia, Bank of Montreal, and the Canadian Imperial Bank of Commerce. 37 Although deposit insurance schemes are nominally supported by the banking system as a whole, in times of crisis, as in 2008, the government provides the finance to ensure that depositors can be paid. 38 See the account of the rise and fall of Enron in McLean and Elkind (2004). 4 RADICAL UNCERTAINTY: THE PURPOSE OF FINANCIAL MARKETS 1 Paul Lambert lost his job in February 2015, an event which, despite his own advice, took him by surprise. 2 Gigerenzer (2002, 2015), Gigerenzer and Gray (2011). 3 Financial Times, 13 August 2007; in other words, the moves in prices that he observed were twenty-five times larger than the standard deviation, a measure of dispersion, of the past experience of changes in prices. 4 Syed (2011). 5 Smith (2012). 6 This example as discussed in Gigerenzer (2014). 7 This is an example of the ‘turkey illusion’, originated by Bertrand Russell (1912) and popularised by Taleb and Blyth (2011), in which the turkey mistakes the pattern of being fed each day for a process that will continue for ever, and is caught unawares when, the day before Thanksgiving, the farmer kills rather than feeds the turkey. The failure to understand the context, or the model, of the process leads to a big surprise for the turkey, similar to the surprise many homeowners got when house prices stopped rising. 8 Letter to Frederick William, Prince of Prussia, 28 November 1770, in Tallentyre, S.G., (1919), p. 232. 9 Knight (1921). 10 Malthus (1798), Chapter IX. 7. 11 The Actuarial Profession, a body of life assurance companies and annuity providers, forecast in 1980 that a man who was 60 in that year could expect to live another 20 years.


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Critical: Science and Stories From the Brink of Human Life by Matt Morgan

agricultural Revolution, Atul Gawande, biofilm, Black Swan, Checklist Manifesto, cognitive dissonance, crew resource management, Daniel Kahneman / Amos Tversky, David Strachan, discovery of penicillin, en.wikipedia.org, hygiene hypothesis, job satisfaction, John Snow's cholera map, meta-analysis, personalized medicine, publication bias, randomized controlled trial, Silicon Valley, stem cell, Steve Jobs, sugar pill, traumatic brain injury

In 2007, the term was borrowed by the Lebanese-American author Nassim Nicholas Taleb who uses it in his book, The Black Swan, to describe unpredictable events that have wide-ranging, society-changing effects. He argued that, while humans are poor at specific future predictions, unlikely events will occur and dramatically alter our lives. Overall the likelihood of any one specific black swan event is extremely low, but just like predicting intensive care admissions, the overall likelihood of one occurring at some time is very high. One such event happened on 12 October 2002. In Kuta, on the Indonesian island of Bali, a terrorist explosion killed 202 people, injuring a further 209.

These stories are cyclical but, for the families involved, these are all individual, unpredictable, tragic events – ‘black swan events’. This term describes outlier occurrences, such as the terrorist attacks of 9/11 or even Brexit on a global scale. The etymology behind the term ‘black swan events’ stems from the sixteenth-century belief that all swans were white until the expedition of Willem de Vlamingh in 1697 to the Swan river area in Western Australia – where Rob now lives. While exploring the area, de Vlamingh described a large water bird with black plumage and a bright red bill. It would later be called Cygnus atratus, or the black swan. In 2007, the term was borrowed by the Lebanese-American author Nassim Nicholas Taleb who uses it in his book, The Black Swan, to describe unpredictable events that have wide-ranging, society-changing effects.

Within hours of the tragedy, survivors with severe burns were arriving at the Royal Perth Hospital as the nearest support facility. In total, the hospital cared for twenty-eight patients, many benefiting from the breakthrough ‘spray-on skin’ developed by the pioneering surgeon, Fiona Wood. This black swan event paved the way for the hospital to become a leading burns centre, a place that would give Rob the best chance of survival. As Rob arrived in the emergency department, the smell of burnt flesh lingered at the back of my throat like a beach barbecue. Seeing the severe facial burns, our first concern was the imminent swelling that occurs in the minutes and hours after a heat injury.


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Lying for Money: How Fraud Makes the World Go Round by Daniel Davies

Alan Greenspan, bank run, banking crisis, Bernie Madoff, bitcoin, Black Swan, Bretton Woods, business cycle, business process, collapse of Lehman Brothers, compound rate of return, cryptocurrency, fake it until you make it, financial deregulation, fixed income, Frederick Winslow Taylor, Gordon Gekko, high net worth, illegal immigration, index arbitrage, junk bonds, Michael Milken, multilevel marketing, Nick Leeson, offshore financial centre, Peter Thiel, Ponzi scheme, price mechanism, principal–agent problem, railway mania, Ronald Coase, Ronald Reagan, Savings and loan crisis, scientific management, short selling, social web, South Sea Bubble, tacit knowledge, tail risk, The Great Moderation, the payments system, The Wealth of Nations by Adam Smith, time value of money, vertical integration, web of trust

The unsolicited phone calls saying ‘You may be entitled to compensation’ provided roughly five minutes’ worth of material per capita for the country’s stand-up comedians between about 2009 and 2014. * This way of thinking about things is related to the ‘via negativa’ advocated by Nassim Nicholas Taleb. The tendency of people like the Medicare administrators to think of fraud as a ‘risk’ and in general to assume that it is something that can be managed as if it happened at random is also an example of one of Taleb’s themes; the mismeasure of randomness and the underestimation of events called ‘black swans’ because they don’t fit into the system that’s meant to categorise them. * This extract, and opposite, are from The Uses of Knowledge in Society


pages: 437 words: 132,041

Alex's Adventures in Numberland by Alex Bellos

Andrew Wiles, Antoine Gombaud: Chevalier de Méré, beat the dealer, Black Swan, Black-Scholes formula, Claude Shannon: information theory, computer age, Daniel Kahneman / Amos Tversky, digital rights, Edward Thorp, family office, forensic accounting, game design, Georg Cantor, Henri Poincaré, Isaac Newton, Johannes Kepler, lateral thinking, Myron Scholes, pattern recognition, Paul Erdős, Pierre-Simon Laplace, probability theory / Blaise Pascal / Pierre de Fermat, random walk, Richard Feynman, Rubik’s Cube, SETI@home, Steve Jobs, The Bell Curve by Richard Herrnstein and Charles Murray, traveling salesman, two and twenty

For instance, if the variation in the price of a share were fat-tailed, it would mean there was more of a chance of a dramatic drop, or hike, in price than if the variation were normally distributed. For this reason, it can sometimes be reckless to assume a bell curve over a fat-tailed curve. The economist Nassim Nicholas Taleb’s position in his bestselling book The Black Swan is that we have tended to underestimate the size and importance of the tails in distribution curves. He argues that the bell curve is a historically defective model because it cannot anticipate the occurrence of, or predict the impact of, very rare, extreme events – such as a major scientific discovery like the invention of the internet, or of a terrorist attack like 9/11.

., A Calculating People: The Spread of Numeracy in Early America, University of Chicago Press, IL, 1982 Cohen, I. B., The Triumph of Numbers, W. W. Norton, New York, 2005 Edwards, A.W.F., Pascal’s Arithmetical Triangle, Johns Hopkins University Press, Baltimore, MD, 1987 Kuper S., and Szymanski S., Why England Lose, HarperCollins, London, 2009 Taleb, N.N., The Black Swan, Penguin, London, 2007 CHAPTER ELEVEN While it is still an open question whether the universe is flat, spherical or hyperbolic, the universe is certainly pretty flat; if its curvature does indeed deviate from zero, it does so only very slightly. An irony of testing the universe for its curvature, however, is that it can never be conclusively proved that the universe is flat since there will always be measurement error.


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Double Entry: How the Merchants of Venice Shaped the Modern World - and How Their Invention Could Make or Break the Planet by Jane Gleeson-White

Affordable Care Act / Obamacare, Alan Greenspan, Bernie Madoff, Black Swan, British Empire, business cycle, carbon footprint, corporate governance, credit crunch, double entry bookkeeping, full employment, Gordon Gekko, income inequality, invention of movable type, invention of writing, Islamic Golden Age, Johann Wolfgang von Goethe, Johannes Kepler, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, Mahbub ul Haq, means of production, Naomi Klein, Nelson Mandela, Ponzi scheme, shareholder value, Silicon Valley, Simon Kuznets, source of truth, spice trade, spinning jenny, The Wealth of Nations by Adam Smith, Thomas Malthus, trade route, traveling salesman, upwardly mobile

Today these numbers are manipulated by the powerful wizards of Wall Street, the mathematical geniuses who run the quantitative equity (or ‘quant’) funds, which rely on complex and sophisticated mathematical algorithms to find the glitches and anomalies, the hidden patterns in the markets, the infinitesimal stock movements and trends which yield their fortunes. Nassim Nicholas Taleb, the author of the bestselling book on improbability, The Black Swan, himself a former quant nerd, says of the quant nerds: ‘Most are idiot savants brought to industrial proportions.’ The elite funds run by these ‘idiot savants’ are called ‘black-box’ funds: ‘opaque to outsiders, the boxes contain investment magic understood by only the wizards who conjured it up’.

Crusades 16, 17, 18 currencies 100 da Gama, Vasco 29 da Pisa, Leonardo see Fibonacci da Vinci, Leonardo 7, 27, 32, 47, 60, 65, 80–2, 84, 87–8 Dafforne, Richard 120–3 Dandolo, Enrico 52 Dark Ages dark arts 35, 83 Darwin, Charles 139, 165 Das Kapital (Marx) 165 Dasgupta, Sir Partha 231–2, 237, 238, 239 Datini, Francesco 23–6, 52, 96 de’ Barbari, Jacopo 79 de’ Belfolci, Folco 34, 44 De divina proportione (Pacioli) 66, 82, 84, 85–6 De ludo scacchorum (Pacioli) 87–8 De pictura (Alberti) 60, 117 De quinque corporibus (Piero) 66 De viribus quantitatis (Pacioli) 83 Dean, Graeme W. 203 debit and credit entries 13, 55, 93–4, 100 difficulties 101–2, 122–3 The Decline of the West (Spengler) 167 Defoe, Daniel 127–8 della Francesca, Piero 7, 32, 34, 44–5, 46, 47 mathematical treatises 45, 66, 75 perspective painting 60, 64, 76–7 della Rovere, Giuliano 59 Deloitte, William 145 Deloitte Touche Tohmatsu 217 demand management 185 democracy 15 depreciation 148, 149, 231 Der moderne Kapitalismus (Sombart) 161–2, 171 derivatives market 198, 200 Descartes, René 40 d’Este, Isabella 83, 84, 88 dividends 144, 146, 147, 148, 149, 202 Doge’s Palace 50, 56 Domenici, Pete V. 191 domestic accounts 15–16 double-entry bookkeeping 8, 115, 120, 166 Badoer’s system 55 and capitalism 159–60, 161–75 and decision-making 126–7 earliest surviving 20–1 to improve the mind 125 link with rhetoric 172–3 in modern era 135–6, 249 origins 6–7, 16, 21–2 Pacioli’s definition 92–3 six essential features 20–1 texts on 117, 136 use by Datini 24, 26 Venetian 55, 67, 97–100, 123–7, 131 see also Particularis de computis et scripturis du Pont, Irénée 156 ducats 50, 55 Dürer, Albrecht 79–80 earnings per share (EPS) 219 earth see planet Earth Earth Summit 2012 248–9 East India Company 142 Ebbers, Bernie 213 eco-accounting 249 economic growth 192–3, 225, 227, 233, 242, 245, 248 economics 185 political economy 171 ecosystems 239–40, 247 education 245 Euclid’s Elements 37–8 quadrivium 36, 38, 43 trivium 38, 43 Egypt 35, 36 Eisenstein, Elizabeth 116–17 Elements (Euclid) 37–8, 39, 67, 68, 84 Elgin Marbles 15 Engels, Friedrich 162, 164, 165 England 116, 121, 131, 133, 147 Enron 3, 173, 194–9, 201, 207, 212–13, 214–16, 222–3 environmental accounting 233–8, 245, 247 environmental damage 222–3, 224–5, 232–3, 240, 241–2, 248 equity 21, 243 Erasmus of Rotterdam 68, 84–5 Erlich, Everett 235 Ernst & Young 209, 210, 216, 217 Espeland, Wendy Nelson 172–3 Euclid, Elements 37–8, 39, 67, 68, 75, 84 Eugenius IV, Pope 34 Europe 17, 20, 21, 22–3, 40, 116, 156, 188 accounting associations 153 currencies 25 medieval 26, 70–1 universities 30, 40, 42 vernacular languages 41 European Environment Agency 247 Evans, John H. 173–5 exchange rates 55 externalities 236 factory system 136–7, 138, 139–41, 165, 166 Farolfi ledger 20–1 Fastow, Andrew 213 Fells, J.M. 140–1 Fibonacci 18–19, 75 Fibonacci numbers 19–20 Liber abaci 19–20, 22, 39–41, 63, 66, 67, 75 Financial Accounting Standards Board (US) 206, 213 financial information 203–6 financial statements 5, 143, 144, 146, 200, 205, 214, 215 Fitoussi, Jean-Paul 243–4 Florence 6, 17, 34, 61, 64, 84 abbaco schools 41 bank ledger 20 expansion of commerce 21 Flugel, Thomas 127 Fondaco dei Tedeschi 56 Ford Motor Company 250–1 forests 240, 241 Forster, E.M. 154–5 Forster, Nathaniel 137 France 147 Franciscans 62, 65, 88, 89 Frankfurt Book Fair 95 Frederick II 95 Freiburg 27 Friedman, Milton 221 fund transfers 54 G20 249 Galileo 116, 166 Geijsbeek, John B. 157–8 General Electric 204 The General Theory of Employment (Keynes) 177–8, 179, 183, 185–6 Genoa 6, 17 geometry 36, 37, 38, 63, 73, 75, 81 Germany 56, 68, 183 Gertner, Jon 244 Giovanni, Enrico 244 Giovanni Farolfi & Co. 20 Glitnir 5 Global Biodiversity Outlook 3 (Sukhdev) global financial crisis (2008) 3, 5, 197, 215, 242, 243–4 globalisation, of finance 206–7, 219, 221 Goethe, Johann W. von 128–31 golden ratio 66, 86 Goodwin, Sir Fred 197 governmental accounting 120 grammar 38, 43 Great Depression 177, 178, 179, 180, 227 Greece, ancient 15 mathematics 34–5, 37–8, 61 philosophers 37 green accounting 244 Green Economy Report (Sukhdev) 248–9 Greenspan, Alan 227–8 Gross Domestic Product (GDP) 3, 180–2, 225, 227–30, 232–3, 235, 237–8, 242–3, 246 alternatives to 243–7, 249 failings of 246 Gross National Product (GNP) 1–3, 181, 190, 231 Groves, Eddy 208–9 Guidobaldo, Duke of Urbino 66, 72, 79, 92 Gutenberg, Johann 68, 77 Hagen, Everett 186 Hamilton, Alexander 22 Hammurabi’s Code 14 Haq, Mahbub ul 245 Henry VIII 25 Herodotus 36 HIH 208, 209, 213, 215 Hindu–Arabic arithmetic 34, 41, 62, 67 Hindu–Arabic numerals 18–19, 21, 26–7, 38, 44, 52, 71, 75 Hoenig, Chris 246–7 honeybee pollination 237 Hoover, Herbert 177 Hopwood, Anthony housework, unpaid 229 How to Pay for the War (Keynes) 182–3 Hudson, George 142–3 human capital 231, 248 Human Development Index 245 Humanism (Florence) 43–4, 59–60, 68 Huxley, Aldous 32–3 income measurement 218–19, 226 income statements 5, 202, 203, 219 in ancient Rome 16–17 see also profit and loss accounts India 29, 238 trade/double entry 22 Indonesia 240 industrial revolution 131, 133, 139, 200, 226 inflation 182, 183 information processing 203 Institute of Accountants and Bookkeepers of New York (IABNY) 156, 157 Institute of Chartered Accountants in England and Wales (ICAEW) 153, 205–6 Insull, Samuel 202, 214 Insull Utility Investments 201–2 interest payments 25, 54, 96 international accounting 189, 207 International Accounting Standards Board 207, 214 International Monetary Fund 187 internet 204 inventory 97–9, 101 Islam 22, 39 Italy 6, 7, 16, 19, 28, 167–8 mathematics 34–42, 62 Jerusalem 17 joint stock companies 133, 136, 142, 147, 148 Joint Stock Companies Act 1844 144, 149 Jones, Edward T. 133–6 Jones’ English System of Book-keeping 133–6 journal 99, 100, 101, 103, 118, 203 Julius II, Pope 59 Kennedy, Robert F. 1–3, 229–30, 246 Keynes, John Maynard 8, 176, 177–80, 182–7, 190, 250 Klein, Naomi 221, 233 KPMG 210, 214, 217 Kreuger, Ivar 201 Kreuger & Toll 201 Kublai Khan 18 Kuznets, Simon 2, 177, 180–1, 189, 229 Lanchester, John 4, 198 Landefeld, Steven 228 Landsbanki 5 Latin 35, 41, 63, 71, 72, 73, 74, 116, 220 Lawrence, D.H. 154–5 Lay, Kenneth 195, 196, 197, 212–13, 214 ledgers 20, 93, 99–100, 103–4, 118, 203 14th century 24, 93 Badoer’s 52, 55 balancing 111 closing accounts 111–13 Farolfi 20–1 Lee, G.A. 20–1 Lee, Thomas A. 203 Lehman Brothers 5, 216 Liber abaci (Fibonacci) 19–20, 22, 39–41, 63, 66, 67, 75 limited liability 147–8, 149 Littleton, A.C. 17, 140, 146, 147, 158–9 Liverpool and Manchester Railway 141 Lives of the Most Eminent Painters (Vasari) 46 Living Planet Survey 241–2 Lloyds-HBOS 5 London and North Western Railway 141 Louis XII 82 Machiavelli 30 Mackinnon, Nick 79–80 Madoff, Bernie 142 Madonna and Child with Saints 47 magic 35, 40, 83, 220 Mair, John 118, 125, 130 Malatesta family 33–4, 43 Malthus, Thomas 171 Manchester cotton mill (Engels) 165 Mandela, Nelson 221 Mantua 83, 84 manufacturing 136–41 manuscripts 61, 70, 77 Manutius, Aldus 84 Manzoni, Domenico 118–19 maritime insurance 53 Mark the Evangelist 51–2 marketplace, 15th century 95 markets, impact on politics 221, 228 mark-to-model 213 Marshall Plan 188 Marx, Karl 162, 163–5, 171 mass production 138 mathematics 7, 22, 28, 47, 89–90 ancient Greek 34–5, 37–8, 63 Arab 18–19, 63 and art 85–6 Hindu 39–40 in Italy 34–42 and magic 35, 40, 220 medieval European 63, 251–2 taught as astrology 29–30, 42 universal application 73, 116–17 see also arithmetic Mattessich, Richard 12–13, 186 Maurice, Prince of Orange 120 Maxwell Communications 207 McDonald’s 224 Meade, James 183–4 measurement 23, 218–19 Medici of Florence 26, 64, 80, 168, 171 Mehmed II 57 Mellis, John 121 memorandum (waste book) 99, 101, 118 entering transactions 105–7, 118, 122 merchandise 104 merchant bankers 21, 26, 69 merchants 10, 23, 35, 41 Arab 18–19, 25 Indian 22 Italian 40, 42 Phoenician 36 Venetian 18, 27, 55–6, 69, 94–5, 149 Mesopotamia 12, 13, 14 metaphysics 36–7 Middle Ages 60, 251–2 Milan 30, 34, 47, 61, 80–3 Millennium Ecosystem Assessment 239 Monsanto 222 Monteage, Stephen 124, 126 Morgan, John Pierpont 156 multiplication 74, 75–6 music 36, 38 Naples 50, 61–2 Napoleonic War 145 national accounts 175, 179–88, 190–3, 226–7, 230, 242, 244 natural capital 230–1, 235–9 navigation charts 23 Neighborhood Tree Survey (NY) 241, 244 Netherlands 119, 120 New Deal (Roosevelt) 177, 202 New York Light Company 155 New York Stock Exchange 155, 176, 201 New Zealand 153, 230 Nicholas V, Pope 61 No Royal Road: Luca Pacioli and his times (Taylor) 46–7 Nordhaus, William D. 180, 191, 227 numbers 37, 218, 219–20, 249 Obama, Barack 215, 246 O’Grady, Oswald 208 Oldcastle, Hugh 121, 124 Olmert, Michael 168 One.Tel 208, 209, 213, 215 Organisation for Economic Co-operation and Development (OECD) 190, 242 Organisation for European Economic Co-operation (OEEC) 188 Ormerod, Paul 244 Ottoman Empire 29, 34, 50, 51, 56, 57, 116 Pacioli, Luca 7, 8, 27–8, 34, 35, 161, 219 abbaco mathematics 40, 41 as academic 65, 80, 84, 89 astrologer 42 birth 30 bookkeeping treatise see Particularis de computis and Piero della Francesca 45–6, 47–8 education 43–8 encyclopaedia see Summa de arithmetica on Euclid 84–5 games/tricks 83–4 itinerant teacher 61–6 last years 88–90 and Leonardo da Vinci 80–2, 84 in Milan 80–3 portrait 47, 79–80 and the printing press 66–72 remembered in Sansepolcro 31–2 in Rome 58–61 in Venice 49–58 Paganini, Paganino de 67–8, 71–2, 78, 85 painting 60, 64, 81 Pakistan 224, 245 Paris 23, 50 Particularis de computis et scripturis (Pacioli) 29–30, 78, 90–114, 117–18, 121 and capitalism 163 foundation of modern accounting 30, 75, 131, 157–9, 166 profit calculation 146–7 partnerships 108–9, 147 Patel, Raj 222, , 224 Patient Protection and Affordable Care Act 2010 (US) 246 patronage 59, 67, 70, 72 Paul II, Pope 59 Payen, Jean-Baptiste 139–40 Peking 18 Perspectiva (Witelo) 64 perspective 23, 42, 45, 60, 64, 76–7, 80, 82 Perugia 62–3, 64, 65 Petty, William 180 phi 86 Philip VI 23 philosophy 37, 40 Phoenicians 36 pi 36 Piazza San Marco 56 Pinto cars 250–1 Pisa 6, 17 Pitcher Partners 209, 210, 211–12 plagiarism 63 planet Earth 8–9, 248 accounting for 254 effects of cost-benefit approach 175 health of 224–5, 239 Plato 37 Platonic solids 45, 79, 86 Pliny the Elder 16 pollution 244 Polly Peck International 207 Polo, Marco 18 Ponzi scheme 142 Postlethwayt, Malachy 124 poverty 237, 246, 248, 249 Prato 23–4 Price, Samuel 145 Price Waterhouse 201, 207 PricewaterhouseCoopers 217 principlism 173–4 printing 29, 45, 60, 63, 66–72, 77–8, 90, 115–17 profit 21, 24, 97, 102–3, 127, 146–8, 159, 161, 167, 169 profit and loss accounts 55, 109–11, 112, 166 Pythagoras 35, 36–7 quadrivium 36, 38, 43 quant nerds 220 railways 141–3, 231 Ramsay, Ian 211 Ratdolt, Erhard 68, 116 record-keeping 15 Reformation 33 regulation 206–14, 215 Reid Murray Holdings 207–8 religion 24, 96, 116, 124–5, 220 see also Christian Church; Islam Renaissance 7, 8, 23, 26, 36, 59, 80, 86, 89, 168 art 6, 7, 44, 60, 86 Resurrection (Piero) 32, 33 retained-earnings statements 5, 219 rhetoric 172–3 Rialto 50, 55, 108 Ricardo, David 171 Rich, Jodee 213 Rinieri Fini & Brothers 20 Ripoli Press 70 Robert of Chester 39 Rockefeller, John D. 156 Roman numerals 19, 26–7, 38, 40, 71, 116 Romantic poets, English 131, 154 Rome 58–61, 64, 89 ancient 15–16 Rompiasi family 57, 58, 97 Roosevelt, Franklin D. 177, 178, 181, 202, 214, 215 Rose, Paul L. 71 Ross, Philip 209–10, 211 Rothschild banks 133 Royal Bank of Scotland 173, 197–8 royal estate management 16–17 Rule of Three 38, 41 Russia 153–4 salt 51 Samuelson, Paul A. 191, 227 Sansepolcro 30–4, 43–4, 48, 65, 77, 88–9, 168 Sanuto, Marco 66, 72 Sarbanes, Paul 191 Sarbanes-Oxley Act 2002 212, 215 Sarkozy, Nicolas 242–3, 245 satellite accounts 234–5 scandals/fraud 194–203, 206, 207–12, 215, 225 Schmandt-Besserat, Denise 11–12 Schumpeter, Joseph 169–70 science 35, 37, 40, 42, 67, 76, 116, 166–7 Scotland 27, 147, 150, 153 Scott, Sir Walter 150–1 Scuola di Rialto 58 Second World War 32, 181–5, 187, 227 Securities and Exchange Commission (US) 202–3, 213, 214 Sen, Amartya 243–4, 245 Sforza, Ludovico 80, 81–2, 85, 86, 168 Sikka, Prem 216, 217 Silberman, Mark 213 Simons, James 220 Sistine Chapel 65 Sixtus IV, Pope 59 Skidelsky, Robert 178, 182, 187 Skilling, Jeffrey K. 196, 197, 212, 214 Smith, Adam 171 social sciences 171, 175 socialism 171 Society of Accountants, Edinburgh 152 Sombart, Werner 161–2, 164, 165–6, 166–8, 169, 170, 171–2, 173 Spain 22, 39 Spengler, Oswald 167 Sri Lanka 232–3, 240 State of the USA 246 Stevin, Simon 120, 121, 166, 169 Stiglitz, Joseph 243–4 Stiglitz-Sen-Fitoussi Commission 243–4 stock markets 143 stocktaking 166 Stone, Sir Richard 183–5, 188–9, 190 sub-prime mortgages Sukhdev, Pavan Summa de arithmetica (Pacioli) 57, 61, 62–3, 64, 72–7, 80, 82 printing 66–8, 71–2 publication 32, 77–9 sustainability 232, 243, 249 System of Integrated Environmental and Economic Accounting (UN) 234 System of National Accounts (UN) 189–90, 247 tabulae rationum 16 Taleb, Nassim N. 220 tariffs 63 Tartaglia, Nicholas 76 Taylor, R. Emmett 47 T-column 99 Thomson, Charles Poulett 143 Tiber Valley 30, 31, 33 Timaeus (Plato) 37 time-and-motion studies 157 Toepfer, Klaus 238–9 Tolstoy, Leo 154 town clocks 23 trade 26, 53, 95 transaction analysis 123 transactions 105–7, 118, 122 in manufacturing accounts 140 Treviso Arithmetic 68 trial balances 123–4, 204 trivium 38, 43 unemployment 179, 182, 183, 187 United Kingdom 144, 145, 155, 201 GDP (2008) 3 United Kingdom (Cont.)


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Trend Following: How Great Traders Make Millions in Up or Down Markets by Michael W. Covel

Albert Einstein, Alvin Toffler, Atul Gawande, backtesting, Bear Stearns, beat the dealer, Bernie Madoff, Black Swan, buy and hold, buy low sell high, California energy crisis, capital asset pricing model, Carl Icahn, Clayton Christensen, commodity trading advisor, computerized trading, correlation coefficient, Daniel Kahneman / Amos Tversky, delayed gratification, deliberate practice, diversification, diversified portfolio, Edward Thorp, Elliott wave, Emanuel Derman, Eugene Fama: efficient market hypothesis, Everything should be made as simple as possible, fiat currency, fixed income, Future Shock, game design, global macro, hindsight bias, housing crisis, index fund, Isaac Newton, Jim Simons, John Bogle, John Meriwether, John Nash: game theory, linear programming, Long Term Capital Management, managed futures, mandelbrot fractal, margin call, market bubble, market fundamentalism, market microstructure, Market Wizards by Jack D. Schwager, mental accounting, money market fund, Myron Scholes, Nash equilibrium, new economy, Nick Leeson, Ponzi scheme, prediction markets, random walk, Reminiscences of a Stock Operator, Renaissance Technologies, Richard Feynman, risk tolerance, risk-adjusted returns, risk/return, Robert Shiller, shareholder value, Sharpe ratio, short selling, South Sea Bubble, Stephen Hawking, survivorship bias, systematic trading, Teledyne, the scientific method, Thomas L Friedman, too big to fail, transaction costs, upwardly mobile, value at risk, Vanguard fund, William of Occam, zero-sum game

If you have questions about any trader or track record that I mentioned, feel free to contact me at my blog at www.michaelcovel.com. Abraham Trading Company Annual Performance Breakdown Yearly Statistics Year Return Drawdown 2008 28.77% 2007 19.20% –7.24% 2006 8.93% –9.03% 2005 –10.95% –26.80% (continues) 347 Much of what happens in history comes from “Black Swan dynamics,” very large, sudden, and totally unpredictable “outliers”… Our track record in predicting those events is dismal; yet by some mechanism called the hindsight bias, we think that we understand them… Why are we so bad at understanding this type of uncertainty? It is now the scientific consensus that our risk-avoidance mechanism is not mediated by the cognitive modules of our brain, but rather by the emotional ones.

Houdek, Robert (Bucky) Isaacson, Christian Jund, MaryAnn Kiely, Eddie Kwong, Pete Kyle, Eric Laing, Elina Manevich, Bill Mann, Jon Markman, Michael Martin, John Mauldin, Timothy M. McCann, Lizzie McLoughlin, James Montier, Georgia Nakou, Peter Navarro, Gail Osten, Michael Panzner, Bob Pardo, Baron Robertson, Jim Rogers, Murray Ruggiero, Michael Seneadza, Takaaki Sera, Tom Shanks, Howard Simons, Barry Sims, Aaron Smith, Michael Stephani, Richard Straus, Nassim Nicholas Taleb, Stephen Taub, Ken Tower, Ken Tropin, Tomoko Uchiyama, Thomas Vician, Jr., Robert Webb, Kate Welling, Gabriel Wisdom, Brent Wood, and Patrick L. Young for all of their efforts and support. And thank you to the following publications and writers who generously allowed me to quote from their work: Sol Waksman and Barclay Managed Futures Report, Futures Magazine, Managed Account Reports, Michael Rulle of Graham Capital Management, and Technical Analysis of Stocks and Commodities Magazine.

It is now the scientific consensus that our risk-avoidance mechanism is not mediated by the cognitive modules of our brain, but rather by the emotional ones. This may have made us fit for the Pleistocene era. “Our risk machinery is designed to run away from tigers; it is not designed for the information-laden modern world.” Nassim Nicholas Taleb, Learning to Expect the Unexpected, Edge.org 348 Trend Following (Updated Edition): Learn to Make Millions in Up or Down Markets Yearly Statistics Year Return Drawdown 2004 15.38% –12.25% 2003 74.66% –14.71% 2002 21.51% –11.81% 2001 19.50% –14.11% 2000 13.54% –17.00% 1999 4.76% –15.17% 1998 4.39% –14.34% 1997 10.88% –12.05% 1996 –0.42% –19.69% 1995 6.12% –21.02% 1994 24.22% –10.99% 1993 34.29% –10.50% 1992 –10.50% –26.55% 1991 24.39% –27.01% 1990 89.95% –7.90% 1989 17.81% –31.96% 1988 142.04% –22.12% Month by Month Returns Month by Month Returns Year 1988 1989 1990 Jan 4.17 Feb Mar Apr May Jun Jul Aug –2.59 –8.78 –12.35 32.34 71.99 –2.82 3.45 –8.05 –12.64 13.91 –20.08 38.65 –4.4 16.08 –13.84 Sep Oct Nov Dec –1.98 8.01 17.83 4.51 –7.75 –14.40 10.30 39.52 3.65 1.81 9.45 12.90 –7.90 2.49 20.08 18.54 8.57 –0.36 0.31 –0.09 1991 –15.94 1.30 2.43 –13.70 2.94 2.11 –1.52 –6.33 11.61 16.61 –2.09 33.75 1992 –12.60 –6.00 –5.47 0.31 –5.71 6.58 16.52 1.92 –0.34 –3.31 4.65 –4.54 6.10 4.57 9.24 4.88 –1.22 6.60 –5.28 1.16 –6.59 3.71 12.83 1993 –4.21 349 Appendix B • Performance Guide Month by Month Returns Year Jan Feb Mar Apr 1994 –1.45 –4.16 2.87 –8.39 1995 –7.91 1.24 6.63 1996 –6.85 –13.78 May Jun Jul Aug Sep Oct Nov Dec 15.01 1.47 0.98 –7.38 5.05 5.43 14.24 1.06 4.73 8.22 0.11 –8.75 –5.34 –1.84 –6.67 –0.19 19.11 9.66 14.27 –9.41 1.52 –6.30 –3.34 6.03 16.84 2.45 –6.41 4.95 –5.37 2.10 7.46 –3.33 –11.39 0.94 4.67 1997 5.28 9.15 –1.50 –5.16 –1.32 0.38 4.11 –8.08 1998 –0.90 4.09 –4.45 –4.45 2.61 –2.34 –0.83 23.24 1999 –11.56 13.35 –9.43 7.52 –6.09 –0.68 –0.83 3.12 0.99 –9.57 13.64 8.41 2000 8.02 –9.05 –4.16 5.48 –2.58 –2.19 –5.26 11.76 –4.53 9.51 8.58 –0.18 2001 2.28 2.99 15.17 –10.20 5.13 4.47 –2.58 4.89 9.28 4.13 –13.68 –0.50 2002 –1.73 1.33 –6.62 4.99 1.51 7.75 –3.97 9.86 3.29 –10.19 –1.80 18.41 2003 24.18 13.18 –4.73 2.02 5.59 –7.06 –4.86 –3.54 7.02 22.09 –0.03 8.69 2004 0.47 8.38 0.88 –6.22 2.53 1.37 6.74 –12.25 7.84 4.32 2.79 –0.51 2005 –5.48 –8.95 –1.00 –10.04 1.93 6.66 –12.16 15.74 –5.79 –5.98 14.15 3.96 2006 2.56 –1.53 5.71 2.75 –1.70 –2.32 –5.26 2.72 –1.51 4.08 2.23 1.41 2007 –1.08 –4.00 –2.32 6.50 4.96 3.66 –2.54 –3.73 5.20 4.32 1.16 6.47 2008 6.44 6.57 –0.21 0.34 –0.94 2.04 –4.19 0.08 5.55 4.73 2.02 3.72E E=estimated Campbell & Company, Inc.


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Data and Goliath: The Hidden Battles to Collect Your Data and Control Your World by Bruce Schneier

23andMe, Airbnb, airport security, AltaVista, Anne Wojcicki, AOL-Time Warner, augmented reality, behavioural economics, Benjamin Mako Hill, Black Swan, Boris Johnson, Brewster Kahle, Brian Krebs, call centre, Cass Sunstein, Chelsea Manning, citizen journalism, Citizen Lab, cloud computing, congestion charging, data science, digital rights, disintermediation, drone strike, Eben Moglen, Edward Snowden, end-to-end encryption, Evgeny Morozov, experimental subject, failed state, fault tolerance, Ferguson, Missouri, Filter Bubble, Firefox, friendly fire, Google Chrome, Google Glasses, heat death of the universe, hindsight bias, informal economy, information security, Internet Archive, Internet of things, Jacob Appelbaum, James Bridle, Jaron Lanier, John Gilmore, John Markoff, Julian Assange, Kevin Kelly, Laura Poitras, license plate recognition, lifelogging, linked data, Lyft, Mark Zuckerberg, moral panic, Nash equilibrium, Nate Silver, national security letter, Network effects, Occupy movement, operational security, Panopticon Jeremy Bentham, payday loans, pre–internet, price discrimination, profit motive, race to the bottom, RAND corporation, real-name policy, recommendation engine, RFID, Ross Ulbricht, satellite internet, self-driving car, Shoshana Zuboff, Silicon Valley, Skype, smart cities, smart grid, Snapchat, social graph, software as a service, South China Sea, sparse data, stealth mode startup, Steven Levy, Stuxnet, TaskRabbit, technological determinism, telemarketer, Tim Cook: Apple, transaction costs, Uber and Lyft, uber lyft, undersea cable, unit 8200, urban planning, Wayback Machine, WikiLeaks, workplace surveillance , Yochai Benkler, yottabyte, zero day

There’s a name for that: hindsight bias. The useful bits of data are obvious after the fact, but were only a few items in a sea of millions of irrelevant data bits beforehand. And those data bits could have been assembled to point in a million different directions. the “narrative fallacy”: Nassim Nicholas Taleb (2007), “The narrative fallacy,” in The Black Swan: The Impact of the Highly Improbable, Random House, chap. 6, http://www.fooledbyrandomness.com. The TSA’s no-fly list: Associated Press (2 Feb 2012), “U.S. no-fly list doubles in one year,” USA Today, http://usatoday30.usatoday.com/news/washington/story/2012-02-02/no-fly-list/52926968/1.

Connecting the dots in a coloring book is easy, because they’re all numbered and visible. In real life, the dots can only be recognized after the fact. That doesn’t stop us from demanding to know why the authorities couldn’t connect the dots. The warning signs left by the Fort Hood shooter, the Boston Marathon bombers, and the Isla Vista shooter look obvious in hindsight. Nassim Taleb, an expert on risk engineering, calls this tendency the “narrative fallacy.” Humans are natural storytellers, and the world of stories is much more tidy, predictable, and coherent than reality. Millions of people behave strangely enough to attract the FBI’s notice, and almost all of them are harmless.

Both are required. Neither kind of oversight works without accountability. Those entrusted with power can’t be free to abuse it with impunity; there must be penalties for abuse. Oversight without accountability means that nothing changes, as we’ve learned again and again. Or, as risk analyst Nassim Taleb points out, organizations are less likely to abuse their power when people have skin in the game. It’s easy to say “transparency, oversight, and accountability,” but much harder to make those principles work in practice. Still, we have to try—and I’ll get to how to do that in the next chapter. These three things give us the confidence to trust powerful institutions.


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The Ascent of Money: A Financial History of the World by Niall Ferguson

Admiral Zheng, Alan Greenspan, An Inconvenient Truth, Andrei Shleifer, Asian financial crisis, asset allocation, asset-backed security, Atahualpa, bank run, banking crisis, banks create money, Bear Stearns, Black Monday: stock market crash in 1987, Black Swan, Black-Scholes formula, Bonfire of the Vanities, Bretton Woods, BRICs, British Empire, business cycle, capital asset pricing model, capital controls, Carmen Reinhart, Cass Sunstein, central bank independence, classic study, collateralized debt obligation, colonial exploitation, commoditize, Corn Laws, corporate governance, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, Daniel Kahneman / Amos Tversky, deglobalization, diversification, diversified portfolio, double entry bookkeeping, Edmond Halley, Edward Glaeser, Edward Lloyd's coffeehouse, equity risk premium, financial engineering, financial innovation, financial intermediation, fixed income, floating exchange rates, Fractional reserve banking, Francisco Pizarro, full employment, Future Shock, German hyperinflation, Greenspan put, Herman Kahn, Hernando de Soto, high net worth, hindsight bias, Home mortgage interest deduction, Hyman Minsky, income inequality, information asymmetry, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Isaac Newton, iterative process, James Carville said: "I would like to be reincarnated as the bond market. You can intimidate everybody.", John Meriwether, joint-stock company, joint-stock limited liability company, Joseph Schumpeter, junk bonds, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labour mobility, Landlord’s Game, liberal capitalism, London Interbank Offered Rate, Long Term Capital Management, low interest rates, market bubble, market fundamentalism, means of production, Mikhail Gorbachev, Modern Monetary Theory, Money creation, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, mortgage debt, mortgage tax deduction, Myron Scholes, Naomi Klein, National Debt Clock, negative equity, Nelson Mandela, Nick Bostrom, Nick Leeson, Northern Rock, Parag Khanna, pension reform, price anchoring, price stability, principal–agent problem, probability theory / Blaise Pascal / Pierre de Fermat, profit motive, quantitative hedge fund, RAND corporation, random walk, rent control, rent-seeking, reserve currency, Richard Thaler, risk free rate, Robert Shiller, rolling blackouts, Ronald Reagan, Savings and loan crisis, savings glut, seigniorage, short selling, Silicon Valley, South Sea Bubble, sovereign wealth fund, spice trade, stocks for the long run, structural adjustment programs, subprime mortgage crisis, tail risk, technology bubble, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Bayes, Thomas Malthus, Thorstein Veblen, tontine, too big to fail, transaction costs, two and twenty, undersea cable, value at risk, W. E. B. Du Bois, Washington Consensus, Yom Kippur War

Ursúa, ‘Macroeconomic Crises since 1870’, Brookings Papers on Economic Activity (forthcoming). See also Robert J. Barro, ‘Rare Disasters and Asset Markets in the Twentieth Century’, Harvard University Working Paper (4 December 2005). 5 Nassim Nicholas Taleb, Fooled by Randomness: The Hidden Role of Chance in Life and in the Markets (2nd edn., New York, 2005) 6 Idem, The Black Swan: The Impact of the Highly Improbable (London, 2007). 7 Georges Soros, The New Paradigm for Financial Markets: The Credit Crash of 2008 and What It Means, (New York, 2008), pp. 91 ff. 8 See Frank H. Knight, Risk, Uncertainty and Profit (Boston, 1921). 9 John Maynard Keynes, ‘The General Theory of Employment’, Economic Journal, 51, 2 (1937), p. 214. 10 Daniel Kahneman and Amos Tversky, ‘Prospect Theory: An Analysis of Decision under Risk’, Econometrica, 47, 2 (March 1979), p. 273. 11 Eliezer Yudkowsky, ‘Cognitive Biases Potentially Affecting Judgment of Global Risks’, in Nick Bostrom and Milan Cirkovic (eds.), Global Catastrophic Risks (Oxford University Press, 2008), pp. 91-119.

On the contrary, financial history is a roller-coaster ride of ups and downs, bubbles and busts, manias and panics, shocks and crashes.3 One recent study of the available data for gross domestic product and consumption since 1870 has identified 148 crises in which a country experienced a cumulative decline in GDP of at least 10 per cent and eighty-seven crises in which consumption suffered a fall of comparable magnitude, implying a probability of financial disaster of around 3.6 per cent per year.4 Even today, despite the unprecedented sophistication of our institutions and instruments, Planet Finance remains as vulnerable as ever to crises. It seems that, for all our ingenuity, we are doomed to be ‘fooled by randomness’5 and surprised by ‘black swans’.6 It may even be that we are living through the deflation of a multi-decade ‘super bubble’.7 There are three fundamental reasons for this. The first is that so much about the future - or, rather, futures, since there is never a singular future - lies in the realm of uncertainty, as opposed to calculable risk.

Beveridge Report 204-5 biases 316 bill brokers 299 bill-discounting banks 53 billets d’état 139 bills, commercial 54 bills of exchange (cambium per literas) 43-4 Birmingham & Midland 56 Bismarck, Otto von 202 Black, Fisher 320-22 black box see Black-Scholes model ‘Black’ days 164 black (or grey) economic zones 275 ‘Black Mondays’: 1929: 158 1987 see financial crises black people see African-American people Black-Scholes model (black box) 320-4 Blackstone 337 ‘black swans’ 342 ‘Black Thursday’ 158 Blain, Spencer H., Jr. 256-8 Blankfein, Lloyd 1-2 Bleichroeder (Arnhold & S.) 315 Bloch, Ivan 297 Bloomfield, Arthur 305 Blunt, John 155-6 BNP Paribas 272 Bolivia 2 Bolsheviks 107 bonds and bond markets 64 benefits of 3 bond insurance companies 347 boom 332 bundled mortgages see securitization collateral for 94 compared with mortgages (spread) 241-2 compared with stock markets 124-5 cotton-backed 94-6 crises and defaults 73 definitions 65-9 emerging market bonds see emerging markets face value (par) 73 future of 115-16 government see government bonds history 65-7 importance and power of 67-9 inflation and 105 insurance companies and 198 interest rates 67 liquidity 71 and mortgage rates 68 and pensions 67 perpetual bonds 76 Right- and Left-wing critics of 89-90 Rothschilds and 80-91 and savings institutions 116 and taxes 68 vulnerability of 99 war and 69-75 widening access to 100 bonds and bond markets - cont. and First World War 297 Bonn Consensus 312 bookkeeping 44-5 Borges, Jorge Luis 111 borrowing see credit; debt Boston 266 Botticelli, Sandro 42 ‘bottomry’ 185 Brady, Nicholas 165 Brailsford, Henry Noel 298 Brazil 18. see also BRICs Bretton Woods 305-8 Bretton Woods II 334 Briand, Aristide 159 BRICs (Brazil, Russia, India, China: Big Rapidly Industrializing Countries) 284 Britain: and American Civil War 94-5 banknotes 27 banks and industrialization 48-9 business failures 349 colonies see British Empire compared with France 141 compared with Japan 209-11 cost of living 26 cotton industry 94-6 East Indies trade 134; see also East India Company economy 210-11 finances for Napoleonic wars 80-84 financial ignorance 11-12 financial sector’s contribution to GDP 5 fiscal system 75 foreign investment 287 foreign investment in 76 Glorious Revolution 75-6 house prices and property ownership 10.


pages: 468 words: 124,573

How to Build a Billion Dollar App: Discover the Secrets of the Most Successful Entrepreneurs of Our Time by George Berkowski

Airbnb, Amazon Web Services, Andy Rubin, barriers to entry, Black Swan, business intelligence, call centre, crowdsourcing, deal flow, Dennis Tito, disruptive innovation, Dunbar number, en.wikipedia.org, game design, Google Glasses, Google Hangouts, Google X / Alphabet X, growth hacking, iterative process, Jeff Bezos, Jony Ive, Kickstarter, knowledge worker, Lean Startup, loose coupling, Marc Andreessen, Mark Zuckerberg, Mary Meeker, minimum viable product, MITM: man-in-the-middle, move fast and break things, Network effects, Oculus Rift, Paul Graham, QR code, Ruby on Rails, Salesforce, self-driving car, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, Skype, Snapchat, social graph, SoftBank, software as a service, software is eating the world, Steve Jobs, Steven Levy, subscription business, TechCrunch disrupt, Travis Kalanick, two-pizza team, ubercab, Y Combinator

Great, disruptive entrepreneurs need to understand the capabilities of the technology available to them, the necessity of building new platforms, how to integrate virality into their products and, perhaps most importantly, the power of timing. Don’t get me wrong: there is almost always an element of luck involved (and often significant opportunity cost). But being an entrepreneur is not for the conservative. Nicholas Nassim Taleb (author of The Black Swan) would question the viability of betting on low-probability, high-impact events, what he calls black-swan events, but that is the business of entrepreneurs: manufacturing opportunities that are rare and complex and ultimately yield huge returns. So let’s take a deep dive into the key disruptions delivered by our billion-dollar apps, and expose the critical factors that you need to take into account.

Index Note: page numbers in bold refer to illustrations, page numbers in italics refer to information contained in tables. 99designs.com 111 500 Startups accelerator 136, 160 Accel Partners 3, 158, 261, 304, 321, 336, 383 accelerators 136, 159–60, 160 accountants 164, 316 accounting software 164 acquisition (of users) costs 148–9, 184, 236–7, 275–9, 282 and Facebook 271, 272, 273–4 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 252, 259, 266, 267–74, 275–84, 295–307 and incentive-based networks 270–1 international 295–307 for million dollar apps 136–7, 139, 140–51, 148–9, 153 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 strategy 222–31 for ten-million-dollar apps 211–12, 213, 222–31, 236–7, 248–9 and traditional channels 268–9 and ‘viral’ growth 225, 278, 279–84 zero-user-acquisition cost 278 acquisitions 414–25 buying sustained growth 417–18 by non-tech corporations 418–20 initial public offerings 420–2 Waze 415–16 activation (user) 136, 137, 139, 153–4, 211–12, 213 Acton, Brian 54, 394 addiction, smartphone 30–1 Adler, Micah 269 administrators 409 AdMob 414–15 advertising 43 business model 67, 89–90 costs 140 and Facebook 271, 272, 273–4 mobile 148–9, 268–70, 272–3, 272 mobile social media 272–3, 272 mobile user-acquisition channels 269–70 outdoor 264 shunning of 42, 54–6 video ads 273 aesthetics 131 after product–market fit (APMF) 180 agencies 195–7, 264, 343 ‘agile coaches’ see scrum masters agile software development 192–3, 299, 315, 357, 377 Ahonen, Tomi 45 ‘aiming high’ 40–1 Airbnb 160, 301 alarm features 48 Albion 111 alerts 293 Alexa.com 146 Alibaba 227 ‘ALT tags’ 147 Amazon 7, 29, 131, 164, 227, 276, 366, 374–5, 401, 406 Amazon Web Services 374 American Express 347 Amobee 149 analytics 134–5, 149, 199, 205, 210, 212, 217–21, 294 and cohort analysis 287–8 Flurry 135, 149, 220 function 217–18 Google Analytics 135, 219–20, 345 limitations 284 Localytics 135, 221 and marketing 263 mistakes involving 218–19 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 Andreessen, Marc 180, 418–19 Andreessen Horowitz 72, 80, 180, 321, 383, 385, 418–19 Android (mobile operating system) 6, 23–4, 38, 415 advertising 274 audience size 119 beta testing 202 building apps for 116–22 and international apps 296 in Japan 306 scaling development and engineering 357–8 time spent on 26 and WhatsApp 55 Angel Capital Association 162 angel investors 154, 155–6, 323 AngelList 99, 131, 155, 159, 233 Angry Birds (game) 6, 42, 47, 57–8, 87, 89, 97 and application programming interface 36 delivering delight 207 design 131 funding 321 game in game 348–9 international growth 297–9 platform 117, 118 product extension 356 virality 282 annual offsites 379 annual revenue per user (ARPU) 215, 219, 232, 236 anonymity 43, 56–7 anti-poaching clauses 247 antidilution rights 245 API see application programming interface app descriptions 143 app development billion-dollar app 8, 389–425 CEO advice 406–13 getting acquired 414–25 people 395–405 process 390–1 five-hundred-million-dollar app 325–87 funding 328, 383–7 hiring staff 334–6, 337–40 killer product expansion 350–63 process 326–8 scaling 326, 330–6, 331–2 scaling marketing 341–9 scaling people 364–72, 377–9 scaling process 373–82 scaling product development 357–63 hundred-million-dollar app 251–324 international growth 295–307 process 252–4 product-market fit 255–6 retention of users 286–94 revenue engines 257–66, 275–85 user acquisition 267–74 million-dollar app 81–171 app Version 0.1 123–35 coding 133–4 design 129–33 feedback 127, 134–5 funding 152–60, 161–71, 176, 235–49 identity of the business 106–14 lean companies 115–22 metrics 136–9, 139 process 82–4 startup process 85–105 testing 126–8 user acquisition 140–51 ten-million-dollar app 173–249 growth engine 222–31, 235–49 metrics 211–21 new and improved Version 1.0 198–210 process 174–6 product–market fit 180–97 revenue engine 232–4 venture capital 235–49 app stores 22, 27–8, 33–4 see also Apple App Store; Google Play app-store optimisation (ASO) 142, 225 AppAnnie 205 Apple 19, 20, 31–2, 393 application programming interface 35–6 designers 129 Facetime app 46 iWatch 38–9 profit per employee 402–3 revenue per employee 401 visual voicemail 50 Worldwide Developers Conference (WWDC) 313 see also iPad; iPhone Apple App Store 22, 27, 32–3, 75, 88, 89, 117, 226 finding apps in 140, 141, 142–5 international apps 297–9 making submissions to 152–3 and profit per employee 403 ratings plus comments 204–5 Apple Enterprise Distribution 201–2 application programming interface (API) 35–6, 185, 360, 374 ARPU see annual revenue per user articles of incorporation 169 ASO see app-store optimisation Atari 20 Atomico 3, 261, 321, 383 attribution 227–31 for referrals 230–1 average transaction value (ATV) 214–15, 219, 232, 236, 387 Avis 95 backlinking to yourself 146 ‘bad leavers’ 247 Balsamiq.com 128 Banana Republic 352 bank accounts 164 banking 156–7 Bardin, Noam 43 Barr, Tom 338 Barra, Hugo 120, 306 Baseline Ventures 72 Baudu 226 beauty 131 BeeJiveIM 33 before product–market fit (BPMF) 180 ‘below the fold’ 143 Beluga Linguistics 297 Benchmark 75 benefits 398–400 beta testing 201–4 Betfair 358 Bezos, Jeff 366, 374 Bible apps 45 billion 9–10 Billion-Dollar Club 5 billionaires 9 Bing 226 ‘black-swan’ events 54 BlackBerry 23 Blank, Steve 257 Blogger 41 blood sugar monitoring devices 38 board seats 242, 243–4 board-member election consent 169 Bolt Peters 363 Booking.com 320 Bootstrap 145 Botha, Roelof 76, 77, 80 Box 7, 90, 276, 396–7, 411 brains 10 brainstorming 108 branding 111–13, 143, 263–4 Braun 129 Bregman, Jay xiii, 14–16, 95, 124, 209, 303 bridge loans 323 Brin, Sergey 366 Bring Your Own Infrastructure (BYOI) 17–18 Brougher, Francoise 340 Brown, Donald 44 Brown, Reggie 104–5 Bubble Witch 421 Buffet, Warren 4 build-measure-learn cycle 116 Burbn.com 72–4, 80 business advisors/coaches 103 business analysts 343 business culture 395–8 business goal setting 310–11 business models 67, 83, 87, 88–91, 175, 253, 259, 327, 351–2, 391, 400, 423–4 business success, engines of 183–4, 423–4 Business Wire 150 CAC see Customer Acquisition Cost Cagan, Marty 314 calendars 49 calorie measurement sensors 38 Cambridge Computer Scientists 160 camera feature 48 Camera+ app 48 Candy Crush Saga 6, 47, 87, 89, 131, 278–81, 318, 349, 421–2 card-readers 41–2 cash flow 164 CEOs see Chief Executive Officers CFOs see Chief Financial Officers channels incentive-based networks 270–1 mobile social-media 271–3, 272 mobile user-acquisition 269–70 source attribution 227–31 testing 224–7 traditional 268–9 viral 280–2 charging phones 49–50 Chartboost 149 chauffer hire see Uber app check-ins, location-based 72, 74 Chief Executive Officers (CEOs) 309, 380 advice from 406–13 and the long haul 68 and product centricity 185–6 role 337 Chief Financial Officers (CFOs) 316 Chief Operations Officers (COOs) 309, 326, 337–40, 380 Chief Technology Officers (CTOs) 186–7, 195 Chillingo 298 China 24–5, 146, 226, 306–7 Cisco 402 Clash of Clans (game) 6, 28, 36, 47, 87, 89, 97, 118, 227, 348–9, 398 Clements, Dave 120 Climate Corporation 412, 419 clock features 47 cloud-based software 67, 90 Clover 419 coding 133–4 cofounders 85, 91–105, 188, 191 chemistry 92–3 complementary skills 93 finding 96–9 level of control 94 passion 93–4 red flags 102–3 successful matches 104–5 testing out 100–2 cohort analysis 237, 287–8 Color.com (social photo-sharing) app 113, 255 colour schemes 111 Commodore 20 communication open 412–13 team 194 with users 208–9 Companiesmadesimple.com 163–4 computers 20–1, 29 conferences 97–8, 202, 312–13 confidentiality provisions 244 connectedness 30 ConnectU 105 consumer audience apps 233–4 content, fresh 147 contracts 165–6 convertible loans 163 Cook, Daren 112 cookies 228–9 Coors 348 COOs see Chief Operations Officers Cost Per Acquisition (CPA) 148–9 Cost Per Download (CPD) 148 Costolo, Dick 77–8, 79–80 costs, and user acquisition 148–9, 184, 236–7, 275–9, 282 Crash Bandicoot 33 crawlers 146–7 Cray-1 supercomputer 20 CRM see customer-relationship management CrunchBase 238 CTOs see Chief Technology Officers Customer Acquisition Cost (CAC) 148–9, 184, 236–7, 275–9 customer lifecycle 212–14 customer segments 346–7 customer-centric approach 344 customer-relationship management (CRM) 290–4, 343 customer-support 208–9 Cutright, Alyssa 369 daily active users (DAUs) 142 D’Angelo, Adam 75–6 data 284–5, 345–7 data engineers 284 dating, online 14, 87–8, 101–2, 263 decision making 379–82, 407–8 defining apps 31–4 delegation 407 delight, delivery 205–7 design 82, 129–33, 206–7 responsive 144 designers 132, 189–91, 363, 376 developer meetups 97 developers see engineers/developers development see app development; software development development agencies 196 ‘development sprint’ 192 Devine, Rory 358–9 Digital Sky Technologies 385 directors of finance 316–17 Distimo 205 DLD 97 Doerr, John 164, 310 Doll, Evan 42–3, 105 domain names 109–10 international 146 protection 145–6 Domainnamesoup.com 109 Dorsey, Jack 41, 58, 72, 75–7, 79–80, 104, 112, 215–16, 305, 312, 412–13 ‘double-trigger’ vesting 247 DoubleClick 414 Dow Jones VentureSource 64 down rounds 322–3 downloads, driving 150–1 drag along rights 245 Dribbble.com 132 Dropbox 7, 90, 131, 276 CEO 407, 410–11 funding 160 scaling 336 staff 399 Dunbar, Robin 364–5 Dunbar number 365 e-commerce/marketplace 28–9, 67, 89, 213–14 Chinese 306 Flipboard and 351–2 and revenue engines 232, 233–4, 276 social media generated 271–2 and user retention 288, 289 eBay 7, 28–9, 131, 180, 276 economic models 275 economies of scale 331–2, 331–2 eCourier 15, 95 education 68–9 edX 69 Ek, Daniel 357 Ellis, Sean 182 emails 291–3 emotion effects of smartphones on 29–30, 30 inspiring 223–4 employees see staff employment contracts 246–7 engagement 236, 278, 283 engineering VPs 337, 358–9 engineers/developers 190–1, 194–5, 361–2, 362, 370, 375–7, 405 enterprise 90, 233–4 Entrepreneur First programme 160 entrepreneurs 3–5, 7–8, 65, 262, 393–4, 409, 424 Ericsson 21 Etsy 107, 109, 110, 358 Euclid Analytics 149 Evernote 7, 90, 131, 399 ExactTarget 291 excitement 30 executive assistants 367 Exitround 419 experience 67–8, 264, 397 Fab.com 352 Facebook 7, 10, 26, 32, 48, 76, 226, 394, 422 and acquisition of users 271, 272, 273–4 acquisitions 416–18, 417 agile culture 375 alerts 293 and application programming interface 36 board 180 and business identity 114 and Candy Crush 280–1 Chief Executive Officer 406 cofounders 100–1 and Color 255–6 design 131, 206, 363 Developer Garage 97 driving downloads on 151 and e-commerce decisions 271, 272 and FreeMyApps.com 271 funding 419 and getting your app found 147 and the ‘hacker way’ 375 initial public offering 420–1 and Instagram 29, 51, 76–80, 90, 117 name 110 ‘No-Meeting Wednesday’ 376 product development 187 profit per employee 403 revenue per employee 401 scaling 336 and Snapchat 57 staff 339, 362, 363, 398, 401, 403 and virality 281 WhatsApp purchase 42, 54–6, 416–17, 417 zero-user-acquisition cost 278 and Zynga 279, 281 Facetime app 46 fanatical users 294 feedback 86, 127, 134–5, 182, 192–3, 198–201, 256, 396 loops 204, 211 qualitative 199 quantitative 199 see also analytics Feld, Brad 170, 241 Fenwick and West 168 Fiksu 264, 269–70 finance, VP of 317–18 finding apps 140–8, 148–9 FireEye 90 First Data 419 first impressions 107–10 Fitbit 38 fitness bracelets 38 flat rounds 322–3 Flipboard 6, 29, 42–3, 49, 51, 89–90 and application programming interface 36 Catalogs 351–2 cofounders 105 design 131, 207 funding 164 growth 351–2 platform choice 119 product innovation 351–2 user notifications 292 virality 281 zero-user-acquisition cost 278 Flurry 135, 149, 220 Fontana, Ash 233 Forbes magazine 40 Ford Motors 419 Founder Institute, The 168 founder vesting 166–7, 244 Foursquare 419 France Telecom 13 franchising 354 FreeMyApps.com 270–1 Friedberg, David 412 Froyo (Android mobile software) 7 Fujii, Kiyotaka 304 full service agencies 195–6 functionality 25–6, 45–50, 131 funding 72, 75–6, 84, 87–8, 152–60, 161–71, 179 accelerators 159–60 angel investors 154, 155–6, 323 for billion-dollar apps 391 convertible loans 163 core documents 169–70 for five-hundred-million-dollar apps 328, 383–7 founder vesting 166–7 for hundred-million-dollar apps 254, 258, 316–17, 318–24 incubators 159–60 legal aspects 163–4 and revenue engines 233–4 Series A 234, 238–40, 238, 240, 241, 242–6, 255, 319–21, 385 Series B 238, 241, 253, 260, 284, 319–21, 322, 384 Series C 384 signing a deal 167–8 for ten-million-dollar apps 152–60, 161–71, 176, 235–49 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 game in game 348–9 gaming 42, 47, 318, 355 business model 67, 89 and revenue engines 232, 278–9 and user retention 288, 289 see also specific games Gandhi, Sameer 336 Gartner 271 Gates, Bill 4 general managers (GMs) 300–3 Gladwell, Malcolm 424 Glassdoor 361–2 Global Positioning System (GPS) 23 Gmail 72 GMs see general managers goal setting 40–1, 310–11 Goldberg, Dave 397 Goldman Sachs 385 ‘good leavers’ 247 Google 7, 19, 23, 27, 72, 88, 164, 226 acquisitions 43, 414–16, 418 application programming interface 35–6 beta testing 202 Chief Executive Officer 406–8 developer meetups 97 finding your app on 144, 147 Hangouts app 46 meetings 381–2 mission 404, 408–9 and the OKR framework 310 profit per employee 403, 405 revenue per employee 401, 405 scaling 332 and Snapchat 57 and source attribution 228–9 staff 339, 340, 361–2, 366, 401, 403, 404–5, 412 Thank God It’s Friday (TGIF) meetings 311–12 transparency 413 value 78 Waze app purchase 43 and WhatsApp 56 zero-user-acquisition cost 278 see also Android (mobile operating system) Google Ad Mob 149 Google AdSense 149 Google Analytics 135, 219–20, 345 Google Glass 38–9, 405 Google I/O conference 313 Google Maps 33, 35, 414, 416 Google Now 37 Google Play 88, 89, 117, 120, 226 and beta testing 202 finding apps in 141–5 profit per employee 403 ratings plus comments 204–5 Google Reader 72 Google Ventures 384 Google X 405 Google+ and business identity 114 and virality 281 Google.org 339 GPS see Global Positioning System Graham, Paul 184–5, 211 Graphical User Interface (GUI) 20 Greylock 321, 383 Gross, Bill 406–7, 409–10 Groupon 7, 51–2, 227, 344–5, 419 Grove, Andy 310 growth 267, 308–17 buying sustained 417–18 engines 184, 210, 222–31, 259, 265 and five-hundred-million-dollar apps 329–36 and Friday update meetings 311–12 and goal setting 310–11 and hiring staff 308–9, 411–12 and product and development teams 313–14 and staff conferences 312–13 targets 234, 260 see also acquisition (of users); international growth; scaling Growth Hackers 182 GUI see Graphical User Interface hackathons 99 Haig, Patrick 143 Hailo app xiii–xiv, 5, 36, 89, 386 big data 284–5 branding 112–13 cofounders 94–6 customer segments 346–7 customer-support 208–9 design 131, 132, 133, 206–7 development 123–7, 153–4 Friday update meetings 311 funding 162, 242 goal setting 310 growth 296–7, 299, 302–4, 308–11, 313, 315–17, 329–30, 334–6 hiring staff 308–9, 334–6, 338, 366–7 idea for 14–18 international growth 296, 297, 299, 302–4 market research 182 marketing 263, 264, 268, 270, 273, 341, 347–8 meetings 381 metrics 137–9, 216 name 107 organisational culture 396 platform choice 117, 120, 121 premises xiii–xiv, 177–8, 329–30, 371–2, 386 product development 189, 191, 196 retention 293–4 revenue engine 276 scaling development and engineering 357 scaling people 365–7 scaling process 377 team 258 testing 177–8, 201–4 and user emotionality 224 virality 280, 282 Hangouts app 46 Harris Interactive 31 HasOffers 149 Hay Day 47, 97 head of data 342 Heads Up Display (HUD) 38 heart rate measurement devices 37–8 Hed, Niklas 42 hiring staff 308–9, 334–6, 337–40, 365–70 history of apps 31–2 HMS President xiii–xiv, 177–9, 329, 371, 386 HockeyApp 202 HootSuite 151 Houston, Drew 407, 410–11 HP 180, 402 HTC smartphone 121 HUD see Heads Up Display human universals 44–5 Humedica 419 hyperlinks 147 hypertext markup language (HTML) 147 I/O conference 2013 202 IAd mobile advertising platform 149 IBM 20, 402 icons 143 ideas see ‘thinking big’ identity of the business 86 branding 111–13 identity crises 106–14 names 106–11 websites 113–14 image descriptions 147 in Mobi 149 in-app purchases 28 incentive-based networks 270–1 incorporation 163–4, 179 incubators 159–60 Index Ventures 3, 261 initial public offerings (IPOs) 64, 67–9, 78, 80, 246, 420–2 innovation 404–5 Instagram 6, 29, 48, 51, 67, 71–80, 88–90, 114, 117, 226, 278, 340, 417–18 cofounders 73–4 design 131 funding 75–6, 77–8 X-Pro II 75 zero-user-acquisition cost 278 instant messaging 46 Instantdomainsearch.com 109 integrators 410 Intel 310 intellectual property 165–6, 244, 247 international growth 295–307 Angry Birds 297–9 Hailo 296, 297, 299, 302–4 language tools 297 Square 295, 299, 304–6 strings files 296 Uber 299–302 International Space Station 13 Internet bubble 13 investment see funding iOS software (Apple operating system) 7, 23–4, 46, 75, 104 advertising 274 audience size 119 building apps for 116–22 and international apps 296 scaling development and engineering 357–8 time spent on 26 iPad 42–3, 118–20, 351 iPhone 6, 19, 22–3, 32, 38–9, 183, 351 advertising on 274 camera 48 designing apps for 117–18, 120 finding apps with 145 games 42, 47, 58 and Instagram 74–6 in Japan 306 and Square 104, 306 and Uber 301 user spend 117 and WhatsApp app 54–5 iPod 22 IPOs see initial public offerings Isaacson, Walter 32 iTunes app 22, 47, 88, 143 iTunes U app 69 Ive, Jony 129 iZettle 304 Jackson, Eric 40 Jain, Ankit 142 Japan 227, 304–6 Jawbone Up 38 Jelly Bean (Android mobile software) 7 Jobs, Steve 4, 22, 32, 323, 393, 425 journalists 150–1 Jun, Lei 306 Kalanick, Travis 299–300, 384, 422 Kayak 336 Keret, Samuel 43 Keyhole Inc. 414 keywords 143, 146 Kidd, Greg 104 King.com 349, 421–2 see also Candy Crush Saga KISSmetrics 291 KitKat (Android mobile software) 7 Klein Perkins Caulfield Byers (KPCB) 158, 261, 321, 383 Kontagent 135 Koolen, Kees 320, 339 Korea 30 Koum, Jan 42, 54, 55–6, 154, 321, 394, 416 Kreiger, Mike 73–6 language tools 297 Launchrock.com 113–14, 145, 202 Lawee, David 415 lawyers 103, 169, 170, 242 leadership 410–11 see also Chief Executive Officers; managers lean companies 69, 115–22, 154, 257, 320–1 Lee, Bob 340 legalities 163–70, 242–7, 301 letting go 406–7 Levie, Aaron 396–7, 411 Levinson, Art 32 LeWeb 97 Libin, Phil 399 licensing 356 life experience 67–8, 264 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 Line app 46, 226 Lingo24 297 LinkedIn 97, 226, 406, 408–9 links 147 liquidation preference 242, 243, 245 non-participating 245 Livio 419 loans, convertible 163 Localytics 135, 221 locations 69 logos 111–14 LTV see lifetime value luck 412 Luckey, Palmer 39 LVMH 304 Lyons, Carl 263 Maiden 95 makers 375–7 see also designers; engineers/developers managers 189–90, 300–3, 375–7, 405 MapMyFitness 419 market research 115, 127, 182 marketing data 345–7 and Facebook 271, 272, 273–4 and incentive-based networks 270–1 marketing engineering team 344–5 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 partner marketing 347–8 scaling 341–9 teams 262–6, 337, 342 and traditional channels 268–9 VPs 262–6, 337, 342 marketplace see e-commerce/marketplace MasterCard 347–8 Matrix Partners 283 McClure, Dave 136, 160, 211, 234 McCue, Mike 42–3, 105, 351 McKelvey, Jim 41, 104 ‘me-too’ products 181 Medium 41 Meebo 73 meetings 379–82, 412–13 annual offsite 379 daily check-ins 381 disruptive nature 376–7 Friday update 311–12 meaningful 381–2 monthly strategic 380 quarterly 380 weekly tactical 380 Meetup.com 98–9 Mendelsen, Jason 170 messaging platforms 226 time spent on 46 and user retention 288, 289 metrics 136–9, 139, 211–21 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 average transaction value (ATV) 214–15, 219, 232, 236, 387 consensual 215–16 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 and product-market fit 209–10 referral 137, 138, 139, 153, 154, 211–12, 213, 230–1 revenue 137, 138, 139, 154, 211–12, 213, 214–15, 219, 291 transparency regarding 312 see also acquisition (of users); retention (of users) mice 20 Microsoft application programming interface 35–6 revenue per employee 401 Windows 20, 22, 24 Millennial Media 149 minimum viable product (MVP) 123, 153 MirCorp 13–14 mission 261, 404, 408–9 Mitchell, Jason 51 Mitsui Sumitomo Bank 305 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 MMS see Multimedia Messaging Service Mobile Almanac 45 Mobile App Tracking 230, 231 mobile technology, rise of 19–39 MoMo app 306 Monsanto 419 moonshots 404–5 Moore, Jonathan 200 MoPub 149 Moqups.com 128 Mosaic 180 Motorola 21 Moz.com 143 Mullins, Jacob 419 Multimedia Messaging Service (MMS) 47 Murphy, Bobby 43, 104–5, 152–3 music player apps 47 MVP see Metrics into Action; minimum viable product names 106–11, 142 NameStation.com 108 Nanigans 273–4 National Venture Capital Association 64 native apps 33–4 NDA see Non Disclosure Agreement negotiation 265 Net Promoter Score (NPS) 206, 209 net-adding users 206 Netflix 400 Netscape 164, 180 New Enterprise Associates 385 New York Times news app 32–3, 256 news and alerts feature 48–9 Nextstop 72 Nguyen, Bill 255–6 NHN 227 Nike Fuelband 38 Nintendo Game Boy 47 Nokia 21, 35–6 Non Disclosure Agreement (NDA) 165 noncompetition/non-solicitation provision 244, 247 notifications 291–4 NPS see Net Promoter Score Oculus VR 39 OKR (‘objectives and key results’) framework 310–11, 380 OmniGraffle 128 open-source software 23, 34–5, 185 OpenCourseWare 68–9 operating systems 20–4 see also Android; iOS software operations VPs 337 org charts 258, 309 organisational culture 395–8 O’Tierney, Tristan 104 outsourcing 194–7 ownership and founder vesting 166–7 and funding 155, 156, 161–3, 318 oxygen saturation measurement devices 37–8 Paananen, Ilkka 118–19, 397–8 Page, Larry 4, 23, 382, 404, 407–8 Palantir 90 Palihapitiya, Chamath 187 Pandora 7, 47, 67, 131, 410 pay-before-you-download model 28 pay-per-download (PPD) 225 Payleven 304 payment systems 7, 33–4, 227, 304, 305 see also Square app PayPal 7, 227, 304, 305 Pepsi 196 Perka 419 perks 398–400 perseverance 67, 394, 410 personal computers (PCs) 29 perspiration measurement devices 38 Pet Rescue Saga 349, 421 Petrov, Alex 369 phablets 7 Pham, Peter 255 PhoneSaber 33 Photoshop 128 PIN technology 305 Pincus, Mark 311 Pinterest app 48, 226 and business identity 114 and e-commerce decisions 271, 272 and getting your app found 147 name 107 and virality 281 Pishevar, Shervin 300 pivoting 73–4 population, global 9–10 portfolio companies 261–2 PowerPoint 128 PPD see pay-per-download preferential return 243 premises 370–2 preparation 412 press kits 148, 150 press releases 150 Preuss, Dom 98 privacy issues 43, 56–7 private vehicle hire see Uber pro-rata rights 242, 243 producers 409 product chunks 360 product development scaling 357–63 scope 199 team building for 188–91 and team location 193–4 and vision 186–8, 191 see also app development; testing product expansion 350–63 product extension 354 product managers 189–90, 405 product-centricity 185–6, 314, 360 product-market fit 9, 180–97, 235–6, 248, 256–7 measurement 209–10, 212, 286–8 profit 267, 320, 342 profit margin 258–9, 318, 321 profit per employee 402–4, 403, 405 profitability 260, 277, 400 Project Loon 405 proms 12 proto.io tool 133 prototype apps 86, 174 app Version 0.1 123–35, 174 new and improved Version 1.0 198–210 rapid-design prototyping 132–3 PRWeb 150 PSP 47 psychological effects of smartphones 29–30, 30 pttrns.com 131 public-relations agencies 343 publicity 150–1, 225, 313 putting metrics into action 138–9 Puzzles and Dragons 47, 131 QlikView 221, 284–5 QQ 307 quality assurance (QA) 190–1, 196 Quora 76 QZone 307 Rabois, Keith 368, 369 Rakuten 227 Rams, Dieter 129 rapid-design prototyping 132–3 ratings plus comments 204–5 Red Bull 223 redemption codes 230 referrals (user) 137, 138, 139, 153, 154, 211–12, 213 attribution for referrals 230–1 referral codes 230 religious apps 45 remuneration 361–2, 362, 363 Renault 13 restated certification 169 retention (of users) 136–9, 153, 154 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 286–94, 288–9 measurement 286–8 for ten-million-dollar apps 206, 211–12, 213, 278 revenue 137–8, 139, 154, 211–12, 213, 214–15, 219, 236, 239–40, 267, 291, 331–2, 341–2, 354 revenue engines 184, 210, 232–4, 257–66, 265, 275–85 revenue per employee 400–2, 402, 405 revenue streams 27–9 Ries, Eric, The Lean Startup 115–16 Rockefeller, John D. 9 Rocket Internet 304 Rolando 33 Rosenberg, Jonathan 413 Rovio 58, 97, 118, 297–9, 318, 320–1, 336, 354, 409 see also Angry Birds Rowghani, Ali 77 Rubin, Andy 23 Runa 419 SaaS see software as a service Sacca, Chris 75–6 sacrifice 86–7 Safari Web browser 32 salaries 361–2, 362, 363 sales VPs 337 Salesforce 291 Samsung 23 Galaxy Gear smartwatch 38 smartphones 121 Sandberg, Sheryl 4, 100–1, 339, 397 SAP 304 scaling 259, 308, 312, 323–4, 326, 330–6, 331–2, 384–5 decision making 379–81 international growth 295–307 marketing 341–9 and organisational culture 396–8 people 338–9, 364–72 premature 334–5 process 373–82 product development and engineering 357–63 and product innovation 350–6 reasons for 333–4 skill set for 335–6 Schmidt, Eric 120 scope 199 screenshots 131, 144, 206 scrum masters (‘agile coaches’) 315, 359, 360 search functions 49 organic 141–2, 141, 145 search-engine optimisation (SEO) 142, 145–8, 225 Sedo.com 109 Seed Fund 136 Seedcamp 160 Sega Game Gear 47 segmentation 220, 287, 290, 346–7 self-empowered squads/units 360 SEO see search-engine optimisation Sequoia Capital 76, 77–80, 158, 255, 321, 383, 385 Series A funding 234, 238–40, 238, 240, 241, 242–6, 255, 261, 262, 319–21, 385 Series B funding 238, 241, 253, 260, 319–21, 322, 384 Series C funding 384 Series Seed documents 168 Sesar, Steven 263 sex, smartphone use during 31 Shabtai, Ehud 43 shares 156, 166–8, 244 ‘sharing big’ 51–2, 52 Shinar, Amir 43 Shopzilla 263 Short Message Service (SMS) 21, 46–7 Silicon Valley 71–4, 77, 79, 99, 162, 168, 180, 184, 255, 340, 361, 411, 422 Sina 227 sitemaps 146–7 skills sets complementary 93 diverse 409–10 for scaling 335–6 Skok, David 283 Skype app 7, 46, 111, 200–1, 226, 357, 419 Sleep Cycle app 48 Smartling 297 smartwatches 7, 38–9 SMS see Short Message Service Snapchat app 6, 43, 46, 56–7, 88, 89, 223, 226, 416, 418 cofounders 104–5 design 131 funding 152–3, 307, 320 name 107 platform 117 staff 340 valuations 333 virality 280, 283 zero-user-acquisition cost 278 social magazines 42–3 see also Flipboard social media 48 driving downloads through 151 and getting your app found 147 mobile channels 271–3, 272 and user retention 288, 289 Sofa 363 SoftBank 227 software development agile 192–3, 299, 315, 357, 377 outsourcing 194–5 see also app development software as a service (SaaS) 67, 90, 208, 214, 233, 276–7 Somerset House 329–30, 371 Sony 21, 47 SoundCloud 358 source attribution 227–31 space tourism 13–14 speech-to-text technology 50 speed 20 Spiegel, Evan 43, 56–7, 104–5, 152–3 Spinvox 50 Splunk 90 Spotify app 47, 357–8 SQL 284 Square app 6, 41–2, 58–9, 87, 89, 333, 350 branding 112 Chief Executive Officer 412–13 cofounders 104 design 131, 363 funding 320–1 international growth 295, 299, 304–6 marketing 348 metrics 215–16 name 107, 110 product–market fit 183 revenue engine 276 scaling people 367–8 scaling product innovation 352–3 staff 340, 367–8 transparency 312 virality 282 Square Cash 353 Square Market 353 Square Register 350, 352–3 Square Wallet 348, 350, 353 Squareup.com 144 staff at billion-dollar app scale 395–405, 423 attracting the best 91 benefits 398–400 conferences 312–13 conflict 334, 378 employee agreements 244 employee legals 246–7 employee option pool 244 employee-feedback systems 378 firing 370, 378 hiring 308–9, 334–6, 411–12 induction programmes 370 investment in 360 mistakes 369–70, 411–12 and premises 370–2 profit per employee 402–4, 403 revenue per employee 400–2, 402 reviews 370 scaling people 364–72, 377–9 scrum masters 315, 359, 360 training programmes 370 see also cofounders; specific job roles; teams Staples 419 Starbucks 338, 348 startup weekends 98 startups, technology difficulties of building 63–80 failure 63–5, 73–4 identity 106–14 lean 115–22, 154 process 82–4, 85–105 secrets of success 66–9 step sensors 38 stock markets 420–1 straplines 111 strings files 296 Stripe 160 style 111 subscriptions 90 success, engines of 183–4, 423–4 SumUp 304 Supercell 28, 47, 97, 118–19, 318, 336, 397–8, 401, 403 see also Clash of Clans; Hay Day SurveyMonkey 397 surveys 206, 209 synapses 10 Systrom, Kevin 71–80 tablets 7 Tableau Software 90 Taleb, Nicholas Nassim 54 Tamir, Diana 51 Tap Tap Revolution (game) 42 Target 419 taxation 164 taxi hailing apps see Hailo app TaxiLight 16 team builders 264 team building 188–91 teams 82, 174, 252, 390 complementary people 409–10 for five-hundred-million-dollar apps 326, 342–5, 357–63, 374, 386 growth 313–14, 326, 342–4 for hundred-million-dollar apps 258–61 located in one place 193–4 marketing 262–6, 342–4 marketing engineering 344–5 product development and engineering 357–63 ‘two-pizza’ 374 TechCrunch Disrupt 97, 99 technology conferences 97–8, 202, 312–13 Techstars 159, 160, 168 Tencent 307 Tencent QQ 226 term sheets 168, 169, 170, 243–4 testing 126–8, 177–8, 187–8, 192–3, 199–201 beta 201–4 channels 224–7 text messaging 21 unlimited packages 42 see also Short Message Service ‘thinking big’ 40–59, 82, 85 big problem solutions 41–3 disruptive ideas 53–9 human universals 44–5 sharing big 51–2, 52 smartphones uses 45–50 Thoughtworks 196 time, spent checking smartphones 25–6, 26, 45–50 Tito, Dennis 13 tone of voice 111 top-down approaches 311 traction 233, 252 traffic information apps 43 traffic trackers 146 translation 296–7 transparency 311–12, 412–13 Trilogy 13 Tumblr 110, 226, 399, 418 Twitter 41, 48, 54, 72, 226, 394 acquisitions 418 and application programming interface 36 and Bootstrap 145 and business identity 114 delivering delight 206 and e-commerce decisions 272 and FreeMyApps.com 271 funding 419, 421 and getting your app found 147 initial public offering 421 and Instagram 51, 76–7, 79–80 name 110 and virality 281 ‘two-pizza’ teams 374 Uber 6, 36, 87, 89, 333, 350 and attribution for referrals 231 design 131 funding 320, 384, 422 international growth 295, 299–302 name 107, 110 revenue engine 276 revenue per employee 401 scaling product innovation 355–6 staff 339, 399 user notifications 292 virality 280 Under Armour 419 Union Square Ventures (USV) 3, 158, 242, 261, 262, 288, 321, 323, 377, 383 unique propositions 198 UnitedHealth Group 419 URLs 110 ‘user experience’ (UX) experts 190 user journeys 127–8, 213–14 user notifications 291–4 user stories 193 users 83, 175, 252, 327, 390 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 communication with 208–9 definition 137 emotional response of 223–4 fanatical 294 finding apps 140–8 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291 metrics 136–9 net-adding of 206 ratings plus comments 204–5 referrals 137, 138, 139, 153, 154, 211–12, 213, 230–1 target 83, 115, 127 wants 180–97 see also acquisition (of users); retention (of users) Usertesting.com 200–1 USV see Union Square Ventures valuations 83, 161–3, 175, 237–8, 238, 253, 318, 319, 322, 327, 333, 391 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 Viber app 6, 46, 1341 video calls 46, 47 viral coefficient 282–4 ‘viral’ growth 225, 278, 279–84 Communication virality 281 and cycle time 283–4 incentivised virality 280–1 inherent virality 280 measurement 282–4 social-network virality 281 word-of-mouth virality 281–2 virtual reality 39 vision 261, 393–4, 408–9, 414, 415 voice calls 46–7 voice-over-Internet protocol (VOIP) 46 voicemail 50 Wall Street Journal 43, 55 warranties 246 Waze app 6, 43, 97 acquisition 415–16 design 131 name 107 zero-user-acquisition cost 278 web browsing 49 Web Summit 97 websites 113–14, 144–8 WebTranslateIt (WTI) 297 WeChat app 46, 226, 306 Weibo 48 Weiner, Jeff 408–9 Wellington Partners 4 Weskamp, Marcos 207 Westergren, Tim 410 WhatsApp 6, 42, 46, 54–6, 87, 90, 226, 394 acquisition 42, 54–6, 416, 416–17, 417 cofounders 96 design 131, 144 funding 154, 320–1 platform 117–18 valuations 333 virality 280 White, Emily 340 Williams, Evan 41, 65 Williams, Rich 344 Wilson, Fred 110, 242, 288, 323, 377 Windows (Microsoft) 20–1, 22, 24, 24 Winklevoss twins 105 wireframes 127–8 Woolley, Caspar 15–16, 95, 124, 338 WooMe.com 14, 87–8, 101–2, 263 Workday 90 world population 9–10 Worldwide Developers Conference (WWDC) 313 wowing people 8–9 WTI see WebTranslateIt Xiaomi 306 Y Combinator 159–60, 184–5, 211, 407, 410–11 Yahoo!

Index Note: page numbers in bold refer to illustrations, page numbers in italics refer to information contained in tables. 99designs.com 111 500 Startups accelerator 136, 160 Accel Partners 3, 158, 261, 304, 321, 336, 383 accelerators 136, 159–60, 160 accountants 164, 316 accounting software 164 acquisition (of users) costs 148–9, 184, 236–7, 275–9, 282 and Facebook 271, 272, 273–4 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 252, 259, 266, 267–74, 275–84, 295–307 and incentive-based networks 270–1 international 295–307 for million dollar apps 136–7, 139, 140–51, 148–9, 153 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 strategy 222–31 for ten-million-dollar apps 211–12, 213, 222–31, 236–7, 248–9 and traditional channels 268–9 and ‘viral’ growth 225, 278, 279–84 zero-user-acquisition cost 278 acquisitions 414–25 buying sustained growth 417–18 by non-tech corporations 418–20 initial public offerings 420–2 Waze 415–16 activation (user) 136, 137, 139, 153–4, 211–12, 213 Acton, Brian 54, 394 addiction, smartphone 30–1 Adler, Micah 269 administrators 409 AdMob 414–15 advertising 43 business model 67, 89–90 costs 140 and Facebook 271, 272, 273–4 mobile 148–9, 268–70, 272–3, 272 mobile social media 272–3, 272 mobile user-acquisition channels 269–70 outdoor 264 shunning of 42, 54–6 video ads 273 aesthetics 131 after product–market fit (APMF) 180 agencies 195–7, 264, 343 ‘agile coaches’ see scrum masters agile software development 192–3, 299, 315, 357, 377 Ahonen, Tomi 45 ‘aiming high’ 40–1 Airbnb 160, 301 alarm features 48 Albion 111 alerts 293 Alexa.com 146 Alibaba 227 ‘ALT tags’ 147 Amazon 7, 29, 131, 164, 227, 276, 366, 374–5, 401, 406 Amazon Web Services 374 American Express 347 Amobee 149 analytics 134–5, 149, 199, 205, 210, 212, 217–21, 294 and cohort analysis 287–8 Flurry 135, 149, 220 function 217–18 Google Analytics 135, 219–20, 345 limitations 284 Localytics 135, 221 and marketing 263 mistakes involving 218–19 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 Andreessen, Marc 180, 418–19 Andreessen Horowitz 72, 80, 180, 321, 383, 385, 418–19 Android (mobile operating system) 6, 23–4, 38, 415 advertising 274 audience size 119 beta testing 202 building apps for 116–22 and international apps 296 in Japan 306 scaling development and engineering 357–8 time spent on 26 and WhatsApp 55 Angel Capital Association 162 angel investors 154, 155–6, 323 AngelList 99, 131, 155, 159, 233 Angry Birds (game) 6, 42, 47, 57–8, 87, 89, 97 and application programming interface 36 delivering delight 207 design 131 funding 321 game in game 348–9 international growth 297–9 platform 117, 118 product extension 356 virality 282 annual offsites 379 annual revenue per user (ARPU) 215, 219, 232, 236 anonymity 43, 56–7 anti-poaching clauses 247 antidilution rights 245 API see application programming interface app descriptions 143 app development billion-dollar app 8, 389–425 CEO advice 406–13 getting acquired 414–25 people 395–405 process 390–1 five-hundred-million-dollar app 325–87 funding 328, 383–7 hiring staff 334–6, 337–40 killer product expansion 350–63 process 326–8 scaling 326, 330–6, 331–2 scaling marketing 341–9 scaling people 364–72, 377–9 scaling process 373–82 scaling product development 357–63 hundred-million-dollar app 251–324 international growth 295–307 process 252–4 product-market fit 255–6 retention of users 286–94 revenue engines 257–66, 275–85 user acquisition 267–74 million-dollar app 81–171 app Version 0.1 123–35 coding 133–4 design 129–33 feedback 127, 134–5 funding 152–60, 161–71, 176, 235–49 identity of the business 106–14 lean companies 115–22 metrics 136–9, 139 process 82–4 startup process 85–105 testing 126–8 user acquisition 140–51 ten-million-dollar app 173–249 growth engine 222–31, 235–49 metrics 211–21 new and improved Version 1.0 198–210 process 174–6 product–market fit 180–97 revenue engine 232–4 venture capital 235–49 app stores 22, 27–8, 33–4 see also Apple App Store; Google Play app-store optimisation (ASO) 142, 225 AppAnnie 205 Apple 19, 20, 31–2, 393 application programming interface 35–6 designers 129 Facetime app 46 iWatch 38–9 profit per employee 402–3 revenue per employee 401 visual voicemail 50 Worldwide Developers Conference (WWDC) 313 see also iPad; iPhone Apple App Store 22, 27, 32–3, 75, 88, 89, 117, 226 finding apps in 140, 141, 142–5 international apps 297–9 making submissions to 152–3 and profit per employee 403 ratings plus comments 204–5 Apple Enterprise Distribution 201–2 application programming interface (API) 35–6, 185, 360, 374 ARPU see annual revenue per user articles of incorporation 169 ASO see app-store optimisation Atari 20 Atomico 3, 261, 321, 383 attribution 227–31 for referrals 230–1 average transaction value (ATV) 214–15, 219, 232, 236, 387 Avis 95 backlinking to yourself 146 ‘bad leavers’ 247 Balsamiq.com 128 Banana Republic 352 bank accounts 164 banking 156–7 Bardin, Noam 43 Barr, Tom 338 Barra, Hugo 120, 306 Baseline Ventures 72 Baudu 226 beauty 131 BeeJiveIM 33 before product–market fit (BPMF) 180 ‘below the fold’ 143 Beluga Linguistics 297 Benchmark 75 benefits 398–400 beta testing 201–4 Betfair 358 Bezos, Jeff 366, 374 Bible apps 45 billion 9–10 Billion-Dollar Club 5 billionaires 9 Bing 226 ‘black-swan’ events 54 BlackBerry 23 Blank, Steve 257 Blogger 41 blood sugar monitoring devices 38 board seats 242, 243–4 board-member election consent 169 Bolt Peters 363 Booking.com 320 Bootstrap 145 Botha, Roelof 76, 77, 80 Box 7, 90, 276, 396–7, 411 brains 10 brainstorming 108 branding 111–13, 143, 263–4 Braun 129 Bregman, Jay xiii, 14–16, 95, 124, 209, 303 bridge loans 323 Brin, Sergey 366 Bring Your Own Infrastructure (BYOI) 17–18 Brougher, Francoise 340 Brown, Donald 44 Brown, Reggie 104–5 Bubble Witch 421 Buffet, Warren 4 build-measure-learn cycle 116 Burbn.com 72–4, 80 business advisors/coaches 103 business analysts 343 business culture 395–8 business goal setting 310–11 business models 67, 83, 87, 88–91, 175, 253, 259, 327, 351–2, 391, 400, 423–4 business success, engines of 183–4, 423–4 Business Wire 150 CAC see Customer Acquisition Cost Cagan, Marty 314 calendars 49 calorie measurement sensors 38 Cambridge Computer Scientists 160 camera feature 48 Camera+ app 48 Candy Crush Saga 6, 47, 87, 89, 131, 278–81, 318, 349, 421–2 card-readers 41–2 cash flow 164 CEOs see Chief Executive Officers CFOs see Chief Financial Officers channels incentive-based networks 270–1 mobile social-media 271–3, 272 mobile user-acquisition 269–70 source attribution 227–31 testing 224–7 traditional 268–9 viral 280–2 charging phones 49–50 Chartboost 149 chauffer hire see Uber app check-ins, location-based 72, 74 Chief Executive Officers (CEOs) 309, 380 advice from 406–13 and the long haul 68 and product centricity 185–6 role 337 Chief Financial Officers (CFOs) 316 Chief Operations Officers (COOs) 309, 326, 337–40, 380 Chief Technology Officers (CTOs) 186–7, 195 Chillingo 298 China 24–5, 146, 226, 306–7 Cisco 402 Clash of Clans (game) 6, 28, 36, 47, 87, 89, 97, 118, 227, 348–9, 398 Clements, Dave 120 Climate Corporation 412, 419 clock features 47 cloud-based software 67, 90 Clover 419 coding 133–4 cofounders 85, 91–105, 188, 191 chemistry 92–3 complementary skills 93 finding 96–9 level of control 94 passion 93–4 red flags 102–3 successful matches 104–5 testing out 100–2 cohort analysis 237, 287–8 Color.com (social photo-sharing) app 113, 255 colour schemes 111 Commodore 20 communication open 412–13 team 194 with users 208–9 Companiesmadesimple.com 163–4 computers 20–1, 29 conferences 97–8, 202, 312–13 confidentiality provisions 244 connectedness 30 ConnectU 105 consumer audience apps 233–4 content, fresh 147 contracts 165–6 convertible loans 163 Cook, Daren 112 cookies 228–9 Coors 348 COOs see Chief Operations Officers Cost Per Acquisition (CPA) 148–9 Cost Per Download (CPD) 148 Costolo, Dick 77–8, 79–80 costs, and user acquisition 148–9, 184, 236–7, 275–9, 282 Crash Bandicoot 33 crawlers 146–7 Cray-1 supercomputer 20 CRM see customer-relationship management CrunchBase 238 CTOs see Chief Technology Officers Customer Acquisition Cost (CAC) 148–9, 184, 236–7, 275–9 customer lifecycle 212–14 customer segments 346–7 customer-centric approach 344 customer-relationship management (CRM) 290–4, 343 customer-support 208–9 Cutright, Alyssa 369 daily active users (DAUs) 142 D’Angelo, Adam 75–6 data 284–5, 345–7 data engineers 284 dating, online 14, 87–8, 101–2, 263 decision making 379–82, 407–8 defining apps 31–4 delegation 407 delight, delivery 205–7 design 82, 129–33, 206–7 responsive 144 designers 132, 189–91, 363, 376 developer meetups 97 developers see engineers/developers development see app development; software development development agencies 196 ‘development sprint’ 192 Devine, Rory 358–9 Digital Sky Technologies 385 directors of finance 316–17 Distimo 205 DLD 97 Doerr, John 164, 310 Doll, Evan 42–3, 105 domain names 109–10 international 146 protection 145–6 Domainnamesoup.com 109 Dorsey, Jack 41, 58, 72, 75–7, 79–80, 104, 112, 215–16, 305, 312, 412–13 ‘double-trigger’ vesting 247 DoubleClick 414 Dow Jones VentureSource 64 down rounds 322–3 downloads, driving 150–1 drag along rights 245 Dribbble.com 132 Dropbox 7, 90, 131, 276 CEO 407, 410–11 funding 160 scaling 336 staff 399 Dunbar, Robin 364–5 Dunbar number 365 e-commerce/marketplace 28–9, 67, 89, 213–14 Chinese 306 Flipboard and 351–2 and revenue engines 232, 233–4, 276 social media generated 271–2 and user retention 288, 289 eBay 7, 28–9, 131, 180, 276 economic models 275 economies of scale 331–2, 331–2 eCourier 15, 95 education 68–9 edX 69 Ek, Daniel 357 Ellis, Sean 182 emails 291–3 emotion effects of smartphones on 29–30, 30 inspiring 223–4 employees see staff employment contracts 246–7 engagement 236, 278, 283 engineering VPs 337, 358–9 engineers/developers 190–1, 194–5, 361–2, 362, 370, 375–7, 405 enterprise 90, 233–4 Entrepreneur First programme 160 entrepreneurs 3–5, 7–8, 65, 262, 393–4, 409, 424 Ericsson 21 Etsy 107, 109, 110, 358 Euclid Analytics 149 Evernote 7, 90, 131, 399 ExactTarget 291 excitement 30 executive assistants 367 Exitround 419 experience 67–8, 264, 397 Fab.com 352 Facebook 7, 10, 26, 32, 48, 76, 226, 394, 422 and acquisition of users 271, 272, 273–4 acquisitions 416–18, 417 agile culture 375 alerts 293 and application programming interface 36 board 180 and business identity 114 and Candy Crush 280–1 Chief Executive Officer 406 cofounders 100–1 and Color 255–6 design 131, 206, 363 Developer Garage 97 driving downloads on 151 and e-commerce decisions 271, 272 and FreeMyApps.com 271 funding 419 and getting your app found 147 and the ‘hacker way’ 375 initial public offering 420–1 and Instagram 29, 51, 76–80, 90, 117 name 110 ‘No-Meeting Wednesday’ 376 product development 187 profit per employee 403 revenue per employee 401 scaling 336 and Snapchat 57 staff 339, 362, 363, 398, 401, 403 and virality 281 WhatsApp purchase 42, 54–6, 416–17, 417 zero-user-acquisition cost 278 and Zynga 279, 281 Facetime app 46 fanatical users 294 feedback 86, 127, 134–5, 182, 192–3, 198–201, 256, 396 loops 204, 211 qualitative 199 quantitative 199 see also analytics Feld, Brad 170, 241 Fenwick and West 168 Fiksu 264, 269–70 finance, VP of 317–18 finding apps 140–8, 148–9 FireEye 90 First Data 419 first impressions 107–10 Fitbit 38 fitness bracelets 38 flat rounds 322–3 Flipboard 6, 29, 42–3, 49, 51, 89–90 and application programming interface 36 Catalogs 351–2 cofounders 105 design 131, 207 funding 164 growth 351–2 platform choice 119 product innovation 351–2 user notifications 292 virality 281 zero-user-acquisition cost 278 Flurry 135, 149, 220 Fontana, Ash 233 Forbes magazine 40 Ford Motors 419 Founder Institute, The 168 founder vesting 166–7, 244 Foursquare 419 France Telecom 13 franchising 354 FreeMyApps.com 270–1 Friedberg, David 412 Froyo (Android mobile software) 7 Fujii, Kiyotaka 304 full service agencies 195–6 functionality 25–6, 45–50, 131 funding 72, 75–6, 84, 87–8, 152–60, 161–71, 179 accelerators 159–60 angel investors 154, 155–6, 323 for billion-dollar apps 391 convertible loans 163 core documents 169–70 for five-hundred-million-dollar apps 328, 383–7 founder vesting 166–7 for hundred-million-dollar apps 254, 258, 316–17, 318–24 incubators 159–60 legal aspects 163–4 and revenue engines 233–4 Series A 234, 238–40, 238, 240, 241, 242–6, 255, 319–21, 385 Series B 238, 241, 253, 260, 284, 319–21, 322, 384 Series C 384 signing a deal 167–8 for ten-million-dollar apps 152–60, 161–71, 176, 235–49 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 game in game 348–9 gaming 42, 47, 318, 355 business model 67, 89 and revenue engines 232, 278–9 and user retention 288, 289 see also specific games Gandhi, Sameer 336 Gartner 271 Gates, Bill 4 general managers (GMs) 300–3 Gladwell, Malcolm 424 Glassdoor 361–2 Global Positioning System (GPS) 23 Gmail 72 GMs see general managers goal setting 40–1, 310–11 Goldberg, Dave 397 Goldman Sachs 385 ‘good leavers’ 247 Google 7, 19, 23, 27, 72, 88, 164, 226 acquisitions 43, 414–16, 418 application programming interface 35–6 beta testing 202 Chief Executive Officer 406–8 developer meetups 97 finding your app on 144, 147 Hangouts app 46 meetings 381–2 mission 404, 408–9 and the OKR framework 310 profit per employee 403, 405 revenue per employee 401, 405 scaling 332 and Snapchat 57 and source attribution 228–9 staff 339, 340, 361–2, 366, 401, 403, 404–5, 412 Thank God It’s Friday (TGIF) meetings 311–12 transparency 413 value 78 Waze app purchase 43 and WhatsApp 56 zero-user-acquisition cost 278 see also Android (mobile operating system) Google Ad Mob 149 Google AdSense 149 Google Analytics 135, 219–20, 345 Google Glass 38–9, 405 Google I/O conference 313 Google Maps 33, 35, 414, 416 Google Now 37 Google Play 88, 89, 117, 120, 226 and beta testing 202 finding apps in 141–5 profit per employee 403 ratings plus comments 204–5 Google Reader 72 Google Ventures 384 Google X 405 Google+ and business identity 114 and virality 281 Google.org 339 GPS see Global Positioning System Graham, Paul 184–5, 211 Graphical User Interface (GUI) 20 Greylock 321, 383 Gross, Bill 406–7, 409–10 Groupon 7, 51–2, 227, 344–5, 419 Grove, Andy 310 growth 267, 308–17 buying sustained 417–18 engines 184, 210, 222–31, 259, 265 and five-hundred-million-dollar apps 329–36 and Friday update meetings 311–12 and goal setting 310–11 and hiring staff 308–9, 411–12 and product and development teams 313–14 and staff conferences 312–13 targets 234, 260 see also acquisition (of users); international growth; scaling Growth Hackers 182 GUI see Graphical User Interface hackathons 99 Haig, Patrick 143 Hailo app xiii–xiv, 5, 36, 89, 386 big data 284–5 branding 112–13 cofounders 94–6 customer segments 346–7 customer-support 208–9 design 131, 132, 133, 206–7 development 123–7, 153–4 Friday update meetings 311 funding 162, 242 goal setting 310 growth 296–7, 299, 302–4, 308–11, 313, 315–17, 329–30, 334–6 hiring staff 308–9, 334–6, 338, 366–7 idea for 14–18 international growth 296, 297, 299, 302–4 market research 182 marketing 263, 264, 268, 270, 273, 341, 347–8 meetings 381 metrics 137–9, 216 name 107 organisational culture 396 platform choice 117, 120, 121 premises xiii–xiv, 177–8, 329–30, 371–2, 386 product development 189, 191, 196 retention 293–4 revenue engine 276 scaling development and engineering 357 scaling people 365–7 scaling process 377 team 258 testing 177–8, 201–4 and user emotionality 224 virality 280, 282 Hangouts app 46 Harris Interactive 31 HasOffers 149 Hay Day 47, 97 head of data 342 Heads Up Display (HUD) 38 heart rate measurement devices 37–8 Hed, Niklas 42 hiring staff 308–9, 334–6, 337–40, 365–70 history of apps 31–2 HMS President xiii–xiv, 177–9, 329, 371, 386 HockeyApp 202 HootSuite 151 Houston, Drew 407, 410–11 HP 180, 402 HTC smartphone 121 HUD see Heads Up Display human universals 44–5 Humedica 419 hyperlinks 147 hypertext markup language (HTML) 147 I/O conference 2013 202 IAd mobile advertising platform 149 IBM 20, 402 icons 143 ideas see ‘thinking big’ identity of the business 86 branding 111–13 identity crises 106–14 names 106–11 websites 113–14 image descriptions 147 in Mobi 149 in-app purchases 28 incentive-based networks 270–1 incorporation 163–4, 179 incubators 159–60 Index Ventures 3, 261 initial public offerings (IPOs) 64, 67–9, 78, 80, 246, 420–2 innovation 404–5 Instagram 6, 29, 48, 51, 67, 71–80, 88–90, 114, 117, 226, 278, 340, 417–18 cofounders 73–4 design 131 funding 75–6, 77–8 X-Pro II 75 zero-user-acquisition cost 278 instant messaging 46 Instantdomainsearch.com 109 integrators 410 Intel 310 intellectual property 165–6, 244, 247 international growth 295–307 Angry Birds 297–9 Hailo 296, 297, 299, 302–4 language tools 297 Square 295, 299, 304–6 strings files 296 Uber 299–302 International Space Station 13 Internet bubble 13 investment see funding iOS software (Apple operating system) 7, 23–4, 46, 75, 104 advertising 274 audience size 119 building apps for 116–22 and international apps 296 scaling development and engineering 357–8 time spent on 26 iPad 42–3, 118–20, 351 iPhone 6, 19, 22–3, 32, 38–9, 183, 351 advertising on 274 camera 48 designing apps for 117–18, 120 finding apps with 145 games 42, 47, 58 and Instagram 74–6 in Japan 306 and Square 104, 306 and Uber 301 user spend 117 and WhatsApp app 54–5 iPod 22 IPOs see initial public offerings Isaacson, Walter 32 iTunes app 22, 47, 88, 143 iTunes U app 69 Ive, Jony 129 iZettle 304 Jackson, Eric 40 Jain, Ankit 142 Japan 227, 304–6 Jawbone Up 38 Jelly Bean (Android mobile software) 7 Jobs, Steve 4, 22, 32, 323, 393, 425 journalists 150–1 Jun, Lei 306 Kalanick, Travis 299–300, 384, 422 Kayak 336 Keret, Samuel 43 Keyhole Inc. 414 keywords 143, 146 Kidd, Greg 104 King.com 349, 421–2 see also Candy Crush Saga KISSmetrics 291 KitKat (Android mobile software) 7 Klein Perkins Caulfield Byers (KPCB) 158, 261, 321, 383 Kontagent 135 Koolen, Kees 320, 339 Korea 30 Koum, Jan 42, 54, 55–6, 154, 321, 394, 416 Kreiger, Mike 73–6 language tools 297 Launchrock.com 113–14, 145, 202 Lawee, David 415 lawyers 103, 169, 170, 242 leadership 410–11 see also Chief Executive Officers; managers lean companies 69, 115–22, 154, 257, 320–1 Lee, Bob 340 legalities 163–70, 242–7, 301 letting go 406–7 Levie, Aaron 396–7, 411 Levinson, Art 32 LeWeb 97 Libin, Phil 399 licensing 356 life experience 67–8, 264 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 Line app 46, 226 Lingo24 297 LinkedIn 97, 226, 406, 408–9 links 147 liquidation preference 242, 243, 245 non-participating 245 Livio 419 loans, convertible 163 Localytics 135, 221 locations 69 logos 111–14 LTV see lifetime value luck 412 Luckey, Palmer 39 LVMH 304 Lyons, Carl 263 Maiden 95 makers 375–7 see also designers; engineers/developers managers 189–90, 300–3, 375–7, 405 MapMyFitness 419 market research 115, 127, 182 marketing data 345–7 and Facebook 271, 272, 273–4 and incentive-based networks 270–1 marketing engineering team 344–5 and mobile social media channels 271–3, 272 and mobile user-acquisition channels 269–70 partner marketing 347–8 scaling 341–9 teams 262–6, 337, 342 and traditional channels 268–9 VPs 262–6, 337, 342 marketplace see e-commerce/marketplace MasterCard 347–8 Matrix Partners 283 McClure, Dave 136, 160, 211, 234 McCue, Mike 42–3, 105, 351 McKelvey, Jim 41, 104 ‘me-too’ products 181 Medium 41 Meebo 73 meetings 379–82, 412–13 annual offsite 379 daily check-ins 381 disruptive nature 376–7 Friday update 311–12 meaningful 381–2 monthly strategic 380 quarterly 380 weekly tactical 380 Meetup.com 98–9 Mendelsen, Jason 170 messaging platforms 226 time spent on 46 and user retention 288, 289 metrics 136–9, 139, 211–21 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 average transaction value (ATV) 214–15, 219, 232, 236, 387 consensual 215–16 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291, 342 and product-market fit 209–10 referral 137, 138, 139, 153, 154, 211–12, 213, 230–1 revenue 137, 138, 139, 154, 211–12, 213, 214–15, 219, 291 transparency regarding 312 see also acquisition (of users); retention (of users) mice 20 Microsoft application programming interface 35–6 revenue per employee 401 Windows 20, 22, 24 Millennial Media 149 minimum viable product (MVP) 123, 153 MirCorp 13–14 mission 261, 404, 408–9 Mitchell, Jason 51 Mitsui Sumitomo Bank 305 Mixpanel.com tool 135, 217–18, 220–1, 287, 290–1, 345 MMS see Multimedia Messaging Service Mobile Almanac 45 Mobile App Tracking 230, 231 mobile technology, rise of 19–39 MoMo app 306 Monsanto 419 moonshots 404–5 Moore, Jonathan 200 MoPub 149 Moqups.com 128 Mosaic 180 Motorola 21 Moz.com 143 Mullins, Jacob 419 Multimedia Messaging Service (MMS) 47 Murphy, Bobby 43, 104–5, 152–3 music player apps 47 MVP see Metrics into Action; minimum viable product names 106–11, 142 NameStation.com 108 Nanigans 273–4 National Venture Capital Association 64 native apps 33–4 NDA see Non Disclosure Agreement negotiation 265 Net Promoter Score (NPS) 206, 209 net-adding users 206 Netflix 400 Netscape 164, 180 New Enterprise Associates 385 New York Times news app 32–3, 256 news and alerts feature 48–9 Nextstop 72 Nguyen, Bill 255–6 NHN 227 Nike Fuelband 38 Nintendo Game Boy 47 Nokia 21, 35–6 Non Disclosure Agreement (NDA) 165 noncompetition/non-solicitation provision 244, 247 notifications 291–4 NPS see Net Promoter Score Oculus VR 39 OKR (‘objectives and key results’) framework 310–11, 380 OmniGraffle 128 open-source software 23, 34–5, 185 OpenCourseWare 68–9 operating systems 20–4 see also Android; iOS software operations VPs 337 org charts 258, 309 organisational culture 395–8 O’Tierney, Tristan 104 outsourcing 194–7 ownership and founder vesting 166–7 and funding 155, 156, 161–3, 318 oxygen saturation measurement devices 37–8 Paananen, Ilkka 118–19, 397–8 Page, Larry 4, 23, 382, 404, 407–8 Palantir 90 Palihapitiya, Chamath 187 Pandora 7, 47, 67, 131, 410 pay-before-you-download model 28 pay-per-download (PPD) 225 Payleven 304 payment systems 7, 33–4, 227, 304, 305 see also Square app PayPal 7, 227, 304, 305 Pepsi 196 Perka 419 perks 398–400 perseverance 67, 394, 410 personal computers (PCs) 29 perspiration measurement devices 38 Pet Rescue Saga 349, 421 Petrov, Alex 369 phablets 7 Pham, Peter 255 PhoneSaber 33 Photoshop 128 PIN technology 305 Pincus, Mark 311 Pinterest app 48, 226 and business identity 114 and e-commerce decisions 271, 272 and getting your app found 147 name 107 and virality 281 Pishevar, Shervin 300 pivoting 73–4 population, global 9–10 portfolio companies 261–2 PowerPoint 128 PPD see pay-per-download preferential return 243 premises 370–2 preparation 412 press kits 148, 150 press releases 150 Preuss, Dom 98 privacy issues 43, 56–7 private vehicle hire see Uber pro-rata rights 242, 243 producers 409 product chunks 360 product development scaling 357–63 scope 199 team building for 188–91 and team location 193–4 and vision 186–8, 191 see also app development; testing product expansion 350–63 product extension 354 product managers 189–90, 405 product-centricity 185–6, 314, 360 product-market fit 9, 180–97, 235–6, 248, 256–7 measurement 209–10, 212, 286–8 profit 267, 320, 342 profit margin 258–9, 318, 321 profit per employee 402–4, 403, 405 profitability 260, 277, 400 Project Loon 405 proms 12 proto.io tool 133 prototype apps 86, 174 app Version 0.1 123–35, 174 new and improved Version 1.0 198–210 rapid-design prototyping 132–3 PRWeb 150 PSP 47 psychological effects of smartphones 29–30, 30 pttrns.com 131 public-relations agencies 343 publicity 150–1, 225, 313 putting metrics into action 138–9 Puzzles and Dragons 47, 131 QlikView 221, 284–5 QQ 307 quality assurance (QA) 190–1, 196 Quora 76 QZone 307 Rabois, Keith 368, 369 Rakuten 227 Rams, Dieter 129 rapid-design prototyping 132–3 ratings plus comments 204–5 Red Bull 223 redemption codes 230 referrals (user) 137, 138, 139, 153, 154, 211–12, 213 attribution for referrals 230–1 referral codes 230 religious apps 45 remuneration 361–2, 362, 363 Renault 13 restated certification 169 retention (of users) 136–9, 153, 154 for five hundred-million-dollar apps 327, 341–3 for hundred-million-dollar apps 286–94, 288–9 measurement 286–8 for ten-million-dollar apps 206, 211–12, 213, 278 revenue 137–8, 139, 154, 211–12, 213, 214–15, 219, 236, 239–40, 267, 291, 331–2, 341–2, 354 revenue engines 184, 210, 232–4, 257–66, 265, 275–85 revenue per employee 400–2, 402, 405 revenue streams 27–9 Ries, Eric, The Lean Startup 115–16 Rockefeller, John D. 9 Rocket Internet 304 Rolando 33 Rosenberg, Jonathan 413 Rovio 58, 97, 118, 297–9, 318, 320–1, 336, 354, 409 see also Angry Birds Rowghani, Ali 77 Rubin, Andy 23 Runa 419 SaaS see software as a service Sacca, Chris 75–6 sacrifice 86–7 Safari Web browser 32 salaries 361–2, 362, 363 sales VPs 337 Salesforce 291 Samsung 23 Galaxy Gear smartwatch 38 smartphones 121 Sandberg, Sheryl 4, 100–1, 339, 397 SAP 304 scaling 259, 308, 312, 323–4, 326, 330–6, 331–2, 384–5 decision making 379–81 international growth 295–307 marketing 341–9 and organisational culture 396–8 people 338–9, 364–72 premature 334–5 process 373–82 product development and engineering 357–63 and product innovation 350–6 reasons for 333–4 skill set for 335–6 Schmidt, Eric 120 scope 199 screenshots 131, 144, 206 scrum masters (‘agile coaches’) 315, 359, 360 search functions 49 organic 141–2, 141, 145 search-engine optimisation (SEO) 142, 145–8, 225 Sedo.com 109 Seed Fund 136 Seedcamp 160 Sega Game Gear 47 segmentation 220, 287, 290, 346–7 self-empowered squads/units 360 SEO see search-engine optimisation Sequoia Capital 76, 77–80, 158, 255, 321, 383, 385 Series A funding 234, 238–40, 238, 240, 241, 242–6, 255, 261, 262, 319–21, 385 Series B funding 238, 241, 253, 260, 319–21, 322, 384 Series C funding 384 Series Seed documents 168 Sesar, Steven 263 sex, smartphone use during 31 Shabtai, Ehud 43 shares 156, 166–8, 244 ‘sharing big’ 51–2, 52 Shinar, Amir 43 Shopzilla 263 Short Message Service (SMS) 21, 46–7 Silicon Valley 71–4, 77, 79, 99, 162, 168, 180, 184, 255, 340, 361, 411, 422 Sina 227 sitemaps 146–7 skills sets complementary 93 diverse 409–10 for scaling 335–6 Skok, David 283 Skype app 7, 46, 111, 200–1, 226, 357, 419 Sleep Cycle app 48 Smartling 297 smartwatches 7, 38–9 SMS see Short Message Service Snapchat app 6, 43, 46, 56–7, 88, 89, 223, 226, 416, 418 cofounders 104–5 design 131 funding 152–3, 307, 320 name 107 platform 117 staff 340 valuations 333 virality 280, 283 zero-user-acquisition cost 278 social magazines 42–3 see also Flipboard social media 48 driving downloads through 151 and getting your app found 147 mobile channels 271–3, 272 and user retention 288, 289 Sofa 363 SoftBank 227 software development agile 192–3, 299, 315, 357, 377 outsourcing 194–5 see also app development software as a service (SaaS) 67, 90, 208, 214, 233, 276–7 Somerset House 329–30, 371 Sony 21, 47 SoundCloud 358 source attribution 227–31 space tourism 13–14 speech-to-text technology 50 speed 20 Spiegel, Evan 43, 56–7, 104–5, 152–3 Spinvox 50 Splunk 90 Spotify app 47, 357–8 SQL 284 Square app 6, 41–2, 58–9, 87, 89, 333, 350 branding 112 Chief Executive Officer 412–13 cofounders 104 design 131, 363 funding 320–1 international growth 295, 299, 304–6 marketing 348 metrics 215–16 name 107, 110 product–market fit 183 revenue engine 276 scaling people 367–8 scaling product innovation 352–3 staff 340, 367–8 transparency 312 virality 282 Square Cash 353 Square Market 353 Square Register 350, 352–3 Square Wallet 348, 350, 353 Squareup.com 144 staff at billion-dollar app scale 395–405, 423 attracting the best 91 benefits 398–400 conferences 312–13 conflict 334, 378 employee agreements 244 employee legals 246–7 employee option pool 244 employee-feedback systems 378 firing 370, 378 hiring 308–9, 334–6, 411–12 induction programmes 370 investment in 360 mistakes 369–70, 411–12 and premises 370–2 profit per employee 402–4, 403 revenue per employee 400–2, 402 reviews 370 scaling people 364–72, 377–9 scrum masters 315, 359, 360 training programmes 370 see also cofounders; specific job roles; teams Staples 419 Starbucks 338, 348 startup weekends 98 startups, technology difficulties of building 63–80 failure 63–5, 73–4 identity 106–14 lean 115–22, 154 process 82–4, 85–105 secrets of success 66–9 step sensors 38 stock markets 420–1 straplines 111 strings files 296 Stripe 160 style 111 subscriptions 90 success, engines of 183–4, 423–4 SumUp 304 Supercell 28, 47, 97, 118–19, 318, 336, 397–8, 401, 403 see also Clash of Clans; Hay Day SurveyMonkey 397 surveys 206, 209 synapses 10 Systrom, Kevin 71–80 tablets 7 Tableau Software 90 Taleb, Nicholas Nassim 54 Tamir, Diana 51 Tap Tap Revolution (game) 42 Target 419 taxation 164 taxi hailing apps see Hailo app TaxiLight 16 team builders 264 team building 188–91 teams 82, 174, 252, 390 complementary people 409–10 for five-hundred-million-dollar apps 326, 342–5, 357–63, 374, 386 growth 313–14, 326, 342–4 for hundred-million-dollar apps 258–61 located in one place 193–4 marketing 262–6, 342–4 marketing engineering 344–5 product development and engineering 357–63 ‘two-pizza’ 374 TechCrunch Disrupt 97, 99 technology conferences 97–8, 202, 312–13 Techstars 159, 160, 168 Tencent 307 Tencent QQ 226 term sheets 168, 169, 170, 243–4 testing 126–8, 177–8, 187–8, 192–3, 199–201 beta 201–4 channels 224–7 text messaging 21 unlimited packages 42 see also Short Message Service ‘thinking big’ 40–59, 82, 85 big problem solutions 41–3 disruptive ideas 53–9 human universals 44–5 sharing big 51–2, 52 smartphones uses 45–50 Thoughtworks 196 time, spent checking smartphones 25–6, 26, 45–50 Tito, Dennis 13 tone of voice 111 top-down approaches 311 traction 233, 252 traffic information apps 43 traffic trackers 146 translation 296–7 transparency 311–12, 412–13 Trilogy 13 Tumblr 110, 226, 399, 418 Twitter 41, 48, 54, 72, 226, 394 acquisitions 418 and application programming interface 36 and Bootstrap 145 and business identity 114 delivering delight 206 and e-commerce decisions 272 and FreeMyApps.com 271 funding 419, 421 and getting your app found 147 initial public offering 421 and Instagram 51, 76–7, 79–80 name 110 and virality 281 ‘two-pizza’ teams 374 Uber 6, 36, 87, 89, 333, 350 and attribution for referrals 231 design 131 funding 320, 384, 422 international growth 295, 299–302 name 107, 110 revenue engine 276 revenue per employee 401 scaling product innovation 355–6 staff 339, 399 user notifications 292 virality 280 Under Armour 419 Union Square Ventures (USV) 3, 158, 242, 261, 262, 288, 321, 323, 377, 383 unique propositions 198 UnitedHealth Group 419 URLs 110 ‘user experience’ (UX) experts 190 user journeys 127–8, 213–14 user notifications 291–4 user stories 193 users 83, 175, 252, 327, 390 activation 136, 137, 139, 153–4, 211–12, 213 annual revenue per user (ARPU) 215, 219, 232, 236 communication with 208–9 definition 137 emotional response of 223–4 fanatical 294 finding apps 140–8 lifetime value (LTV) 184, 215, 219, 220–1, 232, 275–7, 279, 291 metrics 136–9 net-adding of 206 ratings plus comments 204–5 referrals 137, 138, 139, 153, 154, 211–12, 213, 230–1 target 83, 115, 127 wants 180–97 see also acquisition (of users); retention (of users) Usertesting.com 200–1 USV see Union Square Ventures valuations 83, 161–3, 175, 237–8, 238, 253, 318, 319, 322, 327, 333, 391 venture capital 72, 75, 156–8, 165–6, 235–49, 261–2, 383–5, 385, 418–19 Viber app 6, 46, 1341 video calls 46, 47 viral coefficient 282–4 ‘viral’ growth 225, 278, 279–84 Communication virality 281 and cycle time 283–4 incentivised virality 280–1 inherent virality 280 measurement 282–4 social-network virality 281 word-of-mouth virality 281–2 virtual reality 39 vision 261, 393–4, 408–9, 414, 415 voice calls 46–7 voice-over-Internet protocol (VOIP) 46 voicemail 50 Wall Street Journal 43, 55 warranties 246 Waze app 6, 43, 97 acquisition 415–16 design 131 name 107 zero-user-acquisition cost 278 web browsing 49 Web Summit 97 websites 113–14, 144–8 WebTranslateIt (WTI) 297 WeChat app 46, 226, 306 Weibo 48 Weiner, Jeff 408–9 Wellington Partners 4 Weskamp, Marcos 207 Westergren, Tim 410 WhatsApp 6, 42, 46, 54–6, 87, 90, 226, 394 acquisition 42, 54–6, 416, 416–17, 417 cofounders 96 design 131, 144 funding 154, 320–1 platform 117–18 valuations 333 virality 280 White, Emily 340 Williams, Evan 41, 65 Williams, Rich 344 Wilson, Fred 110, 242, 288, 323, 377 Windows (Microsoft) 20–1, 22, 24, 24 Winklevoss twins 105 wireframes 127–8 Woolley, Caspar 15–16, 95, 124, 338 WooMe.com 14, 87–8, 101–2, 263 Workday 90 world population 9–10 Worldwide Developers Conference (WWDC) 313 wowing people 8–9 WTI see WebTranslateIt Xiaomi 306 Y Combinator 159–60, 184–5, 211, 407, 410–11 Yahoo!


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Wanderers: A Novel by Chuck Wendig

Black Swan, Boston Dynamics, centre right, citizen journalism, clean water, Columbine, coronavirus, crisis actor, currency manipulation / currency intervention, disinformation, fake news, game design, global pandemic, hallucination problem, hiring and firing, hive mind, Internet of things, job automation, Kickstarter, Lyft, Maui Hawaii, microaggression, oil shale / tar sands, private military company, quantum entanglement, RFID, satellite internet, side project, Silicon Valley, Skype, supervolcano, tech bro, TED Talk, uber lyft, white picket fence

The system was commissioned by the former administration, under President Nolan, who for a Republican was surprisingly science-friendly (he at least acknowledged the realities of climate change, space exploration, GMOs, and so forth)—though also very surveillance-friendly, which in the context of urging the creation of artificial intelligence tended to raise one’s hackles. Problem was, Black Swan didn’t have a budget line, so the money for it came in part out of the CDC, which had been given considerable funding after an Ebola scare in New York City (one that Benji had himself investigated). So Benex-Voyager created Black Swan specifically with the ability to detect upcoming outbreaks, pandemics, and even zoonotic jumps, where a disease leapt from animal to human. They called it Black Swan after Nassim Nicholas Taleb’s black swan theory, which suggested that some events were utterly unpredictable; only after the events happened did we rationalize their occurrence as something we should have expected.

“I’ve found myself thinking about you quite a lot. You’re brave and smart and kind and I’d be a fool not to trust you. I’m glad to have listened to Black Swan.” Suddenly, the Black Swan phone projected a pulse of green on the wall. Not one, but three pulses. “I think Black Swan likes that you listened to me,” he said. “It just pulsed green.” “Black Swan has impeccable taste. Better question is, how do you feel about me finding you on Black Swan’s suggestion?” “It’s, ahhh, it’s good.” A strange feeling swept over him. He felt feverish. His heart raced in a fit of tachycardia. His palms grew damp.

Further, such unexpected events disproportionately affected the outcome of history—far greater than those events we were able to predict or expect. Black swan events were therefore viewed as outliers—named as such from a statement made by the Roman poet Juvenal: “Rara avis in terris nigroque simillima cygno.” Or, roughly translated: “A rare bird, like a black swan.” His statement was understood throughout history as one meant to symbolize something that was impossible. Because black swans were believed not to exist. Except they did. Just as humankind often believed certain events or outcomes to be impossible—until they happened. Benex-Voyager saw this as a challenge, and named its machine Black Swan ironically.


pages: 379 words: 109,612

Is the Internet Changing the Way You Think?: The Net's Impact on Our Minds and Future by John Brockman

A Declaration of the Independence of Cyberspace, Albert Einstein, AltaVista, Amazon Mechanical Turk, Asperger Syndrome, availability heuristic, Benoit Mandelbrot, biofilm, Black Swan, bread and circuses, British Empire, conceptual framework, corporate governance, Danny Hillis, disinformation, Douglas Engelbart, Douglas Engelbart, Emanuel Derman, epigenetics, Evgeny Morozov, financial engineering, Flynn Effect, Frank Gehry, Future Shock, Google Earth, hive mind, Howard Rheingold, index card, information retrieval, Internet Archive, invention of writing, Jane Jacobs, Jaron Lanier, John Markoff, John Perry Barlow, Kevin Kelly, Large Hadron Collider, lifelogging, lone genius, loss aversion, mandelbrot fractal, Marc Andreessen, Marshall McLuhan, Menlo Park, meta-analysis, Neal Stephenson, New Journalism, Nicholas Carr, One Laptop per Child (OLPC), out of africa, Paul Samuelson, peer-to-peer, pneumatic tube, Ponzi scheme, power law, pre–internet, Project Xanadu, Richard Feynman, Rodney Brooks, Ronald Reagan, satellite internet, Schrödinger's Cat, search costs, Search for Extraterrestrial Intelligence, SETI@home, Silicon Valley, Skype, slashdot, smart grid, social distancing, social graph, social software, social web, Stephen Hawking, Steve Wozniak, Steven Pinker, Stewart Brand, synthetic biology, Ted Nelson, TED Talk, telepresence, the medium is the message, the scientific method, the strength of weak ties, The Wealth of Nations by Adam Smith, theory of mind, trade route, upwardly mobile, Vernor Vinge, Whole Earth Catalog, X Prize, Yochai Benkler

S is for Salon of the twenty-first century The Internet has made me think more about whom I would like to introduce to whom, and about whether to cyberintroduce people or introduce them in person through actual salons for the twenty-first century (see the Brutally Early Club). The Degradation of Predictability—and Knowledge Nassim N. Taleb Distinguished Professor of Risk Engineering, New York University–Polytechnic Institute; principal, Universa Investments; author, The Black Swan I used to think the problem of information is that it turns Homo sapiens into fools—we gain disproportionately in confidence, particularly in domains where information is wrapped in a high degree of noise (say, epidemiology, genetics, economics, etc.).

I also saw how people built too many theories based on sterile news, fooled by the randomness effect. But things are a lot worse. Now I think that, in addition, the supply and spread of information turns the world into Extremistan (a world I describe as one in which random variables are dominated by extremes, with Black Swans playing a large role in them). The Internet, by spreading information, causes an increase in interdependence, the exacerbation of fads (bestsellers like Harry Potter and runs on banks become planetary). Such a world is more “complex,” more moody, much less predictable. So consider the explosive situation: More information (particularly thanks to the Internet) causes more confidence and illusions of knowledge while degrading predictability.

Tipler We Have Become Hunter-Gatherers of Images and Information: Lee Smolin The Human Texture of Information: Jon Kleinberg Not at All: Steven Pinker This Is Your Brain on Internet: Terrence Sejnowski The Sculpting of Human Thought: Donald Hoffman What Kind of a Dumb Question Is That?: Andy Clark Public Dreaming: Thomas Metzinger The Age of (Quantum) Information?: Anton Zeilinger Edge, A to Z (Pars Pro Toto): Hans Ulrich Obrist The Degradation of Predictability—and Knowledge: Nassim N. Taleb Calling You on Your Crap: Sean Carroll How I Think About How I Think: Lera Boroditsky I Am Not Exactly a Thinking Person— I Am a Poet: Jonas Mekas Kayaks Versus Canoes: George Dyson The Upload Has Begun: Sam Harris Hell if I Know: Gregory Paul What I Notice: Brian Eno It’s Not What You Know, It’s What You Can Find Out: Marissa Mayer When I’m on the Net, I Start to Think: Ai Weiwei The Internet Has Become Boring: Andrian Kreye The Dumb Butler: Joshua Greene Finding Stuff Remains a Challenge: Philip Campbell Attention, Crap Detection, and Network Awareness: Howard Rheingold Information Metabolism: Esther Dyson Ctrl + Click to Follow Link: George Church Replacing Experience with Facsimile: Eric Fischl and April Gornik Outsourcing the Mind: Gerd Gigerenzer A Prehistorian’s Perspective: Timothy Taylor The Fourth Phase of Homo sapiens: Scott Atran Transience Is Now Permanence: Douglas Coupland A Return to the Scarlet-Letter Savanna: Jesse Bering Take Love: Helen Fisher Internet Mating Strategies: David M.


pages: 411 words: 108,119

The Irrational Economist: Making Decisions in a Dangerous World by Erwann Michel-Kerjan, Paul Slovic

"World Economic Forum" Davos, Alan Greenspan, An Inconvenient Truth, Andrei Shleifer, availability heuristic, bank run, behavioural economics, Black Swan, business cycle, Cass Sunstein, classic study, clean water, cognitive dissonance, collateralized debt obligation, complexity theory, conceptual framework, corporate social responsibility, Credit Default Swap, credit default swaps / collateralized debt obligations, cross-subsidies, Daniel Kahneman / Amos Tversky, endowment effect, experimental economics, financial innovation, Fractional reserve banking, George Akerlof, hindsight bias, incomplete markets, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Isaac Newton, iterative process, Kenneth Arrow, Loma Prieta earthquake, London Interbank Offered Rate, market bubble, market clearing, money market fund, moral hazard, mortgage debt, Oklahoma City bombing, Pareto efficiency, Paul Samuelson, placebo effect, precautionary principle, price discrimination, price stability, RAND corporation, Richard Thaler, Robert Shiller, Robert Solow, Ronald Reagan, Savings and loan crisis, social discount rate, source of truth, statistical model, stochastic process, subprime mortgage crisis, The Wealth of Nations by Adam Smith, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, too big to fail, transaction costs, ultimatum game, University of East Anglia, urban planning, Vilfredo Pareto

“Heuristic and Linear Models of Judgment: Matching Rules and Environments.” Psychological Review 114, no. 3: 733-758. Makridakis, S., R. M. Hogarth, and A. Gaba (2009). Dance with Chance: Making Luck Work for You. Oxford: Oneworld Publications. Savage, L. J. (1954). The Foundations of Statistics. New York: John Wiley & Sons. Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. New York: Random House. Winter, S. G., G. Cattani, and A. Dorsch (2007). “The Value of Moderate Obsession: Insights from a New Model of Organizational Search.” Organization Science 18, no. 3: 403-419. 4 The More Who Die, the Less We Care PAUL SLOVIC A defining element of catastrophes is the magnitude of their harmful consequences.

The reasons Marsh and Merton gave for thinking that any market inefficiencies will be “arbitraged away” by smart money have a number of limitations (Shleifer and Vishny, 1997; Barberis and Thaler, 2003). 7 These ads are displayed and discussed in Mullainathan and Shleifer (2005). 8 Allen et al. (2002). 9 Higgins (2005). Chapter 3 Hogarth: Subways, Coconuts, and Foggy Minefields 1 Taleb (2007) refers to coconuts with large consequences as “black swans.” 2 For a related approach, see the interesting work by Winter, Cattani, and Dorsch (2007). 3 See, for example, Hogarth and Karelaia (2007). Chapter 4 Slovic: The More Who Die, the Less We Care 1 Portions of this chapter appeared earlier in P. Slovic, “If I Look at the Mass I Will Never Act: Psychic Numbing and Genocide.”


Termites of the State: Why Complexity Leads to Inequality by Vito Tanzi

accounting loophole / creative accounting, Affordable Care Act / Obamacare, Alan Greenspan, Andrei Shleifer, Andrew Keen, Asian financial crisis, asset allocation, barriers to entry, basic income, behavioural economics, bitcoin, Black Swan, Bretton Woods, business cycle, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, Cass Sunstein, central bank independence, centre right, clean water, crony capitalism, David Graeber, David Ricardo: comparative advantage, deindustrialization, Donald Trump, Double Irish / Dutch Sandwich, experimental economics, financial engineering, financial repression, full employment, George Akerlof, Gini coefficient, Gunnar Myrdal, high net worth, hiring and firing, illegal immigration, income inequality, indoor plumbing, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), invisible hand, Jean Tirole, John Maynard Keynes: Economic Possibilities for our Grandchildren, Kenneth Arrow, Kenneth Rogoff, knowledge economy, labor-force participation, libertarian paternalism, Long Term Capital Management, low interest rates, market fundamentalism, means of production, military-industrial complex, moral hazard, Naomi Klein, New Urbanism, obamacare, offshore financial centre, open economy, Pareto efficiency, Paul Samuelson, Phillips curve, price stability, principal–agent problem, profit maximization, pushing on a string, quantitative easing, rent control, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Second Machine Age, secular stagnation, self-driving car, Silicon Valley, Simon Kuznets, synthetic biology, The Chicago School, The Great Moderation, The Market for Lemons, The Rise and Fall of American Growth, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, transfer pricing, Tyler Cowen: Great Stagnation, universal basic income, unorthodox policies, urban planning, very high income, Vilfredo Pareto, War on Poverty, Washington Consensus, women in the workforce

Some humans are not rational, as some psychologists – especially Daniel Kahneman, who received the Nobel Prize in economics for his economically relevant psychological work – and as some economists have shown in recent years (see Kahneman, 1994; Kahneman and Thaler, 2006; Ariely, 2008; Thaler and Sunstein, 2008; Lewis, 2017). Also, unexpected “black swans,” statistically improbable events that tend to be ignored because they are rare, make occasional, unexpected, and unwelcome visits (see Taleb, 2007). Furthermore, in increasingly common, real-life settings, some market operators may acquire so much space in the economy, and implicit monopoly power, that they may come to believe that, if things go badly in 80 Termites of the State some of their market operations, the government will be forced to come to their rescue.

Surowiecki, James, 2015, “Why the Rich Are So Much Richer,” The New York Review of Books LXII (14) (September 24), pp. 32–36. Suskind, Ronald, 2011, Confidence Men: Wall Street, Washington, and the Education of a President (New York, NY: HarperCollins Publishers). Tabellini, Guido and Torsten Persson, 2000, Fiscal Policy in Representative Governments (Cambridge: The MIT Press). Taleb, Nassim Nicholas, 2007, The Black Swan: The Impact of the High Improbable (New York: Random House). Tan Lin Mei and Greg Tower, 1992, “Readability of Tax Laws: An Empirical Study in New Zealand,” Australian Tax Forum 9 (3), pp. 355–372. Tanner, Michael D., 2007, Leviathan on the Right: How Big-Government Conservatism Brought Down the Republican Revolution (Washington, DC: Cato Institute).

See Financial institutions Barro, Robert, 61–64 Barroso, José Manuel, 113–14 Barter, 92 Basic goods, 48 Basic minimum income, 212, 392 Basic needs, 45–46, 49, 351 Bastiat, Frederic, 210 Basu, Kaushik, 399 The Beatles, 53 Becker, Gary, 34, 85 Beckert, Sven, 325 Beethoven, Ludwig van, 203 427 428 Belgium marginal tax rates in, 376 public spending in, 23, 53 welfare policies in, 214 Bentham, Jeremy, 1, 312 Berlusconi, Silvio, 395 Bernanke, Ben, 156 “Betterment taxes,” 194 Beveridge, William, 41–43 Bhutan, “happiness” in, 311–12 “Birth lottery,” 341, 349, 353 Bismarck, Otto von, 20, 22, 219 “Black swans,” 79 Blair, Tony, 113, 395 Bloomberg, 38, 298, 342, 350, 355–56 Bloomberg, Michael, 142 Boeing, 377 Bonuses, 82–83, 85–86 Boskin, Michael, 378–79 Brazil bureaucracy in, 234 Constitution, 269–71 corruption in, 120 economic planning in, 27 federalism in, 284 income inequality in, 221 Multiyear Plan, 234 regulations in, 173 welfare policies in, 212 Breyer, Stephen, 274–75 British Petroleum oil spill, 172–73 Brookings Institution, 370 Brynjolfsson, Erik, 356–57 Bubbles, 330–31 Buchanan, James generally, 7–8, 60–61, 394 on constitutions, 266, 272 on countercyclical policy, 62 on discretion, 71 on fiscal rules, 71–72 on informal norms, 286 on legal rules, 252 on limited role of government, 85, 313–14 on “political market,” 334 in School of Public Choice, 5, 6 on sovereign debt, 64 Buffet, Warren, 379 Bulgaria, Gini coefficient in, 317 Bureaucracy legal rules and, 253–54 public institutions and, 297–98 Bureaucratic state, 22 Burke, Edmund generally, 7–8 on constitutions, 270 Index on income redistribution, 215, 219, 300, 312–13 on role of government, 160, 189 Bush, George W., 84–85, 375 Cable, Don, 363, 364 Cajolement.


pages: 409 words: 105,551

Team of Teams: New Rules of Engagement for a Complex World by General Stanley McChrystal, Tantum Collins, David Silverman, Chris Fussell

Airbus A320, Albert Einstein, Apollo 11, Atul Gawande, autonomous vehicles, bank run, barriers to entry, Black Swan, Boeing 747, butterfly effect, call centre, Captain Sullenberger Hudson, Chelsea Manning, clockwork universe, crew resource management, crowdsourcing, driverless car, Edward Snowden, Flash crash, Frederick Winslow Taylor, global supply chain, Henri Poincaré, high batting average, Ida Tarbell, information security, interchangeable parts, invisible hand, Isaac Newton, Jane Jacobs, job automation, job satisfaction, John Nash: game theory, knowledge economy, Mark Zuckerberg, Mohammed Bouazizi, Nate Silver, Neil Armstrong, Pierre-Simon Laplace, pneumatic tube, radical decentralization, RAND corporation, scientific management, self-driving car, Silicon Valley, Silicon Valley startup, Skype, Steve Jobs, supply-chain management, systems thinking, The Wealth of Nations by Adam Smith, urban sprawl, US Airways Flight 1549, vertical integration, WikiLeaks, zero-sum game

We felt we had eyes on Rahman, and hoped to watch him patiently until he led us to Zarqawi, but we knew the dynamic could change any day. If we struck immediately, we could probably capture Rahman, but unless he cooperated almost immediately, Zarqawi would be alerted and disappear. If we waited and watched, there was a greater chance we would spook the adviser, Zarqawi might move for other reasons, or any number of “black swans” might arise and disrupt our scheme. To add further tension to our decision, massing enough surveillance assets to maintain unblinking surveillance of Rahman diverted us from other potential operations at a time when Baghdad was melting down. Information flowed; options were tabled and argued over.

In a resilience paradigm, managers accept the reality that they will inevitably confront unpredicted threats; rather than erecting strong, specialized defenses, they create systems that aim to roll with the punches, or even benefit from them. Resilient systems are those that can encounter unforeseen threats and, when necessary, put themselves back together again. Investor and writer Nassim Taleb captures a similar concept with the term “antifragile systems.” Fragile systems, he argues, are those that are damaged by shocks; robust systems weather shocks; and antifragile systems, like immune systems, can benefit from shocks. Though the concept’s popularity has increased in recent years, many resilience techniques are not new.

John McQuaid, “Dutch System of Flood Control an Engineering Marvel,” New Orleans Times-Picayune, November 13, 2005, http://www.nola.com/frontpage/t-p/index.ssf?/speced/ruinandrecovery/t-p/index.ssf?/speced/ruinandrecovery/articles/dutch13.html. floods are inevitable . . . Kuster, “From Control to Management,” 72. “command and control approach was not working” . . . Walker and Salt, 25. “fragilized” . . . Nassim Nicholas Taleb, Antifragile: Things That Gain from Disorder (New York: Random House, 2012), 5. “Humans are great optimizers” . . . Walker and Salt, 38. “robust-yet-fragile” . . . Andrew Zolli and Ann Marie Healy, Resilience: Why Things Bounce Back (New York: Simon & Schuster, 2012), 27. Egyptian pyramids . . .


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The Fifth Domain: Defending Our Country, Our Companies, and Ourselves in the Age of Cyber Threats by Richard A. Clarke, Robert K. Knake

"World Economic Forum" Davos, A Declaration of the Independence of Cyberspace, Affordable Care Act / Obamacare, air gap, Airbnb, Albert Einstein, Amazon Web Services, autonomous vehicles, barriers to entry, bitcoin, Black Lives Matter, Black Swan, blockchain, Boeing 737 MAX, borderless world, Boston Dynamics, business cycle, business intelligence, call centre, Cass Sunstein, cloud computing, cognitive bias, commoditize, computer vision, corporate governance, cryptocurrency, data acquisition, data science, deep learning, DevOps, disinformation, don't be evil, Donald Trump, Dr. Strangelove, driverless car, Edward Snowden, Exxon Valdez, false flag, geopolitical risk, global village, immigration reform, information security, Infrastructure as a Service, Internet of things, Jeff Bezos, John Perry Barlow, Julian Assange, Kubernetes, machine readable, Marc Benioff, Mark Zuckerberg, Metcalfe’s law, MITM: man-in-the-middle, Morris worm, move fast and break things, Network effects, open borders, platform as a service, Ponzi scheme, quantum cryptography, ransomware, Richard Thaler, Salesforce, Sand Hill Road, Schrödinger's Cat, self-driving car, shareholder value, Silicon Valley, Silicon Valley startup, Skype, smart cities, Snapchat, software as a service, Steven Levy, Stuxnet, technoutopianism, The future is already here, Tim Cook: Apple, undersea cable, unit 8200, WikiLeaks, Y2K, zero day

While anyone who bought Equifax on the way down and sold it before third-quarter results came in would have something to celebrate, everyone else impacted by the data breach would have tarred and feathered any executive at the company who claimed that they were resilient. For resilience to be a useful concept: In his book Antifragile, Nassim Taleb suggested that “antifragility” was the next evolution beyond resilience, that we want to form businesses and societies that are, in the words of Max Cleland, “strong at the broken places.” Antifragility is the right concept. But it was poor branding. Where the concept of The Black Swan, Taleb’s previous book, became widely used in business schools and boardrooms, antifragility never did. It’s unfortunate because it is the right concept. Rodin defines resilience as: Judith Rodin, The Resilience Dividend: Being Strong in a World Where Things Go Wrong (New York: PublicAffairs, 2014), 3.


pages: 307 words: 82,680

A Pelican Introduction: Basic Income by Guy Standing

"World Economic Forum" Davos, anti-fragile, bank run, basic income, behavioural economics, Bernie Sanders, Bertrand Russell: In Praise of Idleness, Black Lives Matter, Black Swan, Boris Johnson, British Empire, carbon tax, centre right, collective bargaining, cryptocurrency, David Graeber, declining real wages, degrowth, deindustrialization, Donald Trump, Elon Musk, Fellow of the Royal Society, financial intermediation, full employment, future of work, gig economy, Gunnar Myrdal, housing crisis, hydraulic fracturing, income inequality, independent contractor, intangible asset, Jeremy Corbyn, job automation, job satisfaction, Joi Ito, labour market flexibility, land value tax, libertarian paternalism, low skilled workers, lump of labour, Marc Benioff, Mark Zuckerberg, Martin Wolf, mass immigration, mass incarceration, moral hazard, Nelson Mandela, nudge theory, offshore financial centre, open economy, Panopticon Jeremy Bentham, Paul Samuelson, plutocrats, precariat, quantitative easing, randomized controlled trial, rent control, rent-seeking, Salesforce, Sam Altman, self-driving car, shareholder value, sharing economy, Silicon Valley, sovereign wealth fund, Stephen Hawking, The Future of Employment, universal basic income, Wolfgang Streeck, women in the workforce, working poor, Y Combinator, Zipcar

A study of children in Cherokee tribal families who received regular payments from the reservation’s casino earnings found that parents argued less (mainly because they were less likely to argue over money) while children suffered less from anxiety and behavioural disorders, did better at school and were less likely to drift into crime.20 A basic income would also strengthen personal resilience. Nassim Taleb has developed the idea of ‘anti-fragility’ in relation to coping with the shock of rare events, which he calls ‘black swans’.21 In his view, it is a mistake to try too hard to avoid shocks; an efficient economic system requires moderate volatility and disruption (perhaps coming from technological change) coupled with mechanisms that prepare people to deal with shocks.

Shafir (2013), Scarcity: Why Having Too Little Means So Much. London: Allen Lane. 19. World Bank (2015), World Development Report 2015: Mind, Society and Behaviour. Washington, DC: World Bank. 20. M. Velasquez-Manoff (2014), ‘What happens when the poor receive a stipend’, New York Times, 18 January. 21. N. N. Taleb (2012), Antifragile: How to Live in a World We Don’t Understand. New York: Random House. 22. M. Abu Sharkh and I. Stepanikova (2005), Ready to Mobilize? How Economic Security Fosters Pro-Activism Attitudes Instead of Apathy. Socio-Economic Security Programme Working Paper; Geneva: International Labour Organization. 23.


pages: 829 words: 186,976

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't by Nate Silver

airport security, Alan Greenspan, Alvin Toffler, An Inconvenient Truth, availability heuristic, Bayesian statistics, Bear Stearns, behavioural economics, Benoit Mandelbrot, Berlin Wall, Bernie Madoff, big-box store, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, book value, Broken windows theory, business cycle, buy and hold, Carmen Reinhart, Charles Babbage, classic study, Claude Shannon: information theory, Climategate, Climatic Research Unit, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, computer age, correlation does not imply causation, Credit Default Swap, credit default swaps / collateralized debt obligations, cuban missile crisis, Daniel Kahneman / Amos Tversky, disinformation, diversification, Donald Trump, Edmond Halley, Edward Lorenz: Chaos theory, en.wikipedia.org, equity premium, Eugene Fama: efficient market hypothesis, everywhere but in the productivity statistics, fear of failure, Fellow of the Royal Society, Ford Model T, Freestyle chess, fudge factor, Future Shock, George Akerlof, global pandemic, Goodhart's law, haute cuisine, Henri Poincaré, high batting average, housing crisis, income per capita, index fund, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), Internet Archive, invention of the printing press, invisible hand, Isaac Newton, James Watt: steam engine, Japanese asset price bubble, John Bogle, John Nash: game theory, John von Neumann, Kenneth Rogoff, knowledge economy, Laplace demon, locking in a profit, Loma Prieta earthquake, market bubble, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, Monroe Doctrine, mortgage debt, Nate Silver, negative equity, new economy, Norbert Wiener, Oklahoma City bombing, PageRank, pattern recognition, pets.com, Phillips curve, Pierre-Simon Laplace, Plato's cave, power law, prediction markets, Productivity paradox, proprietary trading, public intellectual, random walk, Richard Thaler, Robert Shiller, Robert Solow, Rodney Brooks, Ronald Reagan, Saturday Night Live, savings glut, security theater, short selling, SimCity, Skype, statistical model, Steven Pinker, The Great Moderation, The Market for Lemons, the scientific method, The Signal and the Noise by Nate Silver, The Wisdom of Crowds, Thomas Bayes, Thomas Kuhn: the structure of scientific revolutions, Timothy McVeigh, too big to fail, transaction costs, transfer pricing, University of East Anglia, Watson beat the top human players on Jeopardy!, Wayback Machine, wikimedia commons

Murrah Federal Building, 425 algorithms, 265, 426 all-in bet, 306 Allison, Graham, 433–35 Al Qaeda, 422, 424, 425, 426, 433, 435–36, 440, 444 Alzheimer’s, 420 Amazon.com, 352–53, 500 American exceptionalism, 10 American Football League (AFL), 185–86, 480 American League, 79 American Stock Exchange, 334 Amsterdam, 228 Anchorage, Alaska, 149 Anderson, Chris, 9 Angelo, Tommy, 324–26, 328 animals, earthquake prediction and, 147–48 Annals of Applied Statistics, 511–12 ANSS catalog, 478 Antarctic, 401 anthropology, 228 antiretroviral therapy, 221 Apple, 264 Archilochus, 53 Arctic, 397, 398 Arianism, 490 Aristotle, 2, 112 Armstrong, Scott, 380–82, 381, 388, 402–3, 405, 505, 508 Arrhenius, Svante, 376 artificial intelligence, 263, 293 Asia, 210 asset-price bubble, 190 asymmetrical information, 35 Augustine, Saint, 112 Australia, 379 autism, 218, 218, 487 availability heuristic, 424 avian flu, see bird flu A/Victoria flu strain, 205–6, 208, 483 Babbage, Charles, 263, 283 Babyak, Michael, 167–68 baby boom, 31 Babylonians, 112 Bachmann, Michele, 217 bailout bills, 19, 461 Bak, Per, 172 Baker, Dean, 22 Bane, Eddie, 87 Bank of England, 35 Barbour, Haley, 140 baseball, 9, 10, 16, 74–106, 128, 426, 446, 447, 451n aging curve in, 79, 81–83, 81, 83, 99, 164 betting on, 286 luck vs. skill in, 322 minor league system in, 92–93 results in, 327 rich data in, 79–80, 84 Baseball America, 75, 87, 89, 90, 90, 91 Baseball Encyclopedia, 94 Baseball Prospectus, 75, 78, 88, 297 basic reproduction number (R0), 214–15, 215, 224, 225, 486 basketball, 80n, 92–93, 233–37, 243, 246, 256, 258, 489 batting average, 86, 91, 95, 100, 314, 321, 321, 339 Bayer Laboratories, 11–12, 249 Bayes, Thomas, 240–43, 251, 253, 254, 255, 490 Bayesian reasoning, 240, 241–42, 259, 349, 444 biases and beliefs in, 258–59 chess computers’ use of, 291 Christianity and, 490 in climatology, 371, 377–78, 403, 406–7, 407, 410–11 consensus opinion and, 367 Fisher’s opposition to, 252 gambling esteemed in, 255–56, 362 priors in, 244, 245, 246, 252, 255, 258–59, 260, 403, 406–7, 433n, 444, 451, 490, 497 stock market and, 259–60 Bayes’s theorem, 15, 16, 242, 243–49, 246, 247, 248, 249, 250, 258, 266, 331, 331, 448–49, 450–51 in poker, 299, 301, 304, 306, 307, 322–23 Beane, Billy, 77, 92, 93–94, 99–100, 103, 105–7, 314 Bear Stearns, 37 beauty, complexity and, 173 beer, 387, 459 behavioral economics, 227–28 Belgium, 459 Bellagio, 298–99, 300, 318, 495 bell-curve distribution, 368n, 496 Bengkulu, Indonesia, 161 Benjamin, Joel, 281 Berlin, Isaiah, 53 Berners-Lee, Tim, 448, 514 BetOnSports PLC, 319 bets, see gambling Betsy, Hurricane, 140 betting markets, 201–3, 332–33 see also Intrade biases, 12–13, 16, 293 Bayesian theory’s acknowledgment of, 258–59 in chess, 273 and errors in published research, 250 favorite-longshot, 497 of Fisher, 255 objectivity and, 72–73 toward overconfidence, 179–83, 191, 203, 454 in polls, 252–53 as rational, 197–99, 200 of scouts, 91–93, 102 of statheads, 91–93 of weather forecasts, 134–38 Bible, 2 Wicked, 3, 13 Biden, Joseph, 48 Big Data, 9–12, 197, 249–50, 253, 264, 289, 447, 452 Big Short, The (Lewis), 355 Billings, Darse, 324 Bill James Baseball Abstract, The, 77, 78, 84 bin Laden, Osama, 432, 433, 434, 440, 509 binomial distribution, 479 biological weapons, 437, 438, 443 biomedical research, 11–12, 183 bird flu, 209, 216, 229 Black, Fisher, 362, 367, 369 “Black Friday,” 320 Black Swan, The (Taleb), 368n Black Tuesday, 349 Blanco, Kathleen, 140 Blankley, Tony, 50 Blodget, Henry, 352–54, 356, 364–65, 500 Blue Chip Economic Indicators survey, 199, 335–36 Bluefire, 110–11, 116, 118, 127, 131 bluffing, 301, 303, 306, 310, 311, 328 Bonus Baby rule, 94 books, 2–4 cost of producing, 2 forecasting and, 5 number of, 2–3, 3, 459 boom, dot-com, 346–48, 361 Boston, 77 Boston Red Sox, 63, 74–77, 87, 102, 103–5 Bowman, David, 161–62, 167 Box, George E.

* This is no surprise given how poor most of us—including most of us who invest for a living—are at estimating probabilities. The few who are good at it have the potential to clean up. However, most options traders receive a poor return, and it is a very risky activity on the whole. * As Nassim Nicholas Taleb detailed in The Black Swan and as Fama also discussed in his thesis, the movement of stock prices does not follow a gentle bell-curve distribution. Instead, stock-price movements are characterized by very occasional but very large swings up or down. The distribution of stock-market crashes can also be modeled fairly well by a power-law distribution, which is the same function that governs the frequency of earthquakes

Robert Shiller, the Yale economist, had noted its beginnings as early as 2000 in his book Irrational Exuberance.14 Dean Baker, a caustic economist at the Center for Economic and Policy Research, had written about the bubble in August 2002.15 A correspondent at the Economist magazine, normally known for its staid prose, had spoken of the “biggest bubble in history” in June 2005.16 Paul Krugman, the Nobel Prize–winning economist, wrote of the bubble and its inevitable end in August 2005.17 “This was baked into the system,” Krugman later told me. “The housing crash was not a black swan. The housing crash was the elephant in the room.” Ordinary Americans were also concerned. Google searches on the term “housing bubble” increased roughly tenfold from January 2004 through summer 2005.18 Interest in the term was heaviest in those states, like California, that had seen the largest run-up in housing prices19—and which were about to experience the largest decline.


pages: 254 words: 76,064

Whiplash: How to Survive Our Faster Future by Joi Ito, Jeff Howe

3D printing, air gap, Albert Michelson, AlphaGo, Amazon Web Services, artificial general intelligence, basic income, Bernie Sanders, Big Tech, bitcoin, Black Lives Matter, Black Swan, Bletchley Park, blockchain, Burning Man, business logic, buy low sell high, Claude Shannon: information theory, cloud computing, commons-based peer production, Computer Numeric Control, conceptual framework, CRISPR, crowdsourcing, cryptocurrency, data acquisition, deep learning, DeepMind, Demis Hassabis, digital rights, disruptive innovation, Donald Trump, double helix, Edward Snowden, Elon Musk, Ferguson, Missouri, fiat currency, financial innovation, Flash crash, Ford Model T, frictionless, game design, Gerolamo Cardano, informal economy, information security, interchangeable parts, Internet Archive, Internet of things, Isaac Newton, Jeff Bezos, John Harrison: Longitude, Joi Ito, Khan Academy, Kickstarter, Mark Zuckerberg, microbiome, move 37, Nate Silver, Network effects, neurotypical, Oculus Rift, off-the-grid, One Laptop per Child (OLPC), PalmPilot, pattern recognition, peer-to-peer, pirate software, power law, pre–internet, prisoner's dilemma, Productivity paradox, quantum cryptography, race to the bottom, RAND corporation, random walk, Ray Kurzweil, Ronald Coase, Ross Ulbricht, Satoshi Nakamoto, self-driving car, SETI@home, side project, Silicon Valley, Silicon Valley startup, Simon Singh, Singularitarianism, Skype, slashdot, smart contracts, Steve Ballmer, Steve Jobs, Steven Levy, Stewart Brand, Stuxnet, supply-chain management, synthetic biology, technological singularity, technoutopianism, TED Talk, The Nature of the Firm, the scientific method, The Signal and the Noise by Nate Silver, the strength of weak ties, There's no reason for any individual to have a computer in his home - Ken Olsen, Thomas Kuhn: the structure of scientific revolutions, Two Sigma, universal basic income, unpaid internship, uranium enrichment, urban planning, warehouse automation, warehouse robotics, Wayback Machine, WikiLeaks, Yochai Benkler

Elowitz and Stanislas Leibler, “A Synthetic Oscillatory Network of Transcriptional Regulators,” Nature 403, no. 6767 (January 20, 2000): 335–38, doi:10.1038/35002125. 27 Tom Knight, Randall Rettberg, Leon Chan, Drew Endy, Reshma Shetty, and Austin Che, “Idempotent Vector Design for the Standard Assembly of Biobricks,” http://people.csail.mit.edu/tk/sa3.pdf. 28 Interview with Jeff Howe. Chapter 2: Pull over Push 1 “Nuclear Meltdown Disaster,” Nova (PBS), season 42, episode 22. 2 Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable (London: Penguin UK, 2008). 3 David Nakamura and Chico Harlan, “Japanese Nuclear Plant’s Evaluators Cast Aside Threat of Tsunami,” Washington Post, March 23, 2011, https://www.washingtonpost.com/world/japanese-nuclear-plants-evaluators-cast-aside-threat-of-tsunami/2011/03/22/AB7Rf2KB_story.html. 4 Yuki Sawai, Yuichi Namegaya, Yukinobu Okamura, Kenji Satake, and Masanobu Shishikura, “Challenges of Anticipating the 2011 Tohoku Earthquake and Tsunami Using Coastal Geology,” Geophysical Research Letters 39, no. 21 (November 2012), doi:10.1029/2012GL053692. 5 Gwyneth Zakaib.

In twenty-two hours a tsunami traveled across the Pacific and struck Japan with great force. Waves fourteen feet high were reported, and more than 150 people died. These precautionary measures conformed to a kind of unassailable industrial-age logic. Earthquakes capable of generating such massive tsunamis are incredibly rare. Is it even possible to plan for so-called black swan events (incidents whose very rarity lull people into the false belief that the terminal disease will never strike their family, the market will never fail, and the government will not be overthrown)?2 In fact, if you adjust your field of observation, Japanese tsunami preparations constrained their view to recent history.

And that’s good, because maintaining a healthy relationship with uncertainty is one of the big themes that run through the principles. Mankind has been humbled during the last few years, but that’s nothing compared to what’s headed our way. Successful organizations will not, for instance, bet the house on quarterly sales predictions, knowing that a black swan could be just over the next pass. Instead they might not bet big at all, choosing to adopt a portfolio strategy in which small bets are made on a variety of products or markets or ideas. If the industrial era was about command-and-control management systems, hierarchies and facts, Network Age logic reflects decades in which we—Americans, but all humans as well—have reevaluated our place in the world.


pages: 290 words: 76,216

What's Wrong With Economics: A Primer for the Perplexed by Robert Skidelsky

additive manufacturing, agricultural Revolution, behavioural economics, Black Swan, Bretton Woods, business cycle, carbon tax, Cass Sunstein, central bank independence, cognitive bias, conceptual framework, Corn Laws, corporate social responsibility, correlation does not imply causation, creative destruction, Daniel Kahneman / Amos Tversky, David Ricardo: comparative advantage, degrowth, disruptive innovation, Donald Trump, Dr. Strangelove, full employment, George Akerlof, George Santayana, global supply chain, global village, Gunnar Myrdal, happiness index / gross national happiness, hindsight bias, Hyman Minsky, income inequality, index fund, inflation targeting, information asymmetry, Internet Archive, invisible hand, John Maynard Keynes: Economic Possibilities for our Grandchildren, Joseph Schumpeter, Kenneth Arrow, knowledge economy, labour market flexibility, loss aversion, Mahbub ul Haq, Mark Zuckerberg, market clearing, market friction, market fundamentalism, Martin Wolf, means of production, Modern Monetary Theory, moral hazard, paradox of thrift, Pareto efficiency, Paul Samuelson, Philip Mirowski, Phillips curve, precariat, price anchoring, principal–agent problem, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, shareholder value, Silicon Valley, Simon Kuznets, sunk-cost fallacy, survivorship bias, technoutopianism, The Chicago School, The Market for Lemons, The Nature of the Firm, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Thorstein Veblen, Tragedy of the Commons, transaction costs, transfer pricing, Vilfredo Pareto, Washington Consensus, Wolfgang Streeck, zero-sum game

For this critique, see Albert, 1976 12. Kaldor, 1961: 177–8 13. In a celebrated book, The Black Swan: The Impact of the Highly Improbable (2007), Nassim Taleb accused conventional economics of ignoring the possibility of extreme events, which he called black swans. The fact that all swans were not white has long been known, as in the poet Samuel Taylor Coleridge imagining joining nineteenth-century British convicts being transported to Australia: ‘Receive me, Lads! I’ll go with you, Hunt the black swan and kangaroo.’ 14. This is known as the Duhem-Quine theorem, which states that in order to test empirically an explicit hypothesis such as ‘X is caused by Y’, one must make additional implicit hypotheses such as ‘this is a valid test of whether X is caused by Y’, and ‘the testing instruments are accurate’. 15.


pages: 387 words: 119,409

Work Rules!: Insights From Inside Google That Will Transform How You Live and Lead by Laszlo Bock

Abraham Maslow, Abraham Wald, Airbnb, Albert Einstein, AltaVista, Atul Gawande, behavioural economics, Black Swan, book scanning, Burning Man, call centre, Cass Sunstein, Checklist Manifesto, choice architecture, citizen journalism, clean water, cognitive load, company town, correlation coefficient, crowdsourcing, Daniel Kahneman / Amos Tversky, deliberate practice, en.wikipedia.org, experimental subject, Fairchild Semiconductor, Frederick Winslow Taylor, future of work, Google Earth, Google Glasses, Google Hangouts, Google X / Alphabet X, Googley, helicopter parent, immigration reform, Internet Archive, Kevin Roose, longitudinal study, Menlo Park, mental accounting, meta-analysis, Moneyball by Michael Lewis explains big data, nudge unit, PageRank, Paul Buchheit, power law, Ralph Waldo Emerson, Rana Plaza, random walk, Richard Thaler, Rubik’s Cube, self-driving car, shareholder value, Sheryl Sandberg, side project, Silicon Valley, six sigma, statistical model, Steve Ballmer, Steve Jobs, Steven Levy, Steven Pinker, survivorship bias, Susan Wojcicki, TaskRabbit, The Wisdom of Crowds, Tony Hsieh, Turing machine, Wayback Machine, winner-take-all economy, Y2K

For example, most financial models used by banks up until the 2008 economic crisis assumed a normal distribution of stock market returns. O’Boyle and Aguinis explained: “When stock market performance is predicted using the normal curve, a single-day 10% drop in the financial markets should occur once every 500 years.… In reality, it occurs about once every 5 years.” Nassim Nicholas Taleb, in his book The Black Swan, made exactly this point, explaining that extreme events were much more likely than most banks’ models assumed.172 As a result, swings and downturns happen far more often than predicted when using a normal distribution, but about as often as you would expect using a power law or similar distribution.

Muldrow, “Impact of Valid Selection Procedures on Work-Force Productivity,” Journal of Applied Psychology 64, no. 6 (1979): 609–626. 171. Ernest O’Boyle Jr. and Herman Aguinis, “The Best and the Rest: Revisiting the Norm of Normality of Individual Performance,” Personnel Psychology 65, no. 1 (2012): 79–119. 172. Nassim Nicholas Taleb, The Black Swan (New York: Random House, 2007). 173. Storyboard, “Walt Disney’s Oscars,” The Walt Disney Family Museum, February 22, 2013, http://www.waltdisney.org/storyboard/walt-disneys-oscars%C2%AE. 174. Wikipedia, “List of Best-Selling Fiction Authors,” last modified April 19, 2014, http://en.wikipedia.org/wiki/List_of_best-selling_fiction_authors. 175.


pages: 292 words: 94,660

The Loop: How Technology Is Creating a World Without Choices and How to Fight Back by Jacob Ward

2021 United States Capitol attack, 4chan, Abraham Wald, AI winter, Albert Einstein, Albert Michelson, Amazon Mechanical Turk, assortative mating, autonomous vehicles, availability heuristic, barriers to entry, Bayesian statistics, Benoit Mandelbrot, Big Tech, bitcoin, Black Lives Matter, Black Swan, blockchain, Broken windows theory, call centre, Cass Sunstein, cloud computing, contact tracing, coronavirus, COVID-19, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, data science, deep learning, Donald Trump, drone strike, endowment effect, George Akerlof, George Floyd, hindsight bias, invisible hand, Isaac Newton, Jeffrey Epstein, license plate recognition, lockdown, longitudinal study, Lyft, mandelbrot fractal, Mark Zuckerberg, meta-analysis, natural language processing, non-fungible token, nudge unit, OpenAI, opioid epidemic / opioid crisis, pattern recognition, QAnon, RAND corporation, Richard Thaler, Robert Shiller, selection bias, self-driving car, seminal paper, shareholder value, smart cities, social contagion, social distancing, Steven Levy, survivorship bias, TikTok, Turing test

The mathematician Benoit Mandelbrot updated the model in a 1982 book about fractals to posit that comedians who have made appearances in the past are more likely to make them in the future. Nicholas Taleb carried Mandelbrot’s concept into his book Black Swan, and in his book Antifragile put a specific math to the notion that as an idea survives, its longevity increases. “Every year that passes without extinction doubles the additional life expectancy,” Taleb writes. In a sense, Goldman had identified the kind of law AI might use to evaluate the prospects of a comedian. This lineage of ideas suggests it’s very possible that human taste, and the market forces that seek to satisfy it, are bound by rules that truly can be expressed and perhaps even used to make predictions.


pages: 539 words: 139,378

The Righteous Mind: Why Good People Are Divided by Politics and Religion by Jonathan Haidt

affirmative action, Black Swan, classic study, cognitive bias, cognitive load, illegal immigration, impulse control, income inequality, index card, invisible hand, lateral thinking, meta-analysis, mirror neurons, Monkeys Reject Unequal Pay, Necker cube, Nelson Mandela, out of africa, Peter Singer: altruism, phenotype, Philippa Foot, Plato's cave, Ralph Waldo Emerson, Richard Thaler, Ronald Reagan, social intelligence, social web, stem cell, Steven Pinker, systems thinking, tech billionaire, The Spirit Level, theory of mind, Thomas Malthus, Timothy McVeigh, Tony Hsieh, Tragedy of the Commons, ultimatum game

See also Richerson and Boyd 2005 for a theory about how an earlier period of climatic instability may have driven the first jump in humanity’s transformation into cultural creatures, around 500,000 years ago. 88. Ambrose 1998. Whether or not this specific volcanic eruption changed the course of human evolution, I’m trying to make the larger point that evolution is not a smooth and gradual process, as is assumed in most computer simulations. There were probably many “black swan” events, the highly improbable events described by Taleb (2007) that disrupt our efforts to model processes with just a few variables and some assumptions based on “normal” conditions. 89. Potts and Sloan 2010. 90. The latter part of this period is when the archaeological record begins to show clear signs of decorated objects, beads, symbolic and quasi-religious activities, and tribal behavior more generally.

Sure You Do.” New York Times, Sunday Review, August 14. Sunstein, C. R. 2005. “Moral Heuristics.” Brain and Behavioral Science 28:531–73. Taber, C. S., and M. Lodge. 2006. “Motivated Skepticism in the Evaluation of Political Beliefs.” American Journal of Political Science 50:755–69. Taleb, N. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. Tan, J. H. W., and C. Vogel. 2008. “Religion and Trust: An Experimental Study.” Journal of Economic Psychology 29:832–48. Tattersall, I. 2009. The Fossil Trail: How We Know What We Think We Know About Human Evolution. 2nd ed.


pages: 323 words: 95,939

Present Shock: When Everything Happens Now by Douglas Rushkoff

"Hurricane Katrina" Superdome, algorithmic trading, Alvin Toffler, Andrew Keen, bank run, behavioural economics, Benoit Mandelbrot, big-box store, Black Swan, British Empire, Buckminster Fuller, business cycle, cashless society, citizen journalism, clockwork universe, cognitive dissonance, Credit Default Swap, crowdsourcing, Danny Hillis, disintermediation, Donald Trump, double helix, East Village, Elliott wave, European colonialism, Extropian, facts on the ground, Flash crash, Future Shock, game design, global pandemic, global supply chain, global village, Howard Rheingold, hypertext link, Inbox Zero, invention of agriculture, invention of hypertext, invisible hand, iterative process, James Bridle, John Nash: game theory, Kevin Kelly, laissez-faire capitalism, lateral thinking, Law of Accelerating Returns, Lewis Mumford, loss aversion, mandelbrot fractal, Marshall McLuhan, Merlin Mann, messenger bag, Milgram experiment, mirror neurons, mutually assured destruction, negative equity, Network effects, New Urbanism, Nicholas Carr, Norbert Wiener, Occupy movement, off-the-grid, passive investing, pattern recognition, peak oil, Peter Pan Syndrome, price mechanism, prisoner's dilemma, Ralph Nelson Elliott, RAND corporation, Ray Kurzweil, recommendation engine, scientific management, selective serotonin reuptake inhibitor (SSRI), Silicon Valley, SimCity, Skype, social graph, South Sea Bubble, Steve Jobs, Steve Wozniak, Steven Pinker, Stewart Brand, supply-chain management, technological determinism, the medium is the message, The Wisdom of Crowds, theory of mind, Tragedy of the Commons, Turing test, upwardly mobile, Whole Earth Catalog, WikiLeaks, Y2K, zero-sum game

Many of the “quant” teams at hedge funds and the risk-management groups within brokerage houses use fractals to find technical patterns in stock market movements. They believe that, unlike traditional measurement and prediction, these nonlinear, systems approaches transcend the human inability to imagine the unthinkable. Even Black Swan author Nassim Taleb, who made a career of warning economists and investors against trying to see the future, believes in the power of fractals to predict the sudden shifts and wild outcomes of real markets. He dedicated the book to Benoit Mandelbrot. While fractal geometry can certainly help us find strong, repeating patterns within the market activity of the 1930s Depression, it did not predict the crash of 2007.

See also narrative collapse stress: apocalypto and, 247, 250; on computers, 140n; digiphrenia and, 7, 73, 89, 100, 103, 121–22, 126, 128; narrative collapse and, 49, 65–66; overwinding and, 132, 136, 139, 140n, 144. See also tension/anxiety Surowiecki, James, 228 sync, digiphrenia and, 100–101, 106, 109, 121, 122, 126, 127, 128 systems theory, 200, 226–28 Taleb, Nassim, 229 Tarantino, Quentin, 30 Taylor, Frederick, 81 Tea Party, 53–55, 264 technology: apocalypto and, 249–50, 254, 255, 256–58, 259, 260, 263; development of new, 192; digiphrenia and, 7, 93–109; exploitation of, 30; fractalnoia and, 231–32; interactive, 211; narrative collapse and, 20, 30; new “now” and, 3; as partner in human evolution, 256–57; time as a, 76–87, 88–90; unintended consequences of, 249–50.


pages: 362 words: 99,063

The Education of Millionaires: It's Not What You Think and It's Not Too Late by Michael Ellsberg

affirmative action, Black Swan, Burning Man, corporate governance, creative destruction, do what you love, financial engineering, financial independence, follow your passion, future of work, hiring and firing, independent contractor, job automation, knowledge worker, lateral thinking, Lean Startup, Mark Zuckerberg, Max Levchin, means of production, mega-rich, meta-analysis, new economy, Norman Mailer, Peter Thiel, profit motive, race to the bottom, Sand Hill Road, shareholder value, side project, Silicon Valley, Silicon Valley billionaire, Skype, social intelligence, solopreneur, Steve Ballmer, survivorship bias, telemarketer, Tony Hsieh

In a more positive example, a few kids sitting in their Harvard dorm room (before they dropped out) launched a venture that changed, within a few years, the way much of the world socializes and communicates. That’s the globalized, interconnected world we live in now. Changes in one part of the system impact the entire system. Prepare for many more interruptions, shocks, surprises, global reorganizations, “black swans,” and totally unforeseen developments on this scale (both positive and negative). The “left field” out of which random and unpredictable events can come has just gone global.8 In this increasingly unpredictable and chaotic world, the wisest choice for thriving and flourishing is to focus your efforts on cultivating skills, habits, and ways of being that will work for you under a wide range of market circumstances and economic realities, and which will allow you to bounce back and adapt to changes, shifts, shocks, crashes, and new opportunities as they arise.

Later in his book, he argues that more hours in school training hard in academic subjects, not fewer hours, is essential for inner-city kids’ success. 6 Shapiro, p. 782. 7 Williams, accessed January 15, 2010. 8 Kleinfield, accessed October 9, 2009. 9 Pink (2001), locations 197–199 on Kindle edition. 10 Pink, locations 810–819 on Kindle edition. 11 Pink, location 843 on Kindle edition. ■ SUCCESS SKILL #1 1 Johnson, location 1035 on Kindle edition. 2 Johnson, locations 2696–2714 on Kindle edition. 3 Komisar, p. 154 4 Komisar, pp. 65–66. 5 For a detailed and brilliant exposition of survivorship bias, see Taleb. 6 Godin (2010 A), accessed April 3, 2010. 7 Moskovitz, accessed March 22, 2010. ■ SUCCESS SKILL #2 1 Cohen, accessed December 13, 2010. 2 Bertoni, accessed December 13, 2010. 3 One of his product lines, the David DeAngelo series of trainings for men, is quite controversial. The early trainings in the series focus on helping men “pick up” women through pickup lines, tricks, and cocky attitudes.

■ EPILOGUE 1 Munna, accessed January 29, 2011. 2 Taylor (2009 A), accessed January 29, 2011. 3 Taylor (2009 B), accessed January 29, 2011. 4 Reynolds, accessed January 31, 2011. 5 Segal, accessed January 31, 2011. 6 Thiel Foundation, accessed January 31, 2011. 7 Weisberg, accessed January 31, 2011. 8 For more on this topic, see Taleb. 9 Marmer, accessed April 12, 2011. 10 Herold, accessed March 17, 2011. INDEX Abramson, Josh Absolutepowerdating.com Academic degrees. See Higher education Ackoff, Russell AcroYoga Adams, Anthony Advice earning money from giving to mentors wake-up call, giving Andragogy Andros, Maria, success, evolution of Art of Earning a Living steps in See also Meaningful work, creating Asana.com Ash, David, success, evolution of Baby boomers Backpocketcoo.com Ballmer, Steve Banister, Cyan, success, evolution of Banister, Scott, outcome, focusing on Barry, Katie and Kerry Bencivenga, Gary, web site of Bisnow, Elliott on asking for advice as college non-graduate on contributing on mentors success, evolution of Summit Series Bisnow.com Blank, Steve Bloggers largest platform for making money vlogging Bootstrapping of capital and direct-response marketing elements of and financial stability investing method in of self-education success, case examples Brand marketing Brand of you building online defined versus having resume own name, using success, case examples Brandon, Craig Branson, Sir Richard Brown, James Buffett, Warren Burning Man festival Business Network International BustedTees California Leadership Center Capital bootstrapping of connection capital financial human capital Caples, John Carse, James Cash-generation ethic Cheng, Victor, sales coaching sessions by Cialdini, Robert Clarium Capital Clark, Brian, third tribe marketing Clason, George Clemens, Craig Clinton, Bill Colaizzi, Dr.


pages: 298 words: 43,745

Understanding Sponsored Search: Core Elements of Keyword Advertising by Jim Jansen

AltaVista, AOL-Time Warner, barriers to entry, behavioural economics, Black Swan, bounce rate, business intelligence, butterfly effect, call centre, Claude Shannon: information theory, complexity theory, content marketing, correlation does not imply causation, data science, en.wikipedia.org, first-price auction, folksonomy, Future Shock, information asymmetry, information retrieval, intangible asset, inventory management, life extension, linear programming, longitudinal study, machine translation, megacity, Nash equilibrium, Network effects, PageRank, place-making, power law, price mechanism, psychological pricing, random walk, Schrödinger's Cat, sealed-bid auction, search costs, search engine result page, second-price auction, second-price sealed-bid, sentiment analysis, social bookmarking, social web, software as a service, stochastic process, tacit knowledge, telemarketer, the market place, The Present Situation in Quantum Mechanics, the scientific method, The Wisdom of Crowds, Vickrey auction, Vilfredo Pareto, yield management

References ╇ [1] Jennings, P. 2004. “Persons of the Week: Larry Page and Sergey Brin,” ABC News. Retrieved April 4, 2011, from http://abcnews.go.com/WNT/PersonOfWeek/story?id=131833&page=1 ╇ [2] Hume, D. 1910. An Enquiry Concerning Human Understanding. Cambridge, MA: P.F. Collier & Son. ╇ [3] Taleb, N. N. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. ╇ [4] Brinker, S. 2010. Agile Marketing for Conversion Optimization. (May 24). Retrieved January 26, 2011, from http://searchengineland.com/agile-marketing-for-conversion-optimization37902 ╇ [5] Jansen, B. J., Zhang, M., Sobel, K., and Chowdhury, A. 2009.

Hume’s Problem of Induction questions whether one can predict that any event in the future will occur just because it occurred in the past. The induction problem entered pop culture via the book, The Black Swan, with [3]. the title being a classic example of induction from prior data [3 3]. For many years, it was widely believed that a black swan could not exist, because no European had ever seen one. Therefore, the prediction was that black swans cannot exist. However, black swans do exist, being native to Australia. Basically, in the end, we cannot prove that something will or will not occur just because it occurred or did not occur in the past.

., 116 BAM framework, 140 band wagon effect, 114 Banister, Scott, 11 banner ads, 10–11, 19 Battelle, John, 31 A Beautiful Mind, 197 behavior, 33–38, 44–45, 47–49, 54, 63, 66–67, 70–72, 74, 80–82, 85–87, 94, 99, 101, 115, 151, 155–161, 168, 170, 189, 196, 210–213, 220, 222, 224 behaviorism, 156–157, 170–171, 210, 213 behaviors, x, xi, 34–36, 38, 42–43, 45, 49, 55, 62, 71, 74–75, 86–88, 94, 99, 114–115, 152, 156–159, 161–163, 167, 171, 210–212, 221–222, 226 below the fold, 21, 43 Bernbach, Bill, 61 Bhatia, Sabeer, 134 bid, xxi, 4–5, 12, 14, 19–20, 39, 119–120, 141, 170, 178–182, 184–200, 203, 209 Bierbaum, E. G., 71 biologically programmed desires, 125 The Black Swan, 218 Bloom’s Taxonomy, 96 Borden, Neil H., 131 bounded rationality, 98, 100 Boyce, Rick, 10 brand, 6, 14–15, 25, 69–70, 74, 95, 103, 111–122, 126–127, 129–130, 140–142, 144, 201, 207, 221, 223, 225 brand advertising, 126 Brand attitude, 116 brand awareness, 113 brand equity, 114 brand familiarity, 116 brand image, 1, 14–15, 70, 103, 112–114, 117, 120, 141 Brand recall, 114, 117 Brand recognition, 113, 117 Brand relationship, 114–115, 117 273 274 Index Brand trust, 116–117 branded keyphrases, 119–120, 141, 183, 187 branded terms, 41, 69–70, 186 branding, xiii, 16, 65, 69, 103, 106, 111–114, 116–118, 120–121, 126, 128–129, 131, 135, 140–142, 149, 171, 177, 190, 199, 203, 207–209, 213, 227 Brewer, Jeffrey, 11 Brin, Sergey, 206, 217–218 Broder, Andrei, 44 Brooks, Nico, 76–77 Bullington, Brett, 12 butterfly effect, 205 buying decision, 98–99, 130 buying funnel, 86, 93–98, 101, 103–106, 129–130, 210, 213 Capitani, 74 Caples, John, 127 CA$HVERTISING, 125 causation, 153 caveat emptor, 179 chaos theory, 204 check-in applications, 224 choice set, 71, 79, 94, 120, 130 Choice uncertainty, 99 classic advertising appeals, 124 click fraud, 167–168, 170, 221 Click potential, 76 clickthrough lift, 124 click-through rate, 24, 74–75, 178, See€clickthrough rate, 14–15 The Cluetrain Manifesto, 129 Commercial Alert, 21 communication process, 32–33, 36, 54, 86, 101–103, 105–106, 111, 207, 210, 213 communication theory, 86 complexity theory, 204 comScore, 152 concept of chunking, 42 concept of technological innovation, 5 consumer behavior, xiii, 86, 89, 94, 96, 98, 101, 103, 105–106, 129 consumer buying behavior, 98, 103 consumer buying process, 94, 98, 100–101, 104, 106 consumer decision making, 86, 93–95, 101, 105, 208, 213 consumer purchasing behavior, 86 consumer search process, 48, 90, 93, 98 consumer searching, 41, 47, 63, 86–87, 90, 93, 95, 98–99, 210 consumer searching behavior, 41, 86, 95, 210 content targeting, 19 context, ix, x, xiii, xix, xx, xxi, 1, 11, 32–33, 36, 43, 69, 86, 88, 91–92, 97, 100–103, 106, 112, 114–115, 119, 126–128, 131, 157, 159–164, 166, 177, 187, 212, 217, 220, 224, 226 contextual advertising, xii, 19, 225 Conversion potential, 76 Corporate branding, 112 Correlation, 153 Credence goods, 39–40 creditability, 150 Culliton, James, 131 curiosity, i, ix, x, xiv, 46, 125 Customer brand image, 120 customer market segmentation, 120 Database of Intentions, 31 dayparting, 184, 186 Delhagen, Kate, 12 determinants, 92–93, 98, 118 Direct Hit Technologies, 21 direct response, 126 direct response advertising, 126 Doc Seals, 129 dominate, 125 east, 22, 24, 72 ebay, 179 Ebbinghaus, H., 74 economic theory, 49, 91 effectiveness, 24, 35, 113, 118, 145, 149, 151, 159, 170, 180, 210 efficiency, 62, 151, 170, 180, 210 empirical methods, xii erosion, 159–160 escape, 125 Esch, F.


pages: 1,073 words: 314,528

Strategy: A History by Lawrence Freedman

Albert Einstein, anti-communist, Anton Chekhov, Ayatollah Khomeini, barriers to entry, battle of ideas, behavioural economics, Black Swan, Blue Ocean Strategy, British Empire, business process, butterfly effect, centre right, Charles Lindbergh, circulation of elites, cognitive dissonance, coherent worldview, collective bargaining, complexity theory, conceptual framework, Cornelius Vanderbilt, corporate raider, correlation does not imply causation, creative destruction, cuban missile crisis, Daniel Kahneman / Amos Tversky, defense in depth, desegregation, disinformation, Dr. Strangelove, Edward Lorenz: Chaos theory, en.wikipedia.org, endogenous growth, endowment effect, escalation ladder, Ford Model T, Ford paid five dollars a day, framing effect, Frederick Winslow Taylor, Gordon Gekko, greed is good, Herbert Marcuse, Herman Kahn, Ida Tarbell, information retrieval, interchangeable parts, invisible hand, John Nash: game theory, John von Neumann, Kenneth Arrow, lateral thinking, linear programming, loose coupling, loss aversion, Mahatma Gandhi, means of production, mental accounting, Murray Gell-Mann, mutually assured destruction, Nash equilibrium, Nelson Mandela, Norbert Wiener, Norman Mailer, oil shock, Pareto efficiency, performance metric, Philip Mirowski, prisoner's dilemma, profit maximization, race to the bottom, Ralph Nader, RAND corporation, Richard Thaler, road to serfdom, Ronald Reagan, Rosa Parks, scientific management, seminal paper, shareholder value, social contagion, social intelligence, Steven Pinker, strikebreaker, The Chicago School, The Myth of the Rational Market, the scientific method, theory of mind, Thomas Davenport, Thomas Kuhn: the structure of scientific revolutions, Torches of Freedom, Toyota Production System, transaction costs, Twitter Arab Spring, ultimatum game, unemployed young men, Upton Sinclair, urban sprawl, Vilfredo Pareto, W. E. B. Du Bois, War on Poverty, women in the workforce, Yogi Berra, zero-sum game

This reinforces the tendency to neglect factors about which little is known, thereby encouraging overconfidence.14 These flawed stories of the past shape our predictions of the future. In this he draws attention to the work of Nassim Taleb, who stresses the importance of unexpected and random events (which he calls “black swans”) for which inadequate provision has been made because they are so out of line with past experience. Yet Taleb also acknowledges a contradiction in his method, for although he points to forms of narrative fallacy he also uses stories “to illustrate our gullibility about stories and our preference for the dangerous compression of narratives.”

Naomi Lamoreaux, “Reframing the Past: Thoughts About Business Leadership and Decision Making Under Certainty,” Enterprise and Society 2 (December 2001): 632–659. 13. Daniel M. G. Raff, “How to Do Things with Time,” Enterprise and Society 14, no. 3 (forthcoming, September 2013). 14. Daniel Kahneman, Thinking Fast and Slow, 199, 200–201 206, 259 (see chap. 38, n. 44). 15. Nassim Taleb, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2007), 8. 16. Joseph Davis, ed., Stories of Change: Narrative and Social Movements (New York: State University of New York Press, 2002). 17. Francesca Polletta, It Was Like a Fever, see Chapter 27, n. 1, 166. 18. Joseph Davis, ed., Stories of Change: Narrative and Social Movements (New York: State University of New York Press, 2002). 19.

., “The Changing Face of War,” The Marine Corps Gazette, October 1989, 22–26, available at http://zinelibrary.info/files/TheChangingFaceofWar-onscreen.pdf. 34. Ralph Peters, “The New Warrior Class,” Parameters 24, no. 2 (Summer 1994): 20. 35. Joint Publication 3–13, Information Operations, March 13, 2006. 36. Nik Gowing, ‘Skyful of Lies’ and Black Swans: The New Tyranny of Shifting Information Power in Crises (Oxford, UK: Reuters Institute for the Study of Journalism, 2009). 37. John Arquilla and David Ronfeldt, “Cyberwar is Coming!” Comparative Strategy 12, no. 2 (Spring 1993): 141–165. 38. Steve Metz, Armed Conflict in the 21st Century: The Information Revolution and Post-Modern Warfare (April 2000): “Future war may see attacks via computer viruses, worms, logic bombs, and trojan horses rather than bullets, bombs, and missiles.” 39.


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Connectography: Mapping the Future of Global Civilization by Parag Khanna

"World Economic Forum" Davos, 1919 Motor Transport Corps convoy, 2013 Report for America's Infrastructure - American Society of Civil Engineers - 19 March 2013, 9 dash line, additive manufacturing, Admiral Zheng, affirmative action, agricultural Revolution, Airbnb, Albert Einstein, amateurs talk tactics, professionals talk logistics, Amazon Mechanical Turk, Anthropocene, Asian financial crisis, asset allocation, autonomous vehicles, banking crisis, Basel III, Berlin Wall, bitcoin, Black Swan, blockchain, borderless world, Boycotts of Israel, Branko Milanovic, BRICs, British Empire, business intelligence, call centre, capital controls, Carl Icahn, charter city, circular economy, clean water, cloud computing, collateralized debt obligation, commoditize, complexity theory, continuation of politics by other means, corporate governance, corporate social responsibility, credit crunch, crony capitalism, crowdsourcing, cryptocurrency, cuban missile crisis, data is the new oil, David Ricardo: comparative advantage, deglobalization, deindustrialization, dematerialisation, Deng Xiaoping, Detroit bankruptcy, digital capitalism, digital divide, digital map, disruptive innovation, diversification, Doha Development Round, driverless car, Easter island, edge city, Edward Snowden, Elon Musk, energy security, Ethereum, ethereum blockchain, European colonialism, eurozone crisis, export processing zone, failed state, Fairphone, Fall of the Berlin Wall, family office, Ferguson, Missouri, financial innovation, financial repression, fixed income, forward guidance, gentrification, geopolitical risk, global supply chain, global value chain, global village, Google Earth, Great Leap Forward, Hernando de Soto, high net worth, high-speed rail, Hyperloop, ice-free Arctic, if you build it, they will come, illegal immigration, income inequality, income per capita, industrial cluster, industrial robot, informal economy, Infrastructure as a Service, interest rate swap, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Isaac Newton, Jane Jacobs, Jaron Lanier, John von Neumann, Julian Assange, Just-in-time delivery, Kevin Kelly, Khyber Pass, Kibera, Kickstarter, LNG terminal, low cost airline, low earth orbit, low interest rates, manufacturing employment, mass affluent, mass immigration, megacity, Mercator projection, Metcalfe’s law, microcredit, middle-income trap, mittelstand, Monroe Doctrine, Multics, mutually assured destruction, Neal Stephenson, New Economic Geography, new economy, New Urbanism, off grid, offshore financial centre, oil rush, oil shale / tar sands, oil shock, openstreetmap, out of africa, Panamax, Parag Khanna, Peace of Westphalia, peak oil, Pearl River Delta, Peter Thiel, Philip Mirowski, Planet Labs, plutocrats, post-oil, post-Panamax, precautionary principle, private military company, purchasing power parity, quantum entanglement, Quicken Loans, QWERTY keyboard, race to the bottom, Rana Plaza, rent-seeking, reserve currency, Robert Gordon, Robert Shiller, Robert Solow, rolling blackouts, Ronald Coase, Scramble for Africa, Second Machine Age, sharing economy, Shenzhen special economic zone , Shenzhen was a fishing village, Silicon Valley, Silicon Valley startup, six sigma, Skype, smart cities, Smart Cities: Big Data, Civic Hackers, and the Quest for a New Utopia, South China Sea, South Sea Bubble, sovereign wealth fund, special economic zone, spice trade, Stuxnet, supply-chain management, sustainable-tourism, systems thinking, TaskRabbit, tech worker, TED Talk, telepresence, the built environment, The inhabitant of London could order by telephone, sipping his morning tea in bed, the various products of the whole earth, Tim Cook: Apple, trade route, Tragedy of the Commons, transaction costs, Tyler Cowen, UNCLOS, uranium enrichment, urban planning, urban sprawl, vertical integration, WikiLeaks, Yochai Benkler, young professional, zero day

Peterson Institute for International Economics, 2013. Sudjic, Deyan. Hundred Mile City. Mariner Books, 1993. Sunstein, Cass R. Infotopia: How Many Minds Produce Knowledge. Oxford University Press, 2008. ———. Simpler: The Future of Government. Simon & Schuster, 2013. Taleb, Nassim Nicholas. Antifragile: Things That Gain from Disorder. Random House Trade Paperbacks, 2014. ———. The Black Swan. Random House, 2010. Taniguchi, Eiichi, Tien Fang Fwa, and Russell G. Thompson. Urban Transportation and Logistics: Health, Safety, and Security Concerns. CRC Press, 2013. Tansey, Oisin. “Internationalized Regimes: A Second Dimension of Regime Hybridity.”

Others speak of value webs or value networks to capture the wide range of participants involved in supply chains and their interdependent and mutually beneficial nature. *8 I use “supply chain world” or “supply-demand world” or “supply-demand system” or other variations interchangeably. *9 In his book Antifragile, Nassim Taleb demonstrates through the convexity principle that the degradation effect (harm) diminishes across a range of smaller units as opposed to a larger one of size equal to the sum of the smaller units. *10 Solids, liquids, and gases experience flow and friction when moving in the open or in contained spaces.

It seems almost offensive to list them in one paragraph, but my appreciation for their brilliance and friendship goes beyond anything I can write: Graham Allison, Benjamin Barber, Eric Beinhocker, Daniel Bell, Ian Bremmer, Ann Florini, Tom Friedman, Robert Kaplan, Pratap Mehta, Pankaj Mishra, Charles Pirtle, Carne Ross, John Ruggie, Saskia Sassen, Richard Sennett, Nassim Taleb, and Scott Malcomson, who has edited my essays for close to a decade and kindly reviewed several chapters of this book as well. Friends have witnessed many times the fine line crossed from casual banter to intense debate, usually marked by the unsheathing of my Moleskine notepad. Beyond the innocent bystanders caught in the cross fire, I want to single out those who have been consistent partners in productive discourse: Ozi Amanat, David Anderson, Scott Anthony, Matt Armstrong, Alex Bernard, Neel Chowdhury, Laura Deal, Jon Fasman, Howard French, Jared Genser, Jan-Philipp Goertz, Jeremy Grant, Nisid Hajari, Niels Hartog, Seb Kaempf, Gaurang Khemka, Karan Khemka, Bernd Kolb, Mark Leonard, Greg Lindsay, Shaun Martin, Ann Mettler, Chandran Nair, Madhu Narasimhan, Pradeep Ramamurthy, Abhijnan Rej, Tom Sanderson, Rana Sarkar, Lutfey Siddiqi, David Skilling, Nick Snyder, Robert Steele, Dorjee Sun, Vijay Vaitheeswaran, Kirk Wagar, Chris Wilson, Art Winter, Jan Zielonka, and Teddy Zmrhal.


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Inflated: How Money and Debt Built the American Dream by R. Christopher Whalen

Alan Greenspan, Albert Einstein, bank run, banking crisis, Bear Stearns, Black Swan, book value, Bretton Woods, British Empire, business cycle, buy and hold, California gold rush, Carl Icahn, Carmen Reinhart, central bank independence, classic study, commoditize, conceptual framework, Cornelius Vanderbilt, corporate governance, corporate raider, creative destruction, cuban missile crisis, currency peg, debt deflation, falling living standards, fiat currency, financial deregulation, financial innovation, financial intermediation, floating exchange rates, Ford Model T, Fractional reserve banking, full employment, Glass-Steagall Act, global reserve currency, housing crisis, interchangeable parts, invention of radio, Kenneth Rogoff, laissez-faire capitalism, land bank, liquidity trap, low interest rates, means of production, military-industrial complex, Money creation, money: store of value / unit of account / medium of exchange, moral hazard, mutually assured destruction, Nixon triggered the end of the Bretton Woods system, non-tariff barriers, oil shock, Paul Samuelson, payday loans, plutocrats, price stability, pushing on a string, quantitative easing, rent-seeking, reserve currency, Ronald Reagan, Savings and loan crisis, special drawing rights, Suez canal 1869, Suez crisis 1956, The Chicago School, The Great Moderation, too big to fail, trade liberalization, transcontinental railway, Upton Sinclair, women in the workforce

Friedman, Benjamin, “Postwar Changes in the American Financial Markets,” NBER Working Paper No. 458, March 1981, Issued in March 1981. 16. Whalen, Richard J., “The Shifting Equation of Nuclear Defense,” Fortune (June 1, 1967). 17. Morgan, Iwan, Deficit Government: Taxing and Spending in Modern America (Chicago: Ivan R. Dee, 1995), ix. 18. Taleb, Nassim, The Black Swan: The Impact of the Highly Improbable (New York: Random House, 2008). 19. Baldwin, Robert E., The Changing Nature of U.S. Trade Policy Since WWII (University of Chicago Press, 1984), 5–7. 20. Lake, David, The International Political Economy of Trade, Vol. I, (Cheltenham: Edward Elgar Publishing, 1993), 8–10. 21.

Members of both major political parties in the United States became convinced that deficit spending would employ unused resources correct market failures, and produce optimal economic results. This narrative, this deliberate act of collective delusion, has governed the direction of the U.S. economy ever since. The author Nassim Taleb talks about the importance of narrative in how human beings come to believe that they understand a complex issue: The narrative fallacy addresses our limited ability to look at sequences of facts without weaving an explanation into them, or, equivalently, forcing a logical link, an arrow of relationship, upon them.

Stevenson, Adlai Stewart, John Fat Years and the Lean Stewart, William Silver Knight (pamphlet) Stillman, James Stock investment New Era theory perspective, change Stock markets human nature, impact purchases (financing), short-term loans (usage) Stocks, decline Strong, Benjamin Bankers Trust Company exit Delano/House meeting Morgan control replacement Strong, William Subprime debt bubble, blame Subprime Debt Crisis (2008) Subprime debt crisis, Fed/Treasury assistance Subprime financial crisis, perspective (Raynes) Subprime housing crisis (2007-2009), issues Suez Canal, closing (1956) Sugar Equalization Board Summers, Larry Swanberg, W.A. Sylla, Richard Systemic risk, moral dilemma Szymczak, M.S. Taft, William Howard government debt Taleb, Nassim Tammany Hall Roosevelt, impact Tansil, Charles Callan America Goes to War Tariffs competitiveness, FDR promise FDR maintenance imposition increase protection, increase reduction FDR endorsement Hoover opposition Republican party position Tariffs for revenue only Taxes FDR increase reduction, passage Tennessee Iron & Coal Company U.S.


pages: 354 words: 26,550

High-Frequency Trading: A Practical Guide to Algorithmic Strategies and Trading Systems by Irene Aldridge

algorithmic trading, asset allocation, asset-backed security, automated trading system, backtesting, Black Swan, Brownian motion, business cycle, business process, buy and hold, capital asset pricing model, centralized clearinghouse, collapse of Lehman Brothers, collateralized debt obligation, collective bargaining, computerized trading, diversification, equity premium, fault tolerance, financial engineering, financial intermediation, fixed income, global macro, high net worth, implied volatility, index arbitrage, information asymmetry, interest rate swap, inventory management, Jim Simons, law of one price, Long Term Capital Management, Louis Bachelier, machine readable, margin call, market friction, market microstructure, martingale, Myron Scholes, New Journalism, p-value, paper trading, performance metric, Performance of Mutual Funds in the Period, pneumatic tube, profit motive, proprietary trading, purchasing power parity, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk free rate, risk tolerance, risk-adjusted returns, risk/return, Sharpe ratio, short selling, Small Order Execution System, statistical arbitrage, statistical model, stochastic process, stochastic volatility, systematic trading, tail risk, trade route, transaction costs, value at risk, yield curve, zero-sum game

Risk Management 257 founder of the hedge fund Greenlight Capital, stated that VaR was “relatively useless as a risk-management tool and potentially catastrophic when its use creates a false sense of security among senior managers and watchdogs. This is like an air bag that works all the time, except when you have a car accident.” The article also quoted Nassim Nicholas Taleb, the bestselling author of The Black Swan, as calling VaR metrics “a fraud.” Jorion (2000) points out that the VaR approach both presents a faulty measure of risk and actively pushes strategists to bet on extreme events. Despite all the criticism, VaR and ES have been mainstays of corporate risk management for years, where they present convenient reporting numbers.

., 142, 147, 192, 195, 279 Suleiman, Basak, 260 Summers, Lawrence, 179 Swap trading: fixed-income markets, 40–42 foreign exchange markets, 43–46 Sycara, K., 279–280 Systematic trading, 15 distinguished from high-frequency trading, 18–19 System testing, automated system implementation, 248–249 INDEX Tail risk, 50 comparative ratios and, 56 risk measurement and, 257–258 Take-profit orders, 70, 73 Taleb, Nassim Nicholas, 257 Tamirisa, N.T., 183 Taskin, F., 183 Tâtonnement (trial and error), in price adjustments, 127–128 Tauchen, George, 125 Taxes, post-trade analysis of, 288 Taylor series expansion (bilinear models), 109–110 Technical analysis, 22–23 evolution of, 13–14, 15 inventory trading, 142–143 Technological innovation, financial markets and evolution of high-frequency trading, 7–13 Technology and High-Frequency Trading Survey, 21 Tepla, Lucie, 260 Testing methods, for market efficiency and predictability, 79–89 autoregression-based tests, 86 co-integration-based tests, 89 Martingale hypothesis and, 86–88 non-parametric runs test, 80–82 random walks tests, 82–86 Teversky, A., 253 Thaler, R., 87 Theissen, Eric, 142 Third-party research, 26 Thomson/Reuters, 25 Threshold autoregressive (TAR) models, 110 Tick data, 21, 115–125 bid-ask bounce and, 120–121 bid-ask spreads and, 118–120 duration models of arrival, 121–123 econometric techniques applied to, 123–125 properties of, 116–117 quantity and quality of, 117–118 Time distortion, automated system implementation, 243–245 Time-weighted average price (TWAP), 297 339 Index Timing risk costs, 293–294 Timing specifications, for orders, 68 Tiwari, A., 139 Tkatch, Isabel, 67, 132, 274, 277–278 Todd, P., 214 Tower Research Capital, 24 TRADE Group survey, 17–18 Trading methodology, evolution of, 13–19 Trading platform, 31 Trading software, 25 Trading strategy accuracy (TSA) back-testing method, 222–231 Trailing stop, 267 Transaction costs: information-based trading, 149–151 market microstructure trading, inventory models, 128–129 market versus limit orders, 62–63 portfolio optimization, 206–208 post-trade analysis of, 283–295 Transparent execution costs, 34, 284, 285–288 Treynor ratio, 51, 52t, 55 Triangular arbitrage, foreign exchange markets, 190 Uncovered interest parity arbitrage, foreign exchange markets, 191 Unit testing, automated system implementation, 247 Uppal, R., 210 Upside Potential Ratio, 53t, 56 Use case testing, automated system implementation, 249 U.S.


pages: 350 words: 109,220

In FED We Trust: Ben Bernanke's War on the Great Panic by David Wessel

Alan Greenspan, Asian financial crisis, asset-backed security, bank run, banking crisis, banks create money, Bear Stearns, Berlin Wall, Black Swan, break the buck, business cycle, central bank independence, credit crunch, Credit Default Swap, crony capitalism, debt deflation, Fall of the Berlin Wall, financial engineering, financial innovation, financial intermediation, fixed income, full employment, George Akerlof, Glass-Steagall Act, Greenspan put, housing crisis, inflation targeting, information asymmetry, junk bonds, London Interbank Offered Rate, Long Term Capital Management, low interest rates, market bubble, Michael Milken, money market fund, moral hazard, mortgage debt, new economy, Northern Rock, price stability, quantitative easing, Robert Shiller, Ronald Reagan, Saturday Night Live, Savings and loan crisis, savings glut, Socratic dialogue, too big to fail

Indeed, one reason investors were willing to pay so much for risky securities was that they believed — or acted as if they believed — that the Fed and other central banks had found a way to keep economies growing with little inflation and with recessions that were mild and infrequent. But Nassim Nicholas Taleb, an options trader who made his reputation by describing unanticipated but unusually important events that he called “black swans,” criticizes Greenspan — and Bernanke — for failing to see that the calm was masking a building of hidden risks. “It was like someone sitting on dynamite and saying, ‘It’s okay, we’re safe because nothing has happened.’” Despite its apparent successes, the Greenspan Fed had some well-respected contemporary critics.

Calomiris, “The Subprime Turmoil: What’s Old, What’s New and What’s Next,” Jackson Hole, Wyoming, October 2, 2008. http://www.kc.frb.org/publicat/sympos/2008/ Calomiris.08.20.08.pdf 57 “make sense tactically” Transcript, FOMC meeting, June 24-25, 2003.http://www.federalreserve.gov/ monetarypolicy/fomchistorical2003.htm 57 “It was like someone” “Outspoken: A Conversation with Nassim Nicholas Taleb,” Washington Post, March 15, 2009, B2. 58 “an eventual crisis” William R. White, “Is Price Stability Enough?” Bank for International Settlements, April 2006. http://www.bis.org/publ/work205.pdf 58 “We tried in 2004” Greg Ip and Jon Hilsenrath, “Debt Bomb: Inside the Subprime Mortgage Debacle,” Wall Street Journal, August 7, 2007, A1. 58 “I will stipulate” Transcript, FOMC meeting, August 12, 2003. http://www.federalreserve.gov/monetarypolicy/ fomchistorical2003.htm 59 the Wall Street Journal: “WSJ Forecasting Survey — March 2008,” Wall Street Journal. http://online.wsj.com/public/resources/documents/ wsjecon0308.xls 59 A 2004 Fed working paper: Joshua Gallin, “The Long-Run Relationship between House Prices and Rents,” Board of Governors of Federal Reserve System, September 2004. http://www.federalreserve.gov/pubs/feds/2004/200450/ 200450pap.pdf 59 “I would tell audiences” Alan Greenspan, The Age of Turbulence: Adventures in a New World (New York: Penguin Press, 2007), 232. 60 “We cannot practice” Transcript, Federal Reserve Bank of Kansas City, Jackson Hole Conference, August 2008. http://www.kc.frb.org/PUBLICAT/SYMPOS/1999/ sym99prg.htm 61 “He didn’t say anything” John Cassidy, “Anatomy of a Meltdown,” The New Yorker, December 1, 2008. http://www.newyorker.com/reporting/2008/12/01/ 081201fa_fact_cassidy?


pages: 369 words: 80,355

Too Big to Know: Rethinking Knowledge Now That the Facts Aren't the Facts, Experts Are Everywhere, and the Smartest Person in the Room Is the Room by David Weinberger

airport security, Alfred Russel Wallace, Alvin Toffler, Amazon Mechanical Turk, An Inconvenient Truth, Berlin Wall, Black Swan, book scanning, Cass Sunstein, commoditize, Computer Lib, corporate social responsibility, crowdsourcing, Danny Hillis, David Brooks, Debian, double entry bookkeeping, double helix, Dr. Strangelove, en.wikipedia.org, Exxon Valdez, Fall of the Berlin Wall, future of journalism, Future Shock, Galaxy Zoo, Gregor Mendel, Hacker Ethic, Haight Ashbury, Herman Kahn, hive mind, Howard Rheingold, invention of the telegraph, Jeff Hawkins, jimmy wales, Johannes Kepler, John Harrison: Longitude, Kevin Kelly, Large Hadron Collider, linked data, Neil Armstrong, Netflix Prize, New Journalism, Nicholas Carr, Norbert Wiener, off-the-grid, openstreetmap, P = NP, P vs NP, PalmPilot, Pluto: dwarf planet, profit motive, Ralph Waldo Emerson, RAND corporation, Ray Kurzweil, Republic of Letters, RFID, Richard Feynman, Ronald Reagan, scientific management, semantic web, slashdot, social graph, Steven Pinker, Stewart Brand, systems thinking, technological singularity, Ted Nelson, the Cathedral and the Bazaar, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, Whole Earth Catalog, X Prize

Thank you to Barbara Tillett, also at the Library, for her help. 9 See http://www.trancheproject.org. 10 Interview with John Wilbanks. 11 Southan and Cameron, “Beyond the Tsunami,” p. 117–118. 12 Hiroaki Kitano, “Systems Biology: A Brief Overview,” Science 295, no. 5560 (March 1, 2002): 1662–1664. 13 For a superb introduction, see Steven Johnson, Emergence (Scribner, 2001). 14 See http://www.icosystem.com/labsdemos/the-game/. 15 Eric Bonabeau, “Agent-Based Modeling: Methods and Techniques for Simulating Human Systems,” Proceedings of the National Academy of Sciences 99, suppl. 3 (May 14, 2002): 7280–7287, www.pnas.org/cgi/doi/0.1073/pnas.082080899. 16 Kellan Davidson, “Eureqa and Technological Singularity,” Ithaca Action News, May 12, 2010, http://ithacaactionnews.wordpress.com/2010/05/12/eureqa-and-technological-singularity/. 17 Quoted in Brandon Keim, “Download Your Own Robot Scientist,” Wired Science, December 3, 2009, http://www.wired.com/wiredscience/2009/12/download-robot-scientist/#ixzz0vrP0I4G9. See also the exceptional RadioLab program on this topic: “Limits of Science,” April 16, 2010, http://www.wnyc.org/shows/radiolab/episodes/2010/04/16/segments/149570. 18 Nicholas Taleb Nassim, The Black Swan (Random House, 2007). 19 The story may be apocryphal, according to a report by Nicholas Wade in “A Family Feud over Mendel’s Manuscript on the Laws of Heredity,” May 31, 2010, http://philosophyofscienceportal.blogspot.com/2010/06/gregor-mendel-and-pea-breeding.html. 20 Jennifer Laing, “Comet Hunter,” Universe Today, December 11, 2001, http://www.universetoday.com/html/articles/2001–1211a.html. 21 Jennifer Ouellette, “Astronomy’s Amateurs a Boon for Science,” Discovery News, September 20, 2010, http://news.discovery.com/space/astronomys-amateurs-a-boon-for-science.html. 22 Mark Frauenfelder, “The Return of Amateur Science,” Boing Boing, December 22, 2008, http://www.good.is/post/the-return-of-amateur-science/. 23 Thanks to the people who responded to the request for examples I posted on my Web site: Garrett Coakley, Jeremy Price, Miriam Simun, Andrew Weinberger, Jim Richardson, and Lars Ludwig.

And the solution to this problem is the Eureqa project.”17 The world’s complexity may simply outrun our brain’s capacity to understand it. Model-based knowing has many well-documented difficulties, especially when we are attempting to predict real-world events subject to the vagaries of history; a Cretaceous-era model of that era’s ecology would not have included the arrival of a giant asteroid in its data, and no one expects a black swan.18 Nevertheless, models can have the predictive power demanded of scientific hypotheses. We have a new form of knowing. This new knowledge requires not just giant computers but a network to connect them, to feed them, and to make their work accessible. It exists at the network level, not in the heads of individual human beings.


pages: 291 words: 81,703

Average Is Over: Powering America Beyond the Age of the Great Stagnation by Tyler Cowen

Amazon Mechanical Turk, behavioural economics, Black Swan, brain emulation, Brownian motion, business cycle, Cass Sunstein, Charles Babbage, choice architecture, complexity theory, computer age, computer vision, computerized trading, cosmological constant, crowdsourcing, dark matter, David Brooks, David Ricardo: comparative advantage, deliberate practice, driverless car, Drosophila, en.wikipedia.org, endowment effect, epigenetics, Erik Brynjolfsson, eurozone crisis, experimental economics, Flynn Effect, Freestyle chess, full employment, future of work, game design, Higgs boson, income inequality, industrial robot, informal economy, Isaac Newton, Johannes Kepler, John Markoff, Ken Thompson, Khan Academy, labor-force participation, Loebner Prize, low interest rates, low skilled workers, machine readable, manufacturing employment, Mark Zuckerberg, meta-analysis, microcredit, Myron Scholes, Narrative Science, Netflix Prize, Nicholas Carr, off-the-grid, P = NP, P vs NP, pattern recognition, Peter Thiel, randomized controlled trial, Ray Kurzweil, reshoring, Richard Florida, Richard Thaler, Ronald Reagan, Silicon Valley, Skype, statistical model, stem cell, Steve Jobs, Turing test, Tyler Cowen, Tyler Cowen: Great Stagnation, upwardly mobile, Yogi Berra

When players are decisively up or down, they don’t seem to think or concentrate with the same facility. Again, this is a sign of human rationality, at least if there is some need for a conservation of effort. Before these investigations, Ken expected to find evidence for a Nassim TalebBlack Swan” model of cognitive failure. That is, a lot of errors coming out of the blue. But in fact, radically surprising “Black Swan” errors don’t play much of a role in the final outcome. Most games are decided on the basis of the accumulation of advantages, and the level of error is fairly well predicted by the relative skills of the players. Ken finds these results all the way down to the level of a 1,600-rated player, which would be a middling club player in most cities (he has yet to look at the games of worse players).


pages: 268 words: 81,811

Flash Crash: A Trading Savant, a Global Manhunt, and the Most Mysterious Market Crash in History by Liam Vaughan

algorithmic trading, backtesting, bank run, barriers to entry, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, Bob Geldof, centre right, collapse of Lehman Brothers, data science, Donald Trump, Elliott wave, eurozone crisis, family office, financial engineering, Flash crash, Great Grain Robbery, high net worth, High speed trading, information asymmetry, Jeff Bezos, Kickstarter, land bank, margin call, market design, market microstructure, Market Wizards by Jack D. Schwager, Navinder Sarao, Nick Leeson, offshore financial centre, pattern recognition, Ponzi scheme, proprietary trading, Ralph Nelson Elliott, Reminiscences of a Stock Operator, Ronald Reagan, selling pickaxes during a gold rush, sovereign wealth fund, spectrum auction, Stephen Hawking, the market place, Timothy McVeigh, Tobin tax, tulip mania, yield curve, zero-sum game

“We’d keep hearing: ‘Congress is calling, the White House is calling. They need answers!’ ” Adding to the pressure was a constant flow of commentary and speculation in the press. One article in the Wall Street Journal suggested, with a hint of irony, that trading by a fund advised by Nassim Nicholas Taleb, author of Black Swan, the best-selling treatise on the probability of extreme economic events, may have played a part in the meltdown. Another, on CNBC’s website, cited chatter about a mistyped trade in Procter & Gamble shares being the trigger. Then there were the victims’ stories. After markets closed on May 6, a broker-dealer industry body called FINRA had struck a deal with the exchanges to cancel any trades that occurred more than 60 percent away from their price before the crash started.

It was an illustrious group: The committee’s members were Brooksley Born, ex-CFTC chair; Jack Brennan, ex-CEO of investment company the Vanguard Group; NYU Stern professor Robert Engle; Richard Ketchum, former director of market regulation at the SEC; Cornell professor Maureen O’Hara; ex–Federal Reserve board member Susan Phillips; ex–SEC chair David Ruder; and Joseph Stiglitz from Columbia Business School. At fifty-five, Brennan was the youngest. One article in the Wall Street Journal: Scott Patterson and Tom Lauricella, “Did a Big Bet Help Trigger ‘Black Swan’ Stock Swoon?,” Wall Street Journal, May 10, 2010. Another, on CNBC’s website, cited chatter: “Stock Selloff May Have Been Triggered by a Trader Error,” CNBC.com with Reuters, May 6, 2010. Mike McCarthy, an unemployed father: Lauren LaCapra, “How P&G Plunge Derailed One Investor,” The Street, May 17, 2010.


Logically Fallacious: The Ultimate Collection of Over 300 Logical Fallacies (Academic Edition) by Bo Bennett

Black Swan, book value, butterfly effect, clean water, cognitive bias, correlation does not imply causation, Donald Trump, equal pay for equal work, Neil Armstrong, Richard Feynman, side project, statistical model, sunk-cost fallacy, the scientific method

This can result in the over-confidence in probability theory or simply not knowing exactly where it applies, as opposed to chaotic situations or situations with external influences too subtle or numerous to predict. Example #1: The best example of this fallacy is presented by the person who coined this term, Nassim Nicholas Taleb in his 2007 book, The Black Swan. There are two people: Dr. John, who is regarded as a man of science and logical thinking. Fat Tony, who is regarded as a man who lives by his wits. A third party asks them, "assume a fair coin is flipped 99 times, and each time it comes up heads. What are the odds that the 100th flip would also come up heads?"


pages: 319 words: 89,477

The Power of Pull: How Small Moves, Smartly Made, Can Set Big Things in Motion by John Hagel Iii, John Seely Brown

Albert Einstein, Andrew Keen, barriers to entry, Black Swan, business process, call centre, Clayton Christensen, clean tech, cloud computing, commoditize, corporate governance, creative destruction, disruptive innovation, Elon Musk, en.wikipedia.org, future of work, game design, George Gilder, intangible asset, Isaac Newton, job satisfaction, Joi Ito, knowledge economy, knowledge worker, loose coupling, Louis Pasteur, Malcom McLean invented shipping containers, Marc Benioff, Maui Hawaii, medical residency, Network effects, old-boy network, packet switching, pattern recognition, peer-to-peer, pre–internet, profit motive, recommendation engine, Ronald Coase, Salesforce, shareholder value, Silicon Valley, Skype, smart transportation, software as a service, supply-chain management, tacit knowledge, The Nature of the Firm, the new new thing, the strength of weak ties, too big to fail, trade liberalization, transaction costs, TSMC, Yochai Benkler

Technological Revolutions and Financial Capital. Northampton, Mass.: Edward Elgar, 2002. Polanyi, Michael. Personal Knowledge. Chicago: University of Chicago Press, 1958. Robinson, Ken. The Element. New York: Viking Penguin, 2009. Shirky, Clay. Here Comes Everybody. New York: Penguin, 2008. Taleb, Nassim Nicholas. The Black Swan. New York: Random House, 2007. Tuomi, Ilkka. Networks of Innovation. New York: Oxford University Press, 2002. Warshaw, Matt. The Encyclopedia of Surfing. New York: Harcourt, 2005. Weber, Steven. The Success of Open Source. Boston: Harvard University Press, 2004. Williamson, Oliver E.

., Scale and Scope: The Dynamics of Industrial Capitalism (Cambridge: Harvard University Press, 1994). 4 Ronald Coase, “The Nature of the Firm,” Economica 4, no. 16 (November 1937): 386-405. 5 For more about the role of real-time information in the Saffron Revolution, as well as in other political crises, see Nik Gowing, “‘Skyful of Lies’ and Black Swans: The New Tyranny of Shifting Information Power in Crises,” Reuters Institute for the Study of Journalism, May 2009, http://reutersinstitute.politics.ox.ac.uk/fileadmin/documents/Publications/Skyful_of_Lies.pdf. 6 Ibid. 7 See, for instance, “‘Neda’ Becomes Rallying Cry for Iranian Protests,” CNN, June 22, 2009, http://www.cnn.com/2009/WORLD/meast/06/21/iran.woman.twitter/index.html?


pages: 465 words: 124,074

Atomic Obsession: Nuclear Alarmism From Hiroshima to Al-Qaeda by John Mueller

airport security, Albert Einstein, Black Swan, Cass Sunstein, classic study, conceptual framework, cuban missile crisis, Doomsday Clock, energy security, F. W. de Klerk, failed state, guns versus butter model, Herman Kahn, long peace, Mikhail Gorbachev, mutually assured destruction, nuclear taboo, nuclear winter, oil shock, Oklahoma City bombing, RAND corporation, Ronald Reagan, Seymour Hersh, side project, Strategic Defense Initiative, Suez crisis 1956, Timothy McVeigh, uranium enrichment, William Langewiesche, Yom Kippur War

The Way of the World: A Story of Truth and Hope in an Age of Extremism. New York: HarperCollins. Sweeney, John. 1998. “The Truth About Iraq’s Dying Babies.” Guardian Weekly 15 March: 7. Takeyh, Ray. 2001. “The Rogue Who Came in from the Cold.” Foreign Affairs 80(3) May/June: 62–72. Taleb, Nassim Nicholas. 2007. The Black Swan: The Impact of the Highly Improbable. New York: Random House. Tannenwald, Nina. 2007. The Nuclear Taboo: The United States and the Non-Use of Nuclear Weapons Since 1945. New York: Cambridge University Press. Taubman, William. 1982. Stalin’s American Policy. New York: Norton. Tenet, George, and Bill Harlow. 2007.

With parameters like that and with some additional considerations, he is able to conclude that there is a 29 percent chance of a terrorist atomic bomb being successfully detonated in the next decade. 18. Sheets 2008. 19. Frost 2005, 17–23; Lugar 2005, 2; Pluta and Zimmerman 2006, 257; Bunn 2007, 13–14, 25–25, 36–37; Keller 2002; Ferguson and Potter, 145; Langewiesche 2007, 27–33. 20. Zimmerman and Lewis 2006, 39. See also Brodie 1966, 59; Taleb 2007. 21. On the “aberration” issue, see J. Mueller 2002b, 2002c, 2003; Seitz 2004. 22. Finel 2009; see also Kenney 2009. Environment: P. Smith 2007; see also Schneier 2003, 123–24, 247–48; J. Mueller 2006, 4. Chechens: Kramer 2004/05, 58. Muller 2008, 21–22. See also Jenkins 2008, 299. 23. One of the reasons the Americans were surprised at Pearl Harbor was that they realized the fleet there would never have been able to cramp Japan’s style in its key military effort at the time.


pages: 579 words: 183,063

Tribe of Mentors: Short Life Advice From the Best in the World by Timothy Ferriss

"World Economic Forum" Davos, 23andMe, A Pattern Language, agricultural Revolution, Airbnb, Albert Einstein, Alvin Toffler, Bayesian statistics, bitcoin, Black Lives Matter, Black Swan, blockchain, Brownian motion, Buckminster Fuller, Clayton Christensen, cloud computing, cognitive dissonance, Colonization of Mars, corporate social responsibility, cryptocurrency, David Heinemeier Hansson, decentralized internet, dematerialisation, do well by doing good, do what you love, don't be evil, double helix, driverless car, effective altruism, Elon Musk, Ethereum, ethereum blockchain, family office, fear of failure, Gary Taubes, Geoffrey West, Santa Fe Institute, global macro, Google Hangouts, Gödel, Escher, Bach, haute couture, helicopter parent, high net worth, In Cold Blood by Truman Capote, income inequality, index fund, information security, Jeff Bezos, job satisfaction, Johann Wolfgang von Goethe, Kevin Kelly, Lao Tzu, Larry Ellison, Law of Accelerating Returns, Lyft, Mahatma Gandhi, Marc Andreessen, Marc Benioff, Marshall McLuhan, Max Levchin, Mikhail Gorbachev, minimum viable product, move fast and break things, Mr. Money Mustache, Naomi Klein, Neal Stephenson, Nick Bostrom, non-fiction novel, Peter Thiel, power law, profit motive, public intellectual, Ralph Waldo Emerson, Ray Kurzweil, Salesforce, Saturday Night Live, Sheryl Sandberg, side project, Silicon Valley, Skype, smart cities, smart contracts, Snapchat, Snow Crash, Steve Jobs, Steve Jurvetson, Steven Pinker, Stewart Brand, sunk-cost fallacy, TaskRabbit, tech billionaire, TED Talk, Tesla Model S, too big to fail, Turing machine, uber lyft, Vitalik Buterin, W. E. B. Du Bois, web application, Whole Earth Catalog, Y Combinator

Darren Aronofsky TW/IG: @darrenaronofsky darrenaronofsky.com DARREN ARONOFSKY is the award-winning filmmaker behind cult classic films such as Pi, Requiem for a Dream, and The Wrestler. His first film, 1998’s Pi, won him early plaudits and a Best Director award at the Sundance Film Festival. He is perhaps best known for Black Swan, which was nominated for five Academy Awards including Best Picture and Best Director. His biblically inspired epic Noah opened at #1 at the box office and grossed more than $362 million worldwide. His latest movie is mother!, a psychological horror-thriller film starring Jennifer Lawrence and Javier Bardem

The only product is the set of future decisions the portfolio manager makes. If they get divorced or depressed, if their second in command leaves, the “product” completely changes. Calling it a product ignores the reality that the only source of stability is whether the mindset of the team leader is resilient or even antifragile (Nassim Taleb’s notion of actually getting stronger with volatility). What is one of the best or most worthwhile investments you’ve ever made? I invest a disproportionate amount of my income in paying for an ever-growing collection of trainers and coaches. There are two coaches who have had enormous impact on me in the last five years: Carolyn Coughlin at Cultivating Leadership and Jim Dethmer at Conscious Leadership.

., 91 Schaffhausen, Brian, 108–9 Schmidt, Eric, 221 Scholly, 79 School, adopting a, 449–50 School of Visual Arts, New York City, 24 Schopenhauer, Arthur, 69 Schwarzenegger, Arnold, 14 Schweitzer, Albert, 206 Scudder, Vida Dutton, 112 Seattle Seahawks, 412 Seneca, 39, 112, 206, 253, 513 Shabalov, Alexander, 369 Shake Shack, 371 Shapiro, Dani, 28 Sharapova, Maria, 182–84 Shavit, Michal, 556 Shaw, George Bernard, 235 Shea, Ryan, 492–94 Shopping.com, 31 Shungite stone, 269 Siegel, Dan, 62 Silbermann, Ben, 495–500 Simmons, Louie, 309 Simmons, Marshall, 358, 359 Simon and Garfunkel, 161 Skype, 250 Slater, Kelly, 419–20 Sleep, 3–4, 232 as investing in yourself, 212–13 naps, 319 for stress relief, 529–30 Sleepio, 243 SleepPhones, 36 Slide, 92 Sling Shot, 309, 311 Slovic, Paul, 190 Smelling salts, 387 Socrates, 224 Sohn Conference Foundation, 56 Sonen Capital, 324 Sony, 281 Sorkin, Andrew Ross, 145–46 Soros Fund Management, 428 SoundTracking, 101 Sowell, Thomas, 205 “So what” exercise, 90 SpaceX, 42, 293 Special Olympics, 509 Spiceworks, 64 Spiralizer, 306 Spotify, 286, 288 Square, 250 Stanton, Brandon, 254–55, 565 Starrett, Kelly, 316, 317 StartUp Health, 243 Stay Covered Big Wave SUP leash, 196 Stephenson, Neal, 470–71 Stewart, Zeph, 224 Stiller, Ben, 135–39 Strauss, Neil, 96–99 Strayed, Cheryl, xviii SubPac M2 Wearable Physical Sound System, 57 Suffering, 16, 32, 33, 83, 122, 237, 344, 381, 558–60 Sun Tzu, 436 Super Training Gym, Sacramento, 309 Susan G. Komen for the Cure, 509 Swope, Herbert Bayard, 69 Szabo, Nick, 382–84 T Take-Two Interactive Software, Inc., 289 Taleb, Nassim, 60 Talk therapy, 550 Task and distractions list, 542–43 TaskRabbit, 200 Tata Harper Fierce lip balm, 233 Taubes, Gary, 480 Technology, 213 disruptive, 222–23, 346 Moore’s Law for, 294–95 TED Conference, 407–8 Tesla, 42, 293 Therapy, 26–27, 81, 550 Theroux, Paul, 210 Thich Nhat Hanh, 235, 450 Thiel, Peter, 153 Thoreau, Henry David, 39, 140, 205, 463 Þórisdóttir, Anníe Mist, 305–7, 421 Thrive Global, 211 Thrive Global phone bed, 213–15 Thucydides, 6–7 Thumbtack, 31 Tile Mate key finder, 97 Tippett, Krista, 308 Tivoli Systems, 64 Tolstoy, Leo, 335 Tony Hawk Foundation, 298 Tony Hawk Signature Series, 298 Topic.com, 141 Top Ramen, 391 Torres, Dara, 390–91 Total Immersion, 440, 442, 443 Tradedoubler, 286 Transcendental Meditation, 80, 241, 242, 322, 380, 381, 489 Trickstutorials.com, 385 Truman, Harry, 206 Tumblr, 215 23andMe, 243 Twitch.tv, 64 Twitter, 31, 64, 215, 250, 401 Tyler, Aisha, 431–35 U Uber, 31, 37, 211, 215, 250, 347–48, 459, 461 Ulmer, Kristen, 546–53 Under Armour, 447 Union Square Hospitality Group (USHG), 371 Union Square Ventures, 492 Urban, Tim, 40–49, 495 USCF Memory and Aging Center, 296–97 V Valkee, 243 Van de Snepscheut, Jan L.


pages: 289 words: 113,211

A Demon of Our Own Design: Markets, Hedge Funds, and the Perils of Financial Innovation by Richard Bookstaber

affirmative action, Albert Einstein, asset allocation, backtesting, beat the dealer, behavioural economics, Black Swan, Black-Scholes formula, Bonfire of the Vanities, book value, butterfly effect, commoditize, commodity trading advisor, computer age, computerized trading, disintermediation, diversification, double entry bookkeeping, Edward Lorenz: Chaos theory, Edward Thorp, family office, financial engineering, financial innovation, fixed income, frictionless, frictionless market, Future Shock, George Akerlof, global macro, implied volatility, index arbitrage, intangible asset, Jeff Bezos, Jim Simons, John Meriwether, junk bonds, London Interbank Offered Rate, Long Term Capital Management, loose coupling, managed futures, margin call, market bubble, market design, Mary Meeker, merger arbitrage, Mexican peso crisis / tequila crisis, moral hazard, Myron Scholes, new economy, Nick Leeson, oil shock, Paul Samuelson, Pierre-Simon Laplace, proprietary trading, quantitative trading / quantitative finance, random walk, Renaissance Technologies, risk tolerance, risk/return, Robert Shiller, Robert Solow, rolodex, Saturday Night Live, selection bias, shareholder value, short selling, Silicon Valley, statistical arbitrage, tail risk, The Market for Lemons, time value of money, too big to fail, transaction costs, tulip mania, uranium enrichment, UUNET, William Langewiesche, yield curve, zero-coupon bond, zero-sum game

Indeed, there is an area of statistics called extreme value theory that deals with measuring the probability of tail events. Tail risk has been popularized as a topic by Nassim Taleb in Fooled by Randomness (New York: Texere, 2001) using John Stuart Mill’s example of a black swan. Before they were discovered in Australia, black swans had never been observed and so their discovery was surprising—it was a tail event. Still, while it may be that few people thought much about whether black swans might exist, the possibility of their existence, though a tail event, was within the realm of the anticipatable. To see this, suppose in medieval times a guild of artisans created decorative mantelpieces by painting stuffed swans different colors.


pages: 305 words: 98,072

How to Own the World: A Plain English Guide to Thinking Globally and Investing Wisely by Andrew Craig

Airbnb, Alan Greenspan, Albert Einstein, asset allocation, Berlin Wall, bitcoin, Black Swan, bonus culture, book value, BRICs, business cycle, collaborative consumption, diversification, endowment effect, eurozone crisis, failed state, Fall of the Berlin Wall, financial deregulation, financial innovation, Future Shock, index fund, information asymmetry, joint-stock company, Joseph Schumpeter, Long Term Capital Management, low cost airline, low interest rates, Market Wizards by Jack D. Schwager, mortgage debt, negative equity, Northern Rock, offshore financial centre, oil shale / tar sands, oil shock, passive income, pensions crisis, quantitative easing, Reminiscences of a Stock Operator, road to serfdom, Robert Shiller, Russell Brand, Silicon Valley, smart cities, stocks for the long run, the new new thing, The Wealth of Nations by Adam Smith, Yogi Berra, Zipcar

The Complete Art of War. Boulder: Westview, 1996. Suskind, Ron. The Way of the World: A Story of Truth and Hope in an Age of Extremism. New York: Harper, 2008. Sutherland, Stephen. Liquid Millionaire: How to Make Millions from the Up and Coming Stock Market Boom. Milton Keynes: AuthorHouse, 2008. Taleb, Nassim. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2010. ———. Fooled by Randomness. London: Penguin, 2007. Tannehill, Morris, and Linda Tannehill. The Market for Liberty: Is Government Really Necessary?; Is Government Our Protector … or Our Destroyer? New York: Laissez Faire, 1984.

Bradfield-Moody, James, and Bianca Nogrady. The Sixth Wave. London: ReadHowYouWant.com, 2010. Browne, Harry. Fail-safe Investing: Lifelong Financial Security in 30 Minutes. New York: St. Martin’s Griffin, 2001. Brussee, Warren. The Second Great Depression. Bangor: Booklocker.com, 2005. Bryson, Bill. Notes from a Small Island. London: Black Swan, 1996. Bueno de Mesquita, Bruce. Prediction: How to See and Shape the Future with Game Theory. London: Vintage, 2010. Burns, Robbie. The Naked Trader: How Anyone Can Make Money Trading Shares. Petersfield: Harriman House, 2007. ———. The Naked Trader’s Guide to Spread Betting: How to Make Money from Shares in Up or Down Markets.


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Why I Left Goldman Sachs: A Wall Street Story by Greg Smith

Alan Greenspan, always be closing, asset allocation, Bear Stearns, Black Swan, bonus culture, break the buck, collateralized debt obligation, corporate governance, Credit Default Swap, credit default swaps / collateralized debt obligations, delayed gratification, East Village, fear index, financial engineering, fixed income, Flash crash, glass ceiling, Glass-Steagall Act, Goldman Sachs: Vampire Squid, high net worth, information asymmetry, London Interbank Offered Rate, mega-rich, money market fund, new economy, Nick Leeson, proprietary trading, quantitative hedge fund, Renaissance Technologies, short selling, short squeeze, Silicon Valley, Skype, sovereign wealth fund, Stanford marshmallow experiment, statistical model, technology bubble, too big to fail

These funds were almost always short volatility: in other words, they’d bet that, on average, markets would remain fairly calm, even though there might be some hiccups along the way. Academic studies had shown this strategy to work over prolonged historical periods. The problem was that these hedge funds were not anticipating “Black Swan” events, a term coined by Nassim Nicholas Taleb to explain once-in-a-thousand-year-type events that people do not expect and that models can’t predict. What we saw in 2008 and 2009 was a series of Black Swan events that the statistical models would have told you were not possible, according to history. Instead of the S&P 500 Index having average daily percentage swings of 1 percent, for a sustained period the market was swinging back and forth more than 5 percent per day—five times what was normal.


pages: 662 words: 180,546

Never Let a Serious Crisis Go to Waste: How Neoliberalism Survived the Financial Meltdown by Philip Mirowski

"there is no alternative" (TINA), Adam Curtis, Alan Greenspan, Alvin Roth, An Inconvenient Truth, Andrei Shleifer, asset-backed security, bank run, barriers to entry, Basel III, Bear Stearns, behavioural economics, Berlin Wall, Bernie Madoff, Bernie Sanders, Black Swan, blue-collar work, bond market vigilante , bread and circuses, Bretton Woods, Brownian motion, business cycle, capital controls, carbon credits, Carmen Reinhart, Cass Sunstein, central bank independence, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, complexity theory, constrained optimization, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, dark matter, David Brooks, David Graeber, debt deflation, deindustrialization, democratizing finance, disinformation, do-ocracy, Edward Glaeser, Eugene Fama: efficient market hypothesis, experimental economics, facts on the ground, Fall of the Berlin Wall, financial deregulation, financial engineering, financial innovation, Flash crash, full employment, George Akerlof, Glass-Steagall Act, Goldman Sachs: Vampire Squid, Greenspan put, Hernando de Soto, housing crisis, Hyman Minsky, illegal immigration, income inequality, incomplete markets, information asymmetry, invisible hand, Jean Tirole, joint-stock company, junk bonds, Kenneth Arrow, Kenneth Rogoff, Kickstarter, knowledge economy, l'esprit de l'escalier, labor-force participation, liberal capitalism, liquidity trap, loose coupling, manufacturing employment, market clearing, market design, market fundamentalism, Martin Wolf, money market fund, Mont Pelerin Society, moral hazard, mortgage debt, Naomi Klein, Nash equilibrium, night-watchman state, Northern Rock, Occupy movement, offshore financial centre, oil shock, Pareto efficiency, Paul Samuelson, payday loans, Philip Mirowski, Phillips curve, Ponzi scheme, Post-Keynesian economics, precariat, prediction markets, price mechanism, profit motive, public intellectual, quantitative easing, race to the bottom, random walk, rent-seeking, Richard Thaler, road to serfdom, Robert Shiller, Robert Solow, Ronald Coase, Ronald Reagan, Savings and loan crisis, savings glut, school choice, sealed-bid auction, search costs, Silicon Valley, South Sea Bubble, Steven Levy, subprime mortgage crisis, tail risk, technoutopianism, The Chicago School, The Great Moderation, the map is not the territory, The Myth of the Rational Market, the scientific method, The Theory of the Leisure Class by Thorstein Veblen, The Wisdom of Crowds, theory of mind, Thomas Kuhn: the structure of scientific revolutions, Thorstein Veblen, Tobin tax, tontine, too big to fail, transaction costs, Tyler Cowen, vertical integration, Vilfredo Pareto, War on Poverty, Washington Consensus, We are the 99%, working poor

In academic doctrine, the system as a whole simply cannot fail to price and allocate risks; hence there is no such thing as virulently “toxic” assets. Crappy assets, junk bonds, dogs with fleas, yes; but inherently “toxic,” never. The other dominant metaphor was the biblical “Day of Reckoning.”24 Americans love a good apocalypse, and journalists found some figures who were willing to deliver it, from Naseem Taleb and his “Black Swan” to Nouriel Roubini as Dr. Doom. The evil will be punished, the last shall be made first, the moneychangers will be ejected from the temple, and the righteous shall triumph. I hope I need not expound upon the fact that there is nowhere to be found such Old Testament reckoning in orthodox economic theory: the market correctly evaluates everything in real time, and no one is really punished, but rather experiences depreciation of their human capital (or something like that).

What could be the purpose of yet another jokey variation on the metaphor of the “Invisible Hand” on the cover of some text that purports to convince us that a very few select events or principles (usually a prime number) constitute the Rosetta Stone for decoding recent events? The distance from self-help books (Six Things Momma Taught Me to Succeed When Good People Do Bad Things) to crisis prescription books (Dunk That Invisible Hand in Talcum Powder and Snap on the Handcuffs) and get-rich-quick books (Who’s Afraid of the Big Black Swan?) narrows precipitously in the modern marketplace of ideas. Rest assured this will not be another of those books “about the crisis,” in the sense of purveying yet one more play-by-play account of who did what to whom. Indeed, some of the best-detailed accounts of the economic history of the contraction of 2007–9 are freely available online; the problem seems to be, rather, that no one cares enough anymore to expend the effort to read them.20 There is even a superb film that lays out the basic sequence of breakdown in an admirably clear way for a general audience: I refer to the movie Inside Job (2011).

Andrews Standard & Poor’s Standing Committee on Individual Financial Conflict of Interest Stanford University Starbucks Starr Foundation State Department State Street Bank Steil, Benn Stein, Jeremy Stewart, Jon Stiftung Marktwirtschaft Stigler, George Stiglitz, Joseph about on agnotology on behavioral economics Bhagwati on on economic crisis on EMH on Fannie Mae and Freddie Mac Freefall on macroeconomics Meme Wars Morgenson on on neoclassical orthodoxy on neoliberalism Nobel Prize winner orthodox economics profession on on orthodoxy public profile of “reject the EMH” option on Third Way on “welfare loss,” zombie thought Stratospheric Particle Injection for Climate Engineering project (SPICE) Strauss, Leo Strauss-Kahn, Dominique Structured Investment Vehicle Stulz, Rene Summers, Lawrence about clash with Rajan compared with Shleifer on Council of Economic Advisors DeLong on on “enrichment,” influence of as member of Harvard Corporation named as Rubin’s replacement in Predator Nation as president of Harvard University Quiggin on on Tobin tax Sunstein, Cass Super Sad True Love Story (Shteyngart) Surowiecki, James Suskind, Ron Swagel, Phillip Swan, Elaine Swiss Institute of International Studies (Schweizerisches Institut für Auslandforschung) Szekeley, Al T Taconic Capital Advisors Taibbi, Matt Talbot, Margaret Taleb, Naseem TARP (Troubled Asset Rescue Plan) about Adams on appropriation explained influences on public justification of bailout Wall Street economists on Tax Policy task force Taylor, John B. Tea Party about aspects of Ayn Rand and Cochrane on demonstrators as example of metamorphosis of protest movement influence of jump-start of Koch-funded front organizations and left on origins of on Paul Revere Purity of Populist Expression Tea Party Express Team Greed Team Regulation Tellmann, Ute Ten Commandments of Neoclassicism Thaler, Richard Thatcher, Margaret The Theatre and Its Double (Artaud) Theory of the Leisure Class (Veblen) There Is No Alternative (TINA) Thirteen Commandments Thirteenth Amendment This Time Is Different (Rogoff and Reinhart) Thoma, Mark Thomas, Bill Thurn, Max The Time Machine (Wells) TINA (There Is No Alternative) Tkacik, Maureen Tobin, James Tobin tax “Too Big to Bail” (Ferguson and Johnson) Toxic assets TransUnion Treasury Department about Ausubel on on Bear Stearns “Break the Glass” memo on Inside Job Paulson on pressure from public defense of Rajan on revolving door between Goldman Sachs and Rubin leaves Trichet, Jean-Claude Trier, Lars von Troubled Asset Relief Program.


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The End of Wall Street by Roger Lowenstein

"World Economic Forum" Davos, Alan Greenspan, Asian financial crisis, asset-backed security, bank run, banking crisis, Bear Stearns, benefit corporation, Berlin Wall, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, break the buck, Brownian motion, Carmen Reinhart, collateralized debt obligation, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, diversified portfolio, eurozone crisis, Fall of the Berlin Wall, fear of failure, financial deregulation, financial engineering, fixed income, geopolitical risk, Glass-Steagall Act, Greenspan put, high net worth, Hyman Minsky, interest rate derivative, invisible hand, junk bonds, Ken Thompson, Kenneth Rogoff, London Interbank Offered Rate, Long Term Capital Management, low interest rates, margin call, market bubble, Martin Wolf, Michael Milken, money market fund, moral hazard, mortgage debt, negative equity, Northern Rock, Ponzi scheme, profit motive, race to the bottom, risk tolerance, Ronald Reagan, Rubik’s Cube, Savings and loan crisis, savings glut, short selling, sovereign wealth fund, statistical model, the payments system, too big to fail, tulip mania, Y2K

This regrettable complexity was pithily summarized in a ditty attributed to the nineteenth-century robber baron Daniel Drew: “He who sells what isn’t his’n, must buy it back or go to prison.” y A proper limitation on free speech in the context of securities markets prohibits deliberate falsehoods for the purpose of manipulating prices. In practice, manipulation is difficult to spot and harder to prove. z In The Black Swan, Nassim Nicholas Taleb discussed the impact of highly improbable unforeseen events. aa It was a testimony to Fuld’s powers of persuasion that Fink nonetheless participated (on behalf of BlackRock) in Lehman’s private stock offering. Advisers may have been telling Fuld to get out, but to some extent, they shared his faith in Lehman’s powers of resurrection.

As the maturities on their debts approached, two-year notes became one-year notes; paper maturing in eighteen months now was due in six, and so forth. Creditors were less willing to go home at night with monies owed from Merrill or Lehman; the Street, perforce, survived on a diet of short-term paper. No wonder Fuld was on edge. 10 TOTTERING How can you live in a black swan world?z —TOM RUSSO LEHMAN BEGAN TO TOTTER in the second week of June. Toting up its second quarter, Lehman was staring at its first loss as a public company, a bloodletting of nearly $3 billion. Its execs, who had most of their net worth tied up in Lehman’s sinking stock—down by half since the start of the year—quickly became alarmed.

Prices, they felt, were simply too low. (Nothing so irritates a banker as when the market refuses to conform to his opinion.) Russo, the vice-chairman, thought mortgage securities were so out of line, he bought a big slug of mortgage-backed bonds for his kids. To Russo, to capitulate to such prices was to live in a “black swan” world, in which risk-taking was totally proscribed for fear of an unlikely but catastrophic event. That was exactly how the Street did not do business. Every little bet, every accumulation of bets, was based on the faith that a devastating crash remained but a theoretical possibility, a topic only for drawing room debate.


pages: 261 words: 79,883

Start With Why: How Great Leaders Inspire Everyone to Take Action by Simon Sinek

Apple II, Apple's 1984 Super Bowl advert, Black Swan, business cycle, commoditize, Do you want to sell sugared water for the rest of your life?, hiring and firing, John Markoff, low cost airline, Neil Armstrong, Nick Leeson, Pepsi Challenge, RAND corporation, risk tolerance, Ronald Reagan, shareholder value, Steve Ballmer, Steve Jobs, Steve Wozniak, The Wisdom of Crowds, trade route

., The Monk and the Riddle by Randy Komisar, The Five Dysfunctions of a Team by Patrick Lencioni, Freakanomics by Steven D. Levitt and Stephen J. Dubner, FISH! By Stephen Lundin, Harry Paul, John Christensen and Ken Blanchard, The Naked Brain by Richard Restack, Authentic Happiness by Martin Seligman, The Wisdom of Crowds by James Surowiecki, The Black Swan by Nicholas Taleb, American Mania by Peter Whybrow, M.D., and the single most important book everyone should read, the book that teaches us that we cannot control the circumstances around us, all we can control is our attitude—Man’s Search for Meaning by Viktor Frankel. I want to especially thank all those people who have joined this cause and actively work to inspire those around you.


pages: 772 words: 203,182

What Went Wrong: How the 1% Hijacked the American Middle Class . . . And What Other Countries Got Right by George R. Tyler

"Friedman doctrine" OR "shareholder theory", "World Economic Forum" Davos, 8-hour work day, active measures, activist fund / activist shareholder / activist investor, affirmative action, Affordable Care Act / Obamacare, Alan Greenspan, bank run, banking crisis, Basel III, Bear Stearns, behavioural economics, benefit corporation, Black Swan, blood diamond, blue-collar work, Bolshevik threat, bonus culture, British Empire, business cycle, business process, buy and hold, capital controls, Carmen Reinhart, carried interest, cognitive dissonance, collateralized debt obligation, collective bargaining, commoditize, company town, compensation consultant, corporate governance, corporate personhood, corporate raider, corporate social responsibility, creative destruction, credit crunch, crony capitalism, crowdsourcing, currency manipulation / currency intervention, David Brooks, David Graeber, David Ricardo: comparative advantage, declining real wages, deindustrialization, Diane Coyle, disruptive innovation, Double Irish / Dutch Sandwich, eurozone crisis, financial deregulation, financial engineering, financial innovation, fixed income, Ford Model T, Francis Fukuyama: the end of history, full employment, George Akerlof, George Gilder, Gini coefficient, Glass-Steagall Act, Gordon Gekko, Greenspan put, hiring and firing, Ida Tarbell, income inequality, independent contractor, invisible hand, job satisfaction, John Markoff, joint-stock company, Joseph Schumpeter, junk bonds, Kenneth Rogoff, labor-force participation, laissez-faire capitalism, lake wobegon effect, light touch regulation, Long Term Capital Management, low interest rates, manufacturing employment, market clearing, market fundamentalism, Martin Wolf, minimum wage unemployment, mittelstand, Money creation, moral hazard, Myron Scholes, Naomi Klein, Northern Rock, obamacare, offshore financial centre, Paul Samuelson, Paul Volcker talking about ATMs, pension reform, performance metric, Pershing Square Capital Management, pirate software, plutocrats, Ponzi scheme, precariat, price stability, profit maximization, profit motive, prosperity theology / prosperity gospel / gospel of success, purchasing power parity, race to the bottom, Ralph Nader, rent-seeking, reshoring, Richard Thaler, rising living standards, road to serfdom, Robert Gordon, Robert Shiller, rolling blackouts, Ronald Reagan, Sand Hill Road, Savings and loan crisis, shareholder value, Silicon Valley, Social Responsibility of Business Is to Increase Its Profits, South Sea Bubble, sovereign wealth fund, Steve Ballmer, Steve Jobs, stock buybacks, subprime mortgage crisis, The Chicago School, The Spirit Level, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, Thorstein Veblen, too big to fail, transcontinental railway, transfer pricing, trickle-down economics, tulip mania, Tyler Cowen, Tyler Cowen: Great Stagnation, union organizing, Upton Sinclair, upwardly mobile, women in the workforce, working poor, zero-sum game

A variety of options for eliminating Red Queens have been discussed; the Financial Times and Volcker have proposed that their depository (retail) activities be entirely sold off from investment activities, for example.84 Another option is to limit bank size as proposed by Tarullo, Ohio Senator Sharrod Brown and MIT’s Simon Johnson to a set proportion of US GDP, say 1 or 2 percent.85 The resulting size would still be larger than the optimal suggested by Andrew Haldane and colleagues at the Bank of England. They concluded that economies of scale for banks disappear when assets exceed $100 billion, which should be an internationally adopted size ceiling.86 In the interim before such reforms, New York University professor Nassim Nicholas Taleb of “black swan” fame has proposed eliminating all bonuses at Red Queens to reduce risk and the odds of further taxpayer bailouts.87 Deflate Executive Compensation While the most dramatic examples of market failure in pay-for-performance occurred on Wall Street, it has been broadly characteristic of the American business community during the Reagan decline.

See Philip Augar and John McFall, “To Fix the System We Must Break Up the Banks,” Financial Times, Sept. 10, 2009. 86 Andrew G. Haldane, “On Being the Right Size,” Institute of Economic Affairs’ 22nd Annual Series, 2012, Beesley Lectures, London, Oct. 25, 2012, 13. http://www.bankofengland.co.uk/publications/Documents/speeches/2012/speech615.pdf. 87 Nassim Nicholas Taleb, “End Bonuses for Bankers,” New York Times, Nov. 8, 2011. 88 “Final Report of the High Pay Commission,” High Pay Commission, Joseph Rowntree Charitable Trust, Nov. 22, 2011, http://highpaycommission.co.uk/wp-content/uploads/2011/11/HPC_final_report_WEB.pdf. “Managing High Pay in Companies,” Editorial, Financial Times, Nov. 21, 2011. 89 Michael Skapinker, “CEOs Need to Join the 20 Times Club Now,” Financial Times, Nov. 30, 2011. 90 Adele Ferguson, “More Transparency Needed for Executive Pay Reports,” Sydney Morning Herald, Sept. 18, 2012. 91 Michael Skapinker, “CEOs Need to Join the 20 Times Club Now.” 92 Julia Werdigier, “Shareholder Votes on Pay to Be Binding in Britain,” New York Times, June 21, 2012. 93 “Irresistible Rise of the Angry Investor,” Editorial, Financial Times, May 4, 2012. 94 Richard Milne, “Europe: A Meeting of the Minds,” Financial Times, Feb. 28, 2010. 95 Michael West, “Two Strikes’ Holds Boards to Account,” Sydney Morning Herald, Nov. 17, 2012. 96 Colin Kruger, “Crown Gets Approval for Executive Pay,” Sydney Morning Herald, Oct. 30, 2012.

(economist), 13, 320–21, 358 Storbeck, Olaf (Handelsblatt reporter), 85 Story, Louise (New York Times), 463 Stout, Lynn (Cornell University professor), 43, 163, 169 shareholder capitalism, 163 The Shareholder Value Myth: How Putting Shareholders First Harms Investors, Corporations, and the Public, 47–48 Stulz, Rene (economist), 39, 178 Sullivan, Martin, 277, 348 Summers, Lawrence H. (former Secretary of Treasury), 73, 153–54, 208, 360, 455 Surowiecki, James (New Yorker), 151 Sweeney, Pete (journalist), 245 T Taleb, Nassim Nicholas (economist), 461 Tarbell, Ida, 97 Tax Haven, 276–80, 427, 454–56 Taylor, Karl (economist), 171, 176 Taylor, Maurice (CEO Titan International), 452 Tea Party. See also shareholder capitalism; top 1 percent; top income families, 434–5 Tepper, Jonathan, 215 (chart) Endgame, 215 Thatcher, Margaret (British Prime Minister), 71, 338–39, 371–72 Thibault, Michael, 188 Top earners Reagan era tax cuts, 98, 190 Eisenhower era tax rates, 98 Northern Europeans vs. 284–6 incomes, 5, 24, 96, 190, 274–5, Tough, Paul, How Children Succeed, 305 Trani, John M.


Beautiful Data: The Stories Behind Elegant Data Solutions by Toby Segaran, Jeff Hammerbacher

23andMe, airport security, Amazon Mechanical Turk, bioinformatics, Black Swan, business intelligence, card file, cloud computing, computer vision, correlation coefficient, correlation does not imply causation, crowdsourcing, Daniel Kahneman / Amos Tversky, DARPA: Urban Challenge, data acquisition, data science, database schema, double helix, en.wikipedia.org, epigenetics, fault tolerance, Firefox, Gregor Mendel, Hans Rosling, housing crisis, information retrieval, lake wobegon effect, Large Hadron Collider, longitudinal study, machine readable, machine translation, Mars Rover, natural language processing, openstreetmap, Paradox of Choice, power law, prediction markets, profit motive, semantic web, sentiment analysis, Simon Singh, social bookmarking, social graph, SPARQL, sparse data, speech recognition, statistical model, supply-chain management, systematic bias, TED Talk, text mining, the long tail, Vernor Vinge, web application

> s = sorted_counts[1:1000] > barplot(s) In 1935, the linguist George Zipf observed that word frequency distributions often follow a “power law,” where the frequency of the nth word is proportional to (1/ns), where s is a constant. Unlike a Gaussian distribution, this distribution has infinite variance, which can make it somewhat unwieldy for certain statistical algorithms. Popular books such as Nassim Nicholas Taleb’s The Black Swan (Random House) and Chris Anderson’s The Long Tail (Hyperion) have made these distributions famous as “fat tail” and “long tail” distributions, respectively. Indeed, our data has quite a long tail: 220,000 words, or 76% of the vocabulary, occur only once. SUPERFICIAL DATA ANALYSIS: EXPLORING MILLIONS OF SOCIAL STEREOTYPES Download at Boykma.Com 291 Frequency of tag vs.


pages: 511 words: 148,310

Winning the War on War: The Decline of Armed Conflict Worldwide by Joshua S. Goldstein

Albert Einstein, Ayatollah Khomeini, Bartolomé de las Casas, Berlin Wall, Black Swan, blood diamond, business cycle, colonial rule, cuban missile crisis, death from overwork, Doomsday Clock, failed state, immigration reform, income inequality, invention of writing, invisible hand, land reform, long peace, microcredit, Mikhail Gorbachev, Nelson Mandela, no-fly zone, Oklahoma City bombing, purchasing power parity, RAND corporation, selection bias, Steven Pinker, Suez canal 1869, Suez crisis 1956, Tobin tax, unemployed young men, Winter of Discontent, work culture , Y2K

Stockholm Initiative on Disarmament Demobilisation Reintegration: Final Report. Stockholm, 2006. Swerdlow, Amy. “Pure Milk, Not Poison: Women Strike for Peace and the Test Ban Treaty of 1963.” In Adrienne Harris and Ynestra King, eds., Rocking the Ship of State: Toward a Feminist Peace Politics. Boulder: Westview, 1989: 225–37. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Taylor, Frederick. Dresden: Tuesday, February 13, 1945. New York: HarperCollins, 2004. Tennyson, Alfred. The Works of Alfred Tennyson. Vol. 3: Locksley Hall, and Other Poems. London: Henry S. King, 1874. Thakur, Ramesh.

Melander, Öberg, and Hall 2009; see also Sarkees and Wayman 2010: 559; Lacina and Gleditsch 2005: 154. 236 Quickly defies: Lacina and Gleditsch 2005: 148; see also Collier 2009: 4. 237 Have become rare: Wallensteen and Sollenberg 1996: 356; Harbom and Wallensteen 2009: 578, 579. 237 Djibouti: BBC News 2008a. 237 Georgia and its breakaway: Harbom and Wallensteen 2009: 579–80. 237 Diminished as well: Levy 2002: 351. 238 Trend has flattened out: Hewitt, Wilkenfeld, and Gurr 2007; Harbom and Wallensteen 2009. 238 Ripple of interest: Easterbrook 2005; Mack 2005; Tierney 2005; Noah 2005; Sands 2005; Kaplan 2006; Traub 2006b; Arquilla 2006. 239 Steady downward trend: Wilson and Gurr 1999; see also Goldstein 2002. 239 Not seem to get through: Mack 2007: 523, 524; see also Human Security Centre 2005: 18. 239 Selection bias: Licklider 2005: 37. 239 Reporting the worst: Boulding 1978: 83. 240 Plenty of images: Payne 2004: 13; see also Taleb 2007: 112, 55, 80, 100. 240 Bleeds, it leads: See Boulding 1978: 83. 240 Progress Paradox: Easterbrook 2003: 35, 36. 240–41 Much more peaceful: Payne 2004: 7. 241 Chronological bias: He used this nice phrase at a conference, but calls it “presentism” in Payne 2004: 8. 241 Tendency to assume: Payne 2004: 68, 8, 9. 241 Takes to task: Payne 2004: 14, 9, 69, 267 n.3; Richardson 1960: 112, 128; Luard 1986: 23. 242 Glorify violence: Pinker 2007: 20. 242 Lack moral concern: Payne 2004: 10–11. 242 High-decibel: Easterbrook 2003: 100. 242 Followers and donations: Pinker 2007: 20. 242 The generation: Toynbee 1954: 322. 243 Researchers in Vancouver: Human Security Centre 2005: 17, 36, 28, 41, 42, 44. 244 One area where things: Human Security Report Project 2007: 28, 38–39, 35, 36, 42, 43. 244 Number of terrorist attacks: Human Security Report Project 2007: 2–3.


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Randomistas: How Radical Researchers Changed Our World by Andrew Leigh

Albert Einstein, Amazon Mechanical Turk, Anton Chekhov, Atul Gawande, basic income, behavioural economics, Black Swan, correlation does not imply causation, crowdsourcing, data science, David Brooks, Donald Trump, ending welfare as we know it, Estimating the Reproducibility of Psychological Science, experimental economics, Flynn Effect, germ theory of disease, Ignaz Semmelweis: hand washing, Indoor air pollution, Isaac Newton, It's morning again in America, Kickstarter, longitudinal study, loss aversion, Lyft, Marshall McLuhan, meta-analysis, microcredit, Netflix Prize, nudge unit, offshore financial centre, p-value, Paradox of Choice, placebo effect, price mechanism, publication bias, RAND corporation, randomized controlled trial, recommendation engine, Richard Feynman, ride hailing / ride sharing, Robert Metcalfe, Ronald Reagan, Sheryl Sandberg, statistical model, Steven Pinker, sugar pill, TED Talk, uber lyft, universal basic income, War on Poverty

The case of transportation’, Journal of the American Planning Association, vol. 71, no. 2, 2005, pp. 131–46; Robert Bain, ‘Error and optimism bias in toll road traffic forecasts’, Transportation, vol. 36, no. 5, 2009, pp. 469–82; Bent Flyvbjerg & Eamonn Molloy, ‘Delusion, deception and corruption in major infrastructure projects: Causes, consequences, cures’, International Handbook on the Economics of Corruption, vol. 2, 2012, pp. 81–107. 22Nassim Nicholas Taleb, The Black Swan: The Impact of the Highly Improbable, 2nd edn, New York: Random House, 2010, p. 154. 23Ola Svenson, ‘Are we all less risky and more skillful than our fellow drivers?’ Acta Psychologica, vol. 47, no. 2, pp. 143–8. 24Eighteen per cent rated their own beauty as above average, 79 percent said average, and 3 per cent said below average: Jonathan Kelley, Robert Cushing & Bruce Headey, Codebook for 1984 Australian National Social Science Survey (ICPSR 9084), Ann Arbor, MI: Inter-university Consortium for Political and Social Research, 1989. 25Dominic D.P.


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The Knowledge Illusion by Steven Sloman

Affordable Care Act / Obamacare, Air France Flight 447, attribution theory, bitcoin, Black Swan, Cass Sunstein, combinatorial explosion, computer age, Computing Machinery and Intelligence, CRISPR, crowdsourcing, Dmitri Mendeleev, driverless car, Dunning–Kruger effect, Elon Musk, Ethereum, Flynn Effect, Great Leap Forward, Gregor Mendel, Hernando de Soto, Higgs boson, hindsight bias, hive mind, indoor plumbing, Isaac Newton, John von Neumann, libertarian paternalism, Mahatma Gandhi, Mark Zuckerberg, meta-analysis, Nick Bostrom, obamacare, Peoples Temple, prediction markets, randomized controlled trial, Ray Kurzweil, Richard Feynman, Richard Thaler, Rodney Brooks, Rosa Parks, seminal paper, single-payer health, speech recognition, stem cell, Stephen Hawking, Steve Jobs, technological singularity, The Coming Technological Singularity, The Wisdom of Crowds, Vernor Vinge, web application, Whole Earth Review, Y Combinator

The Emperor of All Maladies: A Biography of Cancer. New York: Scribner. weather forecasting: www.bbc.com/news/business-29256322. The weather in your location today depends: www.scholastic.com/teachers/article/weather. the more likely ones: These issues are discussed in Nassim Nicholas Taleb (2007), The Black Swan. New York: Random House. Gould quote: S. J. Gould (1989). Wonderful Life: The Burgess Shale and the Nature of History, 1st ed. New York: W. W. Norton, 320–321. TWO. WHY WE THINK Borges quotes: J. L. Borges (1964). “Funes the Memorious.” Labyrinths: Selected Stories and Other Writings.


Adam Smith: Father of Economics by Jesse Norman

active measures, Alan Greenspan, Andrei Shleifer, balance sheet recession, bank run, banking crisis, Basel III, Bear Stearns, behavioural economics, Berlin Wall, Black Swan, Branko Milanovic, Bretton Woods, British Empire, Broken windows theory, business cycle, business process, Capital in the Twenty-First Century by Thomas Piketty, Carmen Reinhart, centre right, cognitive dissonance, collateralized debt obligation, colonial exploitation, Corn Laws, Cornelius Vanderbilt, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, David Brooks, David Ricardo: comparative advantage, deindustrialization, electricity market, Eugene Fama: efficient market hypothesis, experimental economics, Fall of the Berlin Wall, Fellow of the Royal Society, financial engineering, financial intermediation, frictionless, frictionless market, future of work, George Akerlof, Glass-Steagall Act, Hyman Minsky, income inequality, incomplete markets, information asymmetry, intangible asset, invention of the telescope, invisible hand, Isaac Newton, Jean Tirole, John Nash: game theory, joint-stock company, Joseph Schumpeter, Kenneth Arrow, Kenneth Rogoff, lateral thinking, loss aversion, low interest rates, market bubble, market fundamentalism, Martin Wolf, means of production, mirror neurons, money market fund, Mont Pelerin Society, moral hazard, moral panic, Naomi Klein, negative equity, Network effects, new economy, non-tariff barriers, Northern Rock, Pareto efficiency, Paul Samuelson, Peter Thiel, Philip Mirowski, price mechanism, principal–agent problem, profit maximization, public intellectual, purchasing power parity, random walk, rent-seeking, Richard Thaler, Robert Shiller, Robert Solow, Ronald Coase, scientific worldview, seigniorage, Socratic dialogue, South Sea Bubble, special economic zone, speech recognition, Steven Pinker, The Chicago School, The Myth of the Rational Market, The Nature of the Firm, The Rise and Fall of American Growth, The Theory of the Leisure Class by Thorstein Veblen, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, theory of mind, Thomas Malthus, Thorstein Veblen, time value of money, transaction costs, transfer pricing, Veblen good, Vilfredo Pareto, Washington Consensus, working poor, zero-sum game

., Globalisation and its Discontents Revisited, Penguin Books 2017 Stiglitz, Joseph E., The Price of Inequality, Penguin Books 2012 Surowiecki, James, The Wisdom of Crowds, Doubleday Books 2004 Szechi, Daniel, The Jacobites: Britain and Europe 1688–1788, Manchester University Press 1994 Taleb, Nassim Nicholas, The Black Swan, Random House 2007 Tavris, Carol and Elliot Aronson, Mistakes Were Made (But Not by Me), Mariner Books 2015 Thompson, Harold, A Scottish Man of Feeling: Some Account of Henry Mackenzie… and of the Golden Age of Burns and Scott, Oxford University Press 1931 Tirole, Jean, Economics for the Common Good, Princeton University Press 2017 Tytler, Alexander Fraser, Lord Woodhouselee, Memoirs of the Life and Writings of the Honourable Henry Home of Kames, T.

And there is the non-trivial point that if the price is not right, if markets do not in fact reflect all available information, then the core theory of capital allocation and efficiency at the heart of the world’s financial system is very seriously flawed. The implications of that thought are horrendous. Thirdly, there is nothing irrational about the tendency of asset markets towards instability. These booms and busts are not what are sometimes referred to as ‘fat tail’ or ‘black swan’ events—that is, events so far outside the normal probabilities as to be all but mathematically impossible. On the contrary, they are the results of positive feedback loops working through specific market channels, whose effect is to magnify and compound instability. That is why they—and their cousins, rapid market over- and undershoots—occur with such alleged statistically improbable regularity.


pages: 466 words: 127,728

The Death of Money: The Coming Collapse of the International Monetary System by James Rickards

"World Economic Forum" Davos, Affordable Care Act / Obamacare, Alan Greenspan, Asian financial crisis, asset allocation, Ayatollah Khomeini, bank run, banking crisis, Bear Stearns, Ben Bernanke: helicopter money, bitcoin, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, Bretton Woods, BRICs, business climate, business cycle, buy and hold, capital controls, Carmen Reinhart, central bank independence, centre right, collateralized debt obligation, collective bargaining, complexity theory, computer age, credit crunch, currency peg, David Graeber, debt deflation, Deng Xiaoping, diversification, Dr. Strangelove, Edward Snowden, eurozone crisis, fiat currency, financial engineering, financial innovation, financial intermediation, financial repression, fixed income, Flash crash, floating exchange rates, forward guidance, G4S, George Akerlof, global macro, global reserve currency, global supply chain, Goodhart's law, Growth in a Time of Debt, guns versus butter model, Herman Kahn, high-speed rail, income inequality, inflation targeting, information asymmetry, invisible hand, jitney, John Meriwether, junk bonds, Kenneth Rogoff, labor-force participation, Lao Tzu, liquidationism / Banker’s doctrine / the Treasury view, liquidity trap, Long Term Capital Management, low interest rates, mandelbrot fractal, margin call, market bubble, market clearing, market design, megaproject, Modern Monetary Theory, Money creation, money market fund, money: store of value / unit of account / medium of exchange, mutually assured destruction, Nixon triggered the end of the Bretton Woods system, obamacare, offshore financial centre, oil shale / tar sands, open economy, operational security, plutocrats, Ponzi scheme, power law, price stability, public intellectual, quantitative easing, RAND corporation, reserve currency, risk-adjusted returns, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, Satoshi Nakamoto, Silicon Valley, Silicon Valley startup, Skype, Solyndra, sovereign wealth fund, special drawing rights, Stuxnet, The Market for Lemons, Thomas Kuhn: the structure of scientific revolutions, Thomas L Friedman, too big to fail, trade route, undersea cable, uranium enrichment, Washington Consensus, working-age population, yield curve

New York: Hyperion, 2003. Tainter, Joseph A. The Collapse of Complex Societies. Cambridge, U.K.: Cambridge University Press, 1988 Takeyh, Ray. Hidden Iran: Paradox and Power in the Islamic Republic. New York: Henry Holt, 2006. Taleb, Nassim Nicholas. Fooled by Randomness: The Hidden Role of Chance in the Markets and in Life. New York: Texere, 2001. ———. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Taylor, John B. Getting Off Track: How Government Actions and Interventions Caused, Prolonged, and Worsened the Financial Crisis. Stanford, Calif.: Hoover Institution Press, 2009.

Singh, Manmohan, and James Aitken. “The (Sizable) Role of Rehypothecation in the Shadow Banking System.” IMF Working Paper no. WP/10/172, July 2010, http://www.imf.org/external/pubs/ft/wp/2010/wp10172.pdf. Sornette, Didier. “Critical Market Crashes.” Physics Reports 378 (2003), pp. 1–98. ———. “Dragon-Kings, Black Swans and the Prediction of Crises.” International Journal of Terraspace Science and Engineering (December 2009), http://arxiv.org/pdf/0907.4290.pdf. Sornette, Didier, and Ryan Woodard. “Financial Bubbles, Real Estate Bubbles, Derivative Bubbles, and the Financial and Economic Crisis.” Proceedings of Applications of Physics and Financial Analysis Conference Series, May 2, 2009, http://arxiv.org/pdf/0905.0220.pdf.


Future Files: A Brief History of the Next 50 Years by Richard Watson

Abraham Maslow, Albert Einstein, bank run, banking crisis, battle of ideas, Black Swan, call centre, carbon credits, carbon footprint, carbon tax, cashless society, citizen journalism, commoditize, computer age, computer vision, congestion charging, corporate governance, corporate social responsibility, deglobalization, digital Maoism, digital nomad, disintermediation, driverless car, epigenetics, failed state, financial innovation, Firefox, food miles, Ford Model T, future of work, Future Shock, global pandemic, global supply chain, global village, hive mind, hobby farmer, industrial robot, invention of the telegraph, Jaron Lanier, Jeff Bezos, knowledge economy, lateral thinking, linked data, low cost airline, low skilled workers, M-Pesa, mass immigration, Northern Rock, Paradox of Choice, peak oil, pensions crisis, precautionary principle, precision agriculture, prediction markets, Ralph Nader, Ray Kurzweil, rent control, RFID, Richard Florida, self-driving car, speech recognition, synthetic biology, telepresence, the scientific method, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Turing test, Victor Gruen, Virgin Galactic, white flight, women in the workforce, work culture , Zipcar

Toffler, Alvin (1970) Future Shock, Random House. Williams, Robyn (2007) Future Perfect, Allen & Unwin. Sources 309 Risk and risk management Aon Analytics (2009) Global Risk Management Survey, Aon Analytics. Bernstein, Peter L (1996) Against the Gods: The Remarkable Story of Risk, John Wiley & Sons. Taleb, Nassim Nicholas (2007) The Black Swan: The Impact of the Highly Improbable, Allen Lane. World Economic Forum (2007) Global Risks 2008, WEF. (The 2009 report is available online at www.weforum.org/pdf/globalrisk/2009.pdf.) Scenarios and scenario planning Freeman, Oliver (2004) Building Scenario Worlds, Richmond Ventures.


pages: 317 words: 106,130

The New Science of Asset Allocation: Risk Management in a Multi-Asset World by Thomas Schneeweis, Garry B. Crowder, Hossein Kazemi

asset allocation, backtesting, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, book value, business cycle, buy and hold, capital asset pricing model, collateralized debt obligation, commodity trading advisor, correlation coefficient, Credit Default Swap, credit default swaps / collateralized debt obligations, currency risk, diversification, diversified portfolio, financial engineering, fixed income, global macro, high net worth, implied volatility, index fund, interest rate swap, invisible hand, managed futures, market microstructure, merger arbitrage, moral hazard, Myron Scholes, passive investing, Richard Feynman, Richard Feynman: Challenger O-ring, risk free rate, risk tolerance, risk-adjusted returns, risk/return, search costs, selection bias, Sharpe ratio, short selling, statistical model, stocks for the long run, survivorship bias, systematic trading, technology bubble, the market place, Thomas Kuhn: the structure of scientific revolutions, transaction costs, value at risk, yield curve, zero-sum game

The Journal of Portfolio Management 18, No. 2 (Winter 1992): 7–19. Siegel, J.J. Stocks for the Long Run: The Definitive Guide to Financial Market Returns and Long-Term Investment Strategies, 4th ed. New York: McGrawHill, 2008. Szado, E., and T. Schneeweis. “Loosening the Collar.” CISDM Working Paper, 2009. Taleb, N. The Black Swan. New York: Random House, 2007. Tobin, James. “Liquidity Preference as Behavior Toward Risk.” Review of Economic Studies 25, Issue 2 (February 1958): 65–86. Tokat, Y., N. Wicas, and F. Kinniry. “The Asset Allocation Debate: A Review and Reconciliation.” Journal of Financial Planning 19, No. 10 (2006): 52–63.


pages: 359 words: 96,019

How to Turn Down a Billion Dollars: The Snapchat Story by Billy Gallagher

Airbnb, Albert Einstein, Amazon Web Services, AOL-Time Warner, Apple's 1984 Super Bowl advert, augmented reality, Bernie Sanders, Big Tech, Black Swan, citizen journalism, Clayton Christensen, computer vision, data science, disruptive innovation, Donald Trump, El Camino Real, Elon Musk, fail fast, Fairchild Semiconductor, Frank Gehry, gamification, gentrification, Google Glasses, Hyperloop, information asymmetry, Jeff Bezos, Justin.tv, Kevin Roose, Lean Startup, Long Term Capital Management, Mark Zuckerberg, Menlo Park, minimum viable product, Nelson Mandela, Oculus Rift, paypal mafia, Peter Thiel, power law, QR code, Robinhood: mobile stock trading app, Salesforce, Sand Hill Road, Saturday Night Live, Sheryl Sandberg, side project, Silicon Valley, Silicon Valley startup, skeuomorphism, Snapchat, social graph, SoftBank, sorting algorithm, speech recognition, stealth mode startup, Steve Jobs, TechCrunch disrupt, too big to fail, value engineering, Y Combinator, young professional

New York: Viking, 2009. Stone, Brad. The Everything Store: Jeff Bezos and the Age of Amazon. New York: Little, Brown and Company, 2013. ________. The Upstarts: How Uber, Airbnb, and the Killer Companies of the New Silicon Valley Are Changing the World. New York: Little, Brown and Company, 2017. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. New York: Random House, 2007. Thompson, Derek. Hit Makers: The Science of Popularity in an Age of Distraction. New York: Penguin, 2017. Tzu, Sun. The Art of War. date unknown; https://www.amazon.com/Art-War-Sun-Tzu/dp/1599869772/ref=sr_1_1?s=books&ie=UTF8&qid=1501497433&sr=1-1&keywords=the+art+of+war Vance, Ashlee.


pages: 592 words: 161,798

The Future of War by Lawrence Freedman

Albert Einstein, autonomous vehicles, Berlin Wall, Black Swan, Boeing 747, British Empire, colonial rule, conceptual framework, crowdsourcing, cuban missile crisis, currency manipulation / currency intervention, disinformation, Donald Trump, Dr. Strangelove, driverless car, drone strike, en.wikipedia.org, energy security, Ernest Rutherford, failed state, Fall of the Berlin Wall, Francis Fukuyama: the end of history, global village, Google Glasses, Herman Kahn, Intergovernmental Panel on Climate Change (IPCC), John Markoff, long peace, megacity, Mikhail Gorbachev, military-industrial complex, moral hazard, mutually assured destruction, New Journalism, Norbert Wiener, nuclear taboo, open economy, pattern recognition, Peace of Westphalia, RAND corporation, Ronald Reagan, South China Sea, speech recognition, Steven Pinker, Strategic Defense Initiative, Stuxnet, Suez canal 1869, Suez crisis 1956, systematic bias, the scientific method, uranium enrichment, urban sprawl, Valery Gerasimov, Wargames Reagan, WarGames: Global Thermonuclear War, WikiLeaks, zero day

Office of the Director of National Intelligence, Global Trends 2010, revised edition (Washington DC: National Intelligence Council, February 1997). Available: https://www.dni.gov/index.php/about/organization/national-intelligence-council-global-trends/global-trends-2010. On the influence of ‘black swan’ as unexpected events see Nassim Nicholas Taleb, Black Swan: The Impact of the Highly Improbable, (London: Penguin, 2008). 35. Office of the Director of National Intelligence, Global Trends 2015: A Dialogue About the Future with Nongovernment Experts (Washington DC: National Intelligence Council, December 2000). 36. Office of the Director of National Intelligence, Mapping the Global Future: Report of the National Intelligence Council’s 2020 Project (Washington DC: National Intelligence Council, December 2004). 37.

It was not surprising that the council was caught out by specific events that in principle might have been foreseeable (the 1998 financial crash was an early example), but each successive edition considered how they might do better in anticipating a discontinuity, something that was not a trend at the time of writing, or a ‘black swan’, a rare event that seemed to come from nowhere yet changed everything.33 When the series started, the document picked up on the key themes of the 1990s—the impact of globalisation, that most conflicts were internal to states rather than between them, that precision-guided munitions and information technologies would ‘continue to be the hallmarks of the revolution in military affairs’ and the likelihood that adversaries would attempt to blunt this US advantage using ‘asymmetric means—ranging from the increased use of terrorism to the possible use of weapons of mass destruction’.


pages: 397 words: 112,034

What's Next?: Unconventional Wisdom on the Future of the World Economy by David Hale, Lyric Hughes Hale

"World Economic Forum" Davos, affirmative action, Alan Greenspan, Asian financial crisis, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, behavioural economics, Berlin Wall, biodiversity loss, Black Swan, Bretton Woods, business cycle, capital controls, carbon credits, carbon tax, Cass Sunstein, central bank independence, classic study, cognitive bias, collapse of Lehman Brothers, collateralized debt obligation, corporate governance, corporate social responsibility, creative destruction, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, currency manipulation / currency intervention, currency peg, currency risk, Daniel Kahneman / Amos Tversky, debt deflation, declining real wages, deindustrialization, diversification, energy security, Erik Brynjolfsson, Fall of the Berlin Wall, financial engineering, financial innovation, floating exchange rates, foreign exchange controls, full employment, Gini coefficient, Glass-Steagall Act, global macro, global reserve currency, global village, high net worth, high-speed rail, Home mortgage interest deduction, housing crisis, index fund, inflation targeting, information asymmetry, Intergovernmental Panel on Climate Change (IPCC), inverted yield curve, invisible hand, Just-in-time delivery, Kenneth Rogoff, Long Term Capital Management, low interest rates, Mahatma Gandhi, Martin Wolf, Mexican peso crisis / tequila crisis, Mikhail Gorbachev, military-industrial complex, Money creation, money market fund, money: store of value / unit of account / medium of exchange, mortgage tax deduction, Network effects, new economy, Nicholas Carr, oil shale / tar sands, oil shock, open economy, passive investing, payday loans, peak oil, Ponzi scheme, post-oil, precautionary principle, price stability, private sector deleveraging, proprietary trading, purchasing power parity, quantitative easing, race to the bottom, regulatory arbitrage, rent-seeking, reserve currency, Richard Thaler, risk/return, Robert Shiller, Ronald Reagan, Savings and loan crisis, sovereign wealth fund, special drawing rights, subprime mortgage crisis, technology bubble, The Great Moderation, Thomas Kuhn: the structure of scientific revolutions, Tobin tax, too big to fail, total factor productivity, trade liberalization, Tragedy of the Commons, Washington Consensus, Westphalian system, WikiLeaks, women in the workforce, yield curve

See also Sharon Begley, Train Your Mind: Change Your Brain (New York: Ballantine Books, 2007). 2. Eyal Ophir, Clifford Nass, and Anthony D. Wagner, “Cognitive Control in Media Multitaskers.” Proceedings of the National Academy of Sciences, August 24, 2009. See also Mark Henderson, “Media Multi-taskers Are in Danger of Brain Overload,” Times of London, August 25, 2009. 3. Nassim N. Taleb, The Black Swan (New York: Random House, 2007). 4. Paul Kedrosky, “The First Disaster of the Internet Age,” Newsweek, October 27, 2008, http://www.newsweek.com/2008/10/17/the-first-disaster-of-the-internet-age.html. 5. Quoted in Nicholas D. Kristof, “The Daily Me,” New York Times, March 19, 2009. 6. Ibid. 7.


Manias, Panics and Crashes: A History of Financial Crises, Sixth Edition by Kindleberger, Charles P., Robert Z., Aliber

active measures, Alan Greenspan, Asian financial crisis, asset-backed security, bank run, banking crisis, Basel III, Bear Stearns, Bernie Madoff, Black Monday: stock market crash in 1987, Black Swan, Boeing 747, Bonfire of the Vanities, break the buck, Bretton Woods, British Empire, business cycle, buy and hold, Carmen Reinhart, central bank independence, cognitive dissonance, collapse of Lehman Brothers, collateralized debt obligation, Corn Laws, corporate governance, corporate raider, credit crunch, Credit Default Swap, credit default swaps / collateralized debt obligations, crony capitalism, cross-border payments, currency peg, currency risk, death of newspapers, debt deflation, Deng Xiaoping, disintermediation, diversification, diversified portfolio, edge city, financial deregulation, financial innovation, Financial Instability Hypothesis, financial repression, fixed income, floating exchange rates, George Akerlof, German hyperinflation, Glass-Steagall Act, Herman Kahn, Honoré de Balzac, Hyman Minsky, index fund, inflation targeting, information asymmetry, invisible hand, Isaac Newton, Japanese asset price bubble, joint-stock company, junk bonds, large denomination, law of one price, liquidity trap, London Interbank Offered Rate, Long Term Capital Management, low interest rates, margin call, market bubble, Mary Meeker, Michael Milken, money market fund, money: store of value / unit of account / medium of exchange, moral hazard, new economy, Nick Leeson, Northern Rock, offshore financial centre, Ponzi scheme, price stability, railway mania, Richard Thaler, riskless arbitrage, Robert Shiller, short selling, Silicon Valley, South Sea Bubble, special drawing rights, Suez canal 1869, telemarketer, The Chicago School, the market place, The Myth of the Rational Market, The Wealth of Nations by Adam Smith, too big to fail, transaction costs, tulip mania, very high income, Washington Consensus, Y2K, Yogi Berra, Yom Kippur War

Simon Johnson and James Kwak authored 13 Bankers: The Wall Street Takeover and the Next Financial Meltdown. Raghuram G. Rajan wrote Fault Lines: How Hidden Fractures Still Threaten the World Economy, Joseph Stiglitz produced Freefall: America, Free Markets, and the Sinking of the World Economy and Nassim Nicholas Taleb brought out The Theory of Black Swan Events, a critique of the prevailing consensus in academic finance about market efficiency. Thomas Sowell’s contribution was The Housing Boom and Bust while a group of fifteen distinguished economists brought out The Squam Lake Report; Fixing the Financial System, with more than thirty recommendations for changes in regulations.

Continental Europeans interpreted this response as a mutiny by a great British institution, the navy, and this interpretation contributed to the British decision to stop pegging the pound to gold.60 War, revolution, restoration, change of regime, and mutiny come largely from outside the system; they are beyond the usual set of risky events that can be modeled as a probability distribution – hence they qualify as a ‘black swan’. Monetary and financial displacements are more difficult to describe as exogenous. But maladroit recoinage, tampering with gold-silver ratios under bimetallism, conversions undertaken to economize on government revenue that unexpectedly divert investor attention to other avenues, new lending that proves successful beyond all anticipation – these also are displacements.


pages: 351 words: 123,876

Beautiful Testing: Leading Professionals Reveal How They Improve Software (Theory in Practice) by Adam Goucher, Tim Riley

Albert Einstein, barriers to entry, Black Swan, business logic, call centre, continuous integration, Debian, Donald Knuth, en.wikipedia.org, Firefox, Grace Hopper, index card, Isaac Newton, natural language processing, off-by-one error, p-value, performance metric, revision control, six sigma, software as a service, software patent, SQL injection, the scientific method, Therac-25, Valgrind, web application

That way, staging becomes the final proving ground for our software before it goes into production, and our employees occasionally do find defects or, more likely, usability issues or performance issues that unit and functional testing did not uncover. # The best book about testing I’ve read this year is, by far, The Black Swan by Nassim Taleb (Random House), and this illustration comes entirely from him, with credit due. Of course, he took it from David Hume, who took it from some ancient Greeks…. * We do keep some element of sales and accounts payable, etc., on production, which is ever so slightly more stable, and has passed that “final test bed” of staging.


pages: 401 words: 119,488

Smarter Faster Better: The Secrets of Being Productive in Life and Business by Charles Duhigg

Air France Flight 447, Asperger Syndrome, Atul Gawande, behavioural economics, Black Swan, cognitive dissonance, Daniel Kahneman / Amos Tversky, data science, David Brooks, digital map, epigenetics, Erik Brynjolfsson, framing effect, high-speed rail, hiring and firing, index card, John von Neumann, knowledge worker, Lean Startup, Malcom McLean invented shipping containers, meta-analysis, new economy, power law, Saturday Night Live, Silicon Valley, Silicon Valley startup, statistical model, Steve Jobs, the scientific method, the strength of weak ties, theory of mind, Toyota Production System, William Langewiesche, Yom Kippur War

Wickens, “Attention in Aviation,” University of Illinois at Urbana-Champaign Institute of Aviation, Research Gate, February 1987, http://www.researchgate.net/publication/4683852_Attention_in_aviation; Christopher D. Wickens, “The Psychology of Aviation Surprise: An 8 Year Update Regarding the Noticing of Black Swans,” Proceedings of the 15th International Symposium on Aviation Psychology, 2009. critical than ever before Ludwig Reinhold Geissler, “The Measurement of Attention,” The American Journal of Psychology (1909): 473–529; William A. Johnston and Steven P. Heinz, “Flexibility and Capacity Demands of Attention,” Journal of Experimental Psychology: General 107, no. 4 (1978): 420; Robin A.

Oppenheimer, “Effects of Fluency on Psychological Distance and Mental Construal (or Why New York Is a Large City, but New York Is a Civilized Jungle),” Psychological Science 19, no. 2 (2008): 161–67; Adam L. Alter and Daniel M. Oppenheimer, “Uniting the Tribes of Fluency to Form a Metacognitive Nation,” Personality and Social Psychology Review 13, no. 3 (2009): 219–35; John Hattie and Gregory C. R. Yates, Visible Learning and the Science of How We Learn (London: Routledge, 2013); Nassim Nicholas Taleb, Antifragile: Things That Gain from Disorder (New York: Random House, 2012); Daniel M. Oppenheimer, “The Secret Life of Fluency,” Trends in Cognitive Sciences 12, no. 6 (2008): 237–41; Edward T. Cokely and Colleen M. Kelley, “Cognitive Abilities and Superior Decision Making Under Risk: A Protocol Analysis and Process Model Evaluation,” Judgment and Decision Making 4, no. 1 (2009): 20–33; Connor Diemand-Yauman, Daniel M.


pages: 481 words: 120,693

Plutocrats: The Rise of the New Global Super-Rich and the Fall of Everyone Else by Chrystia Freeland

"World Economic Forum" Davos, activist fund / activist shareholder / activist investor, Alan Greenspan, Albert Einstein, algorithmic trading, assortative mating, banking crisis, barriers to entry, Basel III, battle of ideas, Bear Stearns, behavioural economics, Bernie Madoff, Big bang: deregulation of the City of London, Black Monday: stock market crash in 1987, Black Swan, Boris Johnson, Branko Milanovic, Bretton Woods, BRICs, Bullingdon Club, business climate, call centre, carried interest, Cass Sunstein, Clayton Christensen, collapse of Lehman Brothers, commoditize, conceptual framework, corporate governance, creative destruction, credit crunch, Credit Default Swap, crony capitalism, Deng Xiaoping, disruptive innovation, don't be evil, double helix, energy security, estate planning, experimental subject, financial deregulation, financial engineering, financial innovation, Flash crash, Ford Model T, Frank Gehry, Gini coefficient, Glass-Steagall Act, global village, Goldman Sachs: Vampire Squid, Gordon Gekko, Guggenheim Bilbao, haute couture, high net worth, income inequality, invention of the steam engine, job automation, John Markoff, joint-stock company, Joseph Schumpeter, knowledge economy, knowledge worker, liberation theology, light touch regulation, linear programming, London Whale, low skilled workers, manufacturing employment, Mark Zuckerberg, Martin Wolf, Max Levchin, Mikhail Gorbachev, Moneyball by Michael Lewis explains big data, NetJets, new economy, Occupy movement, open economy, Peter Thiel, place-making, plutocrats, Plutonomy: Buying Luxury, Explaining Global Imbalances, postindustrial economy, Potemkin village, profit motive, public intellectual, purchasing power parity, race to the bottom, rent-seeking, Rod Stewart played at Stephen Schwarzman birthday party, Ronald Reagan, self-driving car, seminal paper, Sheryl Sandberg, short selling, Silicon Valley, Silicon Valley billionaire, Silicon Valley startup, Simon Kuznets, sovereign wealth fund, starchitect, stem cell, Steve Jobs, TED Talk, the long tail, the new new thing, The Spirit Level, The Wealth of Nations by Adam Smith, Tony Hsieh, too big to fail, trade route, trickle-down economics, Tyler Cowen: Great Stagnation, wage slave, Washington Consensus, winner-take-all economy, zero-sum game

“The Evolving Structure of the American Economy and the Employment Challenge.” Maurice R. Greenberg Center for Geoeconomic Studies working paper. Council on Foreign Relations Press, March 2011. Sull, Donald. Why Good Companies Go Bad and How Great Managers Remake Them. Harvard Business Review Press, 2005. Taleb, Nassim Nicholas. The Black Swan: The Impact of the Highly Improbable. Random House, 2007. Walter, Carl E., and Fraser J. T. Howie. Red Capitalism: The Fragile Financial Foundation of China’s Extraordinary Rise. John Wiley & Sons, 2011. Winters, Jeffrey A. Oligarchy. Cambridge University Press, 2011. Wolf, Martin.


pages: 542 words: 132,010

The Science of Fear: How the Culture of Fear Manipulates Your Brain by Daniel Gardner

Atul Gawande, availability heuristic, behavioural economics, Black Swan, Cass Sunstein, citizen journalism, cognitive bias, cognitive dissonance, Columbine, correlation does not imply causation, Daniel Kahneman / Amos Tversky, David Brooks, Doomsday Clock, feminist movement, haute couture, hindsight bias, illegal immigration, Intergovernmental Panel on Climate Change (IPCC), lateral thinking, Linda problem, mandatory minimum, medical residency, Mikhail Gorbachev, millennium bug, moral panic, mutually assured destruction, nuclear winter, Oklahoma City bombing, placebo effect, precautionary principle, public intellectual, Ralph Nader, RAND corporation, Ronald Reagan, social intelligence, Stephen Hawking, Steven Levy, Steven Pinker, the long tail, the scientific method, Timothy McVeigh, Tunguska event, uranium enrichment, Y2K, young professional

., The Seven Sins of Memory: How the Mind Forgets and Remembers, Houghton Mifflin, Boston, MA, 2001. Stewart, Bernard W., and Paul Kleihues (eds.),World Cancer Report, International Agency for Research on Cancer Press, Lyon, France, 2003. Sullum, Jacob, Saying Yes: In Defense of Drug Use, Jeremy P. Tarcher, New York, 2003. Taleb, Nassim Nicholas, The Black Swan: The Impact of the Highly Improbable, Random House, New York, 2007. Tavris, Carol, and Elliot Aronson, Mistakes Were Made (But Not by Me): Why We Justify Foolish Beliefs, Bad Decisions, and Hurtful Acts, Harcourt, San Diego, CA, 2007. Tetlock, Philip E., Expert Political Judgment, Princeton University Press, Princeton, NJ, 2005.


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Future Crimes: Everything Is Connected, Everyone Is Vulnerable and What We Can Do About It by Marc Goodman

23andMe, 3D printing, active measures, additive manufacturing, Affordable Care Act / Obamacare, Airbnb, airport security, Albert Einstein, algorithmic trading, Alvin Toffler, Apollo 11, Apollo 13, artificial general intelligence, Asilomar, Asilomar Conference on Recombinant DNA, augmented reality, autonomous vehicles, Baxter: Rethink Robotics, Bill Joy: nanobots, bitcoin, Black Swan, blockchain, borderless world, Boston Dynamics, Brian Krebs, business process, butterfly effect, call centre, Charles Lindbergh, Chelsea Manning, Citizen Lab, cloud computing, Cody Wilson, cognitive dissonance, computer vision, connected car, corporate governance, crowdsourcing, cryptocurrency, data acquisition, data is the new oil, data science, Dean Kamen, deep learning, DeepMind, digital rights, disinformation, disintermediation, Dogecoin, don't be evil, double helix, Downton Abbey, driverless car, drone strike, Edward Snowden, Elon Musk, Erik Brynjolfsson, Evgeny Morozov, Filter Bubble, Firefox, Flash crash, Free Software Foundation, future of work, game design, gamification, global pandemic, Google Chrome, Google Earth, Google Glasses, Gordon Gekko, Hacker News, high net worth, High speed trading, hive mind, Howard Rheingold, hypertext link, illegal immigration, impulse control, industrial robot, information security, Intergovernmental Panel on Climate Change (IPCC), Internet of things, Jaron Lanier, Jeff Bezos, job automation, John Harrison: Longitude, John Markoff, Joi Ito, Jony Ive, Julian Assange, Kevin Kelly, Khan Academy, Kickstarter, Kiva Systems, knowledge worker, Kuwabatake Sanjuro: assassination market, Large Hadron Collider, Larry Ellison, Laura Poitras, Law of Accelerating Returns, Lean Startup, license plate recognition, lifelogging, litecoin, low earth orbit, M-Pesa, machine translation, Mark Zuckerberg, Marshall McLuhan, Menlo Park, Metcalfe’s law, MITM: man-in-the-middle, mobile money, more computing power than Apollo, move fast and break things, Nate Silver, national security letter, natural language processing, Nick Bostrom, obamacare, Occupy movement, Oculus Rift, off grid, off-the-grid, offshore financial centre, operational security, optical character recognition, Parag Khanna, pattern recognition, peer-to-peer, personalized medicine, Peter H. Diamandis: Planetary Resources, Peter Thiel, pre–internet, printed gun, RAND corporation, ransomware, Ray Kurzweil, Recombinant DNA, refrigerator car, RFID, ride hailing / ride sharing, Rodney Brooks, Ross Ulbricht, Russell Brand, Salesforce, Satoshi Nakamoto, Second Machine Age, security theater, self-driving car, shareholder value, Sheryl Sandberg, Silicon Valley, Silicon Valley startup, SimCity, Skype, smart cities, smart grid, smart meter, Snapchat, social graph, SoftBank, software as a service, speech recognition, stealth mode startup, Stephen Hawking, Steve Jobs, Steve Wozniak, strong AI, Stuxnet, subscription business, supply-chain management, synthetic biology, tech worker, technological singularity, TED Talk, telepresence, telepresence robot, Tesla Model S, The future is already here, The Future of Employment, the long tail, The Wisdom of Crowds, Tim Cook: Apple, trade route, uranium enrichment, Virgin Galactic, Wall-E, warehouse robotics, Watson beat the top human players on Jeopardy!, Wave and Pay, We are Anonymous. We are Legion, web application, Westphalian system, WikiLeaks, Y Combinator, you are the product, zero day

This thriving criminal superorganism lives, breathes, and is controlled from within the deepest, darkest recesses of the Internet—the Dark Web, the inner sanctum of the digital underground and the nerve center of Crime, Inc. CHAPTER 11 Inside the Digital Underground Our representation of the standard criminal might be based on the properties of those less intelligent ones who were caught. NASSIM NICHOLAS TALEB, THE BLACK SWAN Dread Pirate Roberts (DPR) was the most wanted man in the digital underground. From within the darkest reaches of cyberspace, the mysterious outlaw ran a vast empire of covert criminality. He was the subject of a global manhunt, actively pursued by special agents from the FBI, Drug Enforcement Agency (DEA), ATF, Homeland Security, the Royal Canadian Mounted Police, Scotland Yard, and Interpol.

Adding 50 billion new objects to the global information grid by 2020 means that each of these devices, for good or ill, will be able to potentially interact with the other 50 billion connected objects on earth. The result will be 2.5 sextillion potential networked object-to-object interactions—a network so vast and complex it can scarcely be understood or modeled. The IoT will be a global network of unintended consequences and black swan events, ones that will do things nobody ever designed or purposely planned. While there may be serendipitous benefits of such a network, there is also every chance many of its developments will be undesirable, negatively affecting global security, personal privacy, and human rights. Moreover, if you think the number of error messages and application crashes we face today are a problem, just wait until the Web is embedded in everything from your car to your sneakers to your microwave.


pages: 550 words: 154,725

The Idea Factory: Bell Labs and the Great Age of American Innovation by Jon Gertner

Albert Einstein, back-to-the-land, Black Swan, business climate, Charles Babbage, Claude Shannon: information theory, Clayton Christensen, complexity theory, corporate governance, cuban missile crisis, Dennis Ritchie, Edward Thorp, Fairchild Semiconductor, Henry Singleton, horn antenna, Hush-A-Phone, information retrieval, invention of the telephone, James Watt: steam engine, Karl Jansky, Ken Thompson, knowledge economy, Leonard Kleinrock, machine readable, Metcalfe’s law, Nicholas Carr, Norbert Wiener, Picturephone, Richard Feynman, Robert Metcalfe, Russell Ohl, Sand Hill Road, Silicon Valley, Skype, space junk, Steve Jobs, Telecommunications Act of 1996, Teledyne, traveling salesman, undersea cable, uranium enrichment, vertical integration, William Shockley: the traitorous eight

The Schawlow and Townes March 1960 patent—No. 2,929,922—is titled “Maser and Maser Communications System.” In later years, it would become popular to say that the laser, during its early incarnation, was a solution looking for a problem—a quip apparently made by a colleague of Ted Maiman’s at Hughes Aircraft. In his bestselling book The Black Swan (New York: Random House, 2007), for instance, Nassim Nicholas Taleb asserts that the laser had “no real purpose.” The evidence contradicts this. 10 Joan Lisa Bromberg, The Laser in America, 1950–1970 (Cambridge, MA: MIT Press, 1991), p. 92. 11 The reason that a laser is so much more suited to carrying information than ordinary light is that it is highly ordered (coherent) and monochromatic. 12 “Research Breakthroughs in Optical Masers and Superconductors,” Bell Laboratories Record, March 1961.


pages: 1,544 words: 391,691

Corporate Finance: Theory and Practice by Pierre Vernimmen, Pascal Quiry, Maurizio Dallocchio, Yann le Fur, Antonio Salvi

"Friedman doctrine" OR "shareholder theory", accelerated depreciation, accounting loophole / creative accounting, active measures, activist fund / activist shareholder / activist investor, AOL-Time Warner, ASML, asset light, bank run, barriers to entry, Basel III, Bear Stearns, Benoit Mandelbrot, bitcoin, Black Swan, Black-Scholes formula, blockchain, book value, business climate, business cycle, buy and hold, buy low sell high, capital asset pricing model, carried interest, collective bargaining, conceptual framework, corporate governance, correlation coefficient, credit crunch, Credit Default Swap, currency risk, delta neutral, dematerialisation, discounted cash flows, discrete time, disintermediation, diversification, diversified portfolio, Dutch auction, electricity market, equity premium, equity risk premium, Eugene Fama: efficient market hypothesis, eurozone crisis, financial engineering, financial innovation, fixed income, Flash crash, foreign exchange controls, German hyperinflation, Glass-Steagall Act, high net worth, impact investing, implied volatility, information asymmetry, intangible asset, interest rate swap, Internet of things, inventory management, invisible hand, joint-stock company, joint-stock limited liability company, junk bonds, Kickstarter, lateral thinking, London Interbank Offered Rate, low interest rates, mandelbrot fractal, margin call, means of production, money market fund, moral hazard, Myron Scholes, new economy, New Journalism, Northern Rock, performance metric, Potemkin village, quantitative trading / quantitative finance, random walk, Right to Buy, risk free rate, risk/return, shareholder value, short selling, Social Responsibility of Business Is to Increase Its Profits, sovereign wealth fund, Steve Jobs, stocks for the long run, supply-chain management, survivorship bias, The Myth of the Rational Market, time value of money, too big to fail, transaction costs, value at risk, vertical integration, volatility arbitrage, volatility smile, yield curve, zero-coupon bond, zero-sum game

Loughran, Book-to-market across firm size, exchange, and seasonality: Is there an effect?, Journal of Financial and Quantitative Analysis, 32(3), 249–268, September 1997. R. Raghuram, Has financial development made the world riskier?, NHBER Working Paper, 2005. J. Ritter, The long-run performance of IPOs, Journal of Finance, 46(1), 3–27, March 1991. N.S. Taleb, The Black Swan, 2nd edn, Random House, 2010. For those wanting to know more about behavioural finance: M. Baker, R. Ruback, J. Wurgler, Behavioral corporate finance: A survey, in Handbook of Corporate Finance, Empirical Corporate Finance, E. Eckbo (Ed.), Elsevier/North Holland, 2007. A. Barnea, H. Cronqvist, S.

For a global view on risk: G. Bénéplanc, J.-Ch. Rochet, Risk Management in Turbulent Times, Oxford University Press, 2012. Deloitte, The Value Killers Revisited. A risk management study, 2014. S. Myint, F. Famery, The Handbook of Corporate Financial Risk Management, Risk Books, 2012. N.N. Taleb, The Black Swan. The Impact of the Highly Improbable, Penguin, 2008. Chapter 51 Managing operational real estate Fifty shades of rent Methods for managing operational real estate differ from group to group. Some prefer to remain the king of the castle and own their operational real estate, while others consider these blocked assets as frozen cash that could be better used in developing the group’s core business more rapidly.


pages: 1,034 words: 241,773

Enlightenment Now: The Case for Reason, Science, Humanism, and Progress by Steven Pinker

3D printing, Abraham Maslow, access to a mobile phone, affirmative action, Affordable Care Act / Obamacare, agricultural Revolution, Albert Einstein, Alfred Russel Wallace, Alignment Problem, An Inconvenient Truth, anti-communist, Anton Chekhov, Arthur Eddington, artificial general intelligence, availability heuristic, Ayatollah Khomeini, basic income, Berlin Wall, Bernie Sanders, biodiversity loss, Black Swan, Bonfire of the Vanities, Brexit referendum, business cycle, capital controls, Capital in the Twenty-First Century by Thomas Piketty, carbon footprint, carbon tax, Charlie Hebdo massacre, classic study, clean water, clockwork universe, cognitive bias, cognitive dissonance, Columbine, conceptual framework, confounding variable, correlation does not imply causation, creative destruction, CRISPR, crowdsourcing, cuban missile crisis, Daniel Kahneman / Amos Tversky, dark matter, data science, decarbonisation, degrowth, deindustrialization, dematerialisation, demographic transition, Deng Xiaoping, distributed generation, diversified portfolio, Donald Trump, Doomsday Clock, double helix, Eddington experiment, Edward Jenner, effective altruism, Elon Musk, en.wikipedia.org, end world poverty, endogenous growth, energy transition, European colonialism, experimental subject, Exxon Valdez, facts on the ground, fake news, Fall of the Berlin Wall, first-past-the-post, Flynn Effect, food miles, Francis Fukuyama: the end of history, frictionless, frictionless market, Garrett Hardin, germ theory of disease, Gini coefficient, Great Leap Forward, Hacker Conference 1984, Hans Rosling, hedonic treadmill, helicopter parent, Herbert Marcuse, Herman Kahn, Hobbesian trap, humanitarian revolution, Ignaz Semmelweis: hand washing, income inequality, income per capita, Indoor air pollution, Intergovernmental Panel on Climate Change (IPCC), invention of writing, Jaron Lanier, Joan Didion, job automation, Johannes Kepler, John Snow's cholera map, Kevin Kelly, Khan Academy, knowledge economy, l'esprit de l'escalier, Laplace demon, launch on warning, life extension, long peace, longitudinal study, Louis Pasteur, Mahbub ul Haq, Martin Wolf, mass incarceration, meta-analysis, Michael Shellenberger, microaggression, Mikhail Gorbachev, minimum wage unemployment, moral hazard, mutually assured destruction, Naomi Klein, Nate Silver, Nathan Meyer Rothschild: antibiotics, negative emissions, Nelson Mandela, New Journalism, Norman Mailer, nuclear taboo, nuclear winter, obamacare, ocean acidification, Oklahoma City bombing, open economy, opioid epidemic / opioid crisis, paperclip maximiser, Paris climate accords, Paul Graham, peak oil, Peter Singer: altruism, Peter Thiel, post-truth, power law, precautionary principle, precision agriculture, prediction markets, public intellectual, purchasing power parity, radical life extension, Ralph Nader, randomized controlled trial, Ray Kurzweil, rent control, Republic of Letters, Richard Feynman, road to serfdom, Robert Gordon, Rodney Brooks, rolodex, Ronald Reagan, Rory Sutherland, Saturday Night Live, science of happiness, Scientific racism, Second Machine Age, secular stagnation, self-driving car, sharing economy, Silicon Valley, Silicon Valley ideology, Simon Kuznets, Skype, smart grid, Social Justice Warrior, sovereign wealth fund, sparse data, stem cell, Stephen Hawking, Steve Bannon, Steven Pinker, Stewart Brand, Stuxnet, supervolcano, synthetic biology, tech billionaire, technological determinism, technological singularity, Ted Kaczynski, Ted Nordhaus, TED Talk, The Rise and Fall of American Growth, the scientific method, The Signal and the Noise by Nate Silver, The Spirit Level, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Thomas Kuhn: the structure of scientific revolutions, Thomas Malthus, total factor productivity, Tragedy of the Commons, union organizing, universal basic income, University of East Anglia, Unsafe at Any Speed, Upton Sinclair, uranium enrichment, urban renewal, W. E. B. Du Bois, War on Poverty, We wanted flying cars, instead we got 140 characters, women in the workforce, working poor, World Values Survey, Y2K

When pessimists are forced to concede that life has been getting better and better for more and more people, they have a retort at the ready. We are cheerfully hurtling toward a catastrophe, they say, like the man who fell off the roof and says “So far so good” as he passes each floor. Or we are playing Russian roulette, and the deadly odds are bound to catch up to us. Or we will be blindsided by a black swan, a four-sigma event far along the tail of the statistical distribution of hazards, with low odds but calamitous harm. For half a century the four horsemen of the modern apocalypse have been overpopulation, resource shortages, pollution, and nuclear war. They have recently been joined by a cavalry of more exotic knights: nanobots that will engulf us, robots that will enslave us, artificial intelligence that will turn us into raw materials, and Bulgarian teenagers who will brew a genocidal virus or take down the Internet from their bedrooms.

See populism authority, deference to, 5 autocracy vs. democracy, 202–3, 202, 470n15 automation, 118–19, 300, 331 Availability heuristic, 41–2 awareness of, 369, 381, 383 critical thinking courses and, 378 doomsday prophecies and, 293, 302 media coverage and, 42–4, 201 superforecasters and awareness of, 369 terrorism and, 42, 195 Axial Age, 23, 264, 411 Azerbaijan, 158 Baby Boomers, 225 and crime boom of the 1960s, 173–4 depression and, 280–81 emancipative values and, 226 happiness underachievement of, 273, 283–9, 288 opioid overdoses and, 184–5 and populism, 341–2, 342 secularization and, 437 suicide and, 279–80 Babylon, 253–4 Bacon, Francis, 383 Bailey, Ronald, 464n45 Ball, Lucille, 186 Balmford, Andrew, 122 Banaji, Mahzarin, xix Bangladesh democratization and, 442 environment of, 130 escape from poverty of, 85, 86 famine and stunting in, 71, 71, 72 fertility as decreasing in, 126 industrialization and women in the workforce, 94 War of Independence (1971), 160, 161 Bannon, Stephen, 430, 448, 449, 455n1 Banting, Frederick, 63 Baron, Jonathan, 369 Barrett, Clark, 17 Basque ETA movement, 195 Batbie, Anselme, 341 Baudelaire, Charles, 30 Bauer, Peter, 79 Bauman, Zygmunt, 397 Baumeister, Roy, 267, 477n20 Bayesian reasoning, 369–70, 380, 381, 393 Bazile, Leon, 376 Beatles, 257, 274 beauty in art, 395, 406, 407 counter-entropic patterns as, 18 evolutionary psychology of, 18, 407, 408, 426 intrinsic value of, 18, 35, 248, 414, 433–4 in religion, 432 from science, 34, 260, 386, 407–8, 433–4 Beccaria, Cesare, 12, 174, 417 BECCS (bioenergy with carbon capture and storage), 151 Beckett, Samuel, 456n10 Belarus, 209, 313 Belgium, 169, 170, 259 Bell, Daniel, 390 Benin, 203, 475n30 Benjamin, Walter, 39–40 Benny, Jack, 333 Bentham, Jeremy, 223, 417 Bergman, Ingmar, 280 Berlin, Isaiah, 344 Berlin Wall, 163, 200–201, 203 Berry, Ken, 316 Best, Charles, 63 Better Angels of Our Nature, The (Pinker), 45–6 battle deaths (1946–2016), 159–60, 159 capital punishment, 209, 211 democracy vs. autocracy, 202 genocide deaths, 161 hate crimes, 220 homicide rates, 171 homosexuality, decriminalization of, 223 most recent year of data, 156, 466n1 objections to reliance on data in, 43–7 racist, sexist, and homophobic opinions, 216 rape and domestic violence, 221 terrorism deaths, 194 trends of, generally, 156 victimization of children, 229 war between great powers, 157–8, 157 Betteridge’s Law of Headlines, 282, 404 Bettmann, Otto, 178–9, 185, 186 Bible antihumanistic content of, 440 crucifixion in, 208 despotism in, 199 in fabric of human knowledge, 433 famine in, 68 life expectancy in, 58 literal truth of, belief in, 489n53, 490n84 maternal pain and suffering in, 57 morality as relative in, 429 on the poor, 89 prophets in, 49, 293 suicide in, 278 See also God Bierce, Ambrose, 428 Big Bang, 17, 385, 424 Bill & Melinda Gates Foundation, 66 bin Laden, Osama, 443 biochar, 150 bioethics, research and committees for, 402 bioterrorism, 300–302, 305, 306–7 Birdzell, L. E., 79 black swans. See power-law distribution; rare events Blake, William, 92 Blank Slate, The: The Modern Denial of Human Nature (Pinker), 45, 373, 484n61 Bloom, Paul, 101–2 Blue Collar (film), 113 blue lies, 358–9 Bogotá, Colombia, 172 Bohr, Niels, 308 Boko Haram, 67, 162 Boltzmann, Ludwig, 15 Bonaparte, Napoleon, 84–5 books, 239, 260–61, 408 Borlaug, Norman, 75–6, 77 Bornstein, David, 50 Bosch, Carl, 75 Bosnia, 151, 404, 436 Boston, Massachusetts, 130, 172, 183 Botswana, 91, 141 Boyd, Richard, 429 Boyer, Paul, 311 brain consciousness and, 426 hearing and, 20–21 human investment in bigger, 22–3 intelligence and, 21, 242 as metabolically greedy organ, 242 pleasure and pain and, 414 See also cognitive biases; intelligence; reason Brand, Stewart, 77, 122, 123, 133, 149, 301–2, 463n32, 465n76 Brandt, Willy, 200 Branwen, Gwern, 303 Braudel, Fernand, 68, 69, 79 Brazil, 90, 109, 172, 178, 200 Brecht, Bertolt, 23, 224, 447 Brezhnev, Leonid, 203 Briand, Aristide, 164 Briggs, John, 463n32 Brink, David, 429 Brin, Sergey, 100 Brockman, John, 390 Brontë, Charlotte, 284 Bronze Age, life expectancy and, 54 Brooklyn Dodgers, 179 Brooks, Rodney, 477n20 Browning, Elizabeth Barrett, 230 Bruno, Giordano, 442 Bryce, Robert, 146 Buddhism, 23, 204, 412 Buffet, Warren, 117 bullying, 49 Burckhardt, Jacob, 165 Burke, Edmund, 341, 363, 366 Burkina Faso, 203 Burma.

New York: Basic Books. Sowell, T. 2015. Wealth, poverty, and politics: An international perspective. New York: Basic Books. Spagat, M. 2015. Is the risk of war declining? Sense About Science USA. http://www.senseaboutscienceusa.org/is-the-risk-of-war-declining/. Spagat, M. 2017. Pinker versus Taleb: A non-deadly quarrel over the decline of violence. War, Numbers, and Human Losses. http://personal.rhul.ac.uk/uhte/014/York%20talk%20Spagat.pdf. Stansell, C. 2010. The feminist promise: 1792 to the present. New York: Modern Library. Stanton, S. J., Beehner, J. C., Saini, E. K., Kuhn, C. M., & LaBar, K.


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The Irrational Bundle by Dan Ariely

accounting loophole / creative accounting, air freight, Albert Einstein, Alvin Roth, An Inconvenient Truth, assortative mating, banking crisis, Bear Stearns, behavioural economics, Bernie Madoff, Black Swan, Broken windows theory, Burning Man, business process, cashless society, Cass Sunstein, clean water, cognitive dissonance, cognitive load, compensation consultant, computer vision, Cornelius Vanderbilt, corporate governance, credit crunch, Credit Default Swap, Daniel Kahneman / Amos Tversky, delayed gratification, Demis Hassabis, Donald Trump, end world poverty, endowment effect, Exxon Valdez, fake it until you make it, financial engineering, first-price auction, Ford Model T, Frederick Winslow Taylor, fudge factor, Garrett Hardin, George Akerlof, Gordon Gekko, greed is good, happiness index / gross national happiness, hedonic treadmill, IKEA effect, Jean Tirole, job satisfaction, John Perry Barlow, Kenneth Arrow, knowledge economy, knowledge worker, lake wobegon effect, late fees, loss aversion, Murray Gell-Mann, name-letter effect, new economy, operational security, Pepsi Challenge, Peter Singer: altruism, placebo effect, price anchoring, Richard Feynman, Richard Thaler, Saturday Night Live, Schrödinger's Cat, search costs, second-price auction, Shai Danziger, shareholder value, Silicon Valley, Skinner box, Skype, social contagion, software as a service, Steve Jobs, subprime mortgage crisis, sunk-cost fallacy, The Wealth of Nations by Adam Smith, The Wisdom of Crowds, Tragedy of the Commons, ultimatum game, Upton Sinclair, Walter Mischel, young professional

Deep, readable, and providing refreshing evidence that there are domains and situations in which material incentives work in unexpected ways. We humans are humans, with qualities that can be destroyed by the introduction of economic gains. A must-read!” —Nassim Nicholas Taleb, New York Times bestselling author of The Black Swan: The Impact of the Highly Improbable “Surprisingly entertaining. . . . Ariely’s book makes economics and the strange happenings of the human mind fun.” —USA Today “A fascinating romp through the science of decision-making that unmasks the ways that emotions, social norms, expectations, and context lead us astray.”