Eugene Fama: efficient market hypothesis

The Myth of the Rational Market: A History of Risk, Reward, and Delusion on Wall Street
by Justin Fox
Published 29 May 2009

Outspoken critic of the efficient market hypothesis and the academic approach to finance. Alfred Cowles III Chicago Tribune heir who, while convalescing from tuberculosis in Colorado in the 1920s, decided to research the effectiveness of various stock market forecasters. The 1933 paper in which he documented that most of the forecasts weren’t very good was a landmark in stock market research, and led him—by way of Irving Fisher—to bankroll much early mathematical economic research. Eugene Fama Finance professor at the University of Chicago who in the late 1960s formulated the efficient market hypothesis. Later, in a series of empirical studies with Kenneth French in the 1990s, he showed that the evidence didn’t support his original hypothesis.

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Bubbles developed; markets failed. Much depended on the rules that governed the market, and the greatest impact of experimental economics has been on market design. Plott had even grander ambitions. During an academic year spent at the University of Chicago in the late 1970s, he asked Eugene Fama for advice on testing his efficient market hypothesis in an experimental setting. “He said his theory has nothing to do with experiments; it has to do with the U.S. stock market,” Plott recalled. “‘But don’t general principles apply?’ ‘No, it only applies to the U.S. stock market.’” It was against actual financial market data that the hypothesis would have to be tested.

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All research proceeded from the assumption that “pervasive market forces” invariably pushed security prices toward their correct, fundamental values. This had been well established empirically back in the 1960s, after all. Or had it? THE 1970 BOOK Predictability of Stock Prices, by Clive Granger and Oskar Morgenstern, reads as a sort of alternate-universe version of Eugene Fama’s far better known distillation of the efficient market hypothesis. Granger and Morgenstern had been members in good standing of the 1960s random walk fellowship. They were also big-time economists. Granger went on to win a Nobel Prize in Economics, for unrelated work, in 2002. Morgenstern was coauthor (if not quite cocreator) of the von Neumann-Morgenstern model for decision making under uncertainty that dominated economics and finance.

In Pursuit of the Perfect Portfolio: The Stories, Voices, and Key Insights of the Pioneers Who Shaped the Way We Invest
by Andrew W. Lo and Stephen R. Foerster
Published 16 Aug 2021

While financial advisers may add considerable value to your portfolio, make sure you know what you’re paying in fees and what you’re getting in return. 4 Eugene Fama and Efficient Markets WE’RE CONSTANTLY EXPOSED to quotations of stock prices, but we rarely give a thought to what this has to do with the true value of stocks. Eugene (Gene) Fama probably influences our thinking about price versus value more than anyone else today with his very simple hypothesis: when it comes to stocks, what you see is what you get. In other words, if the market for stocks is efficient, then market prices reflect our collective best guess as to the underlying intrinsic value of stocks. Fama first proposed the “efficient market hypothesis” (EMH) and then spent his career developing a wide range of tests of the EMH.

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Bloomberg Markets, October, http://rmerton.scripts.mit.edu/rmerton/wp-content/uploads/2015/11/Harvards_Financial-Scientist.pdf. Case, Karl E., and Robert J. Shiller. 2003. “Is There a Bubble in the Housing Market?” Brookings Papers on Economic Activity, no. 2: 299–362. Cassidy, John. 2010. “Interview with Eugene Fama.” The New Yorker, January 13, http://www.newyorker.com/news/john-cassidy/interview-with-eugene-fama. CFA Institute. 2015. “Looking Back: Thoughts from Investment Luminary Martin L. Leibowitz.” Other Webcast Series, April 8, https://www.cfainstitute.org/learning/products/multimedia/Pages/129155.aspx?WPID=BrowseProducts. Chambers, David, Elroy Dimson, and Justin Foo. 2015.

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“Keynes the Stock Market Investor: A Quantitative Analysis.” Journal of Financial and Quantitative Analysis 50, no. 4: 843–68. Chatnani, Niti Nandini. 2010. Commodity Markets: Operations, Instruments, and Applications. New Delhi: Tata McGraw-Hill. Clement, Douglas. 2007. “Interview with Eugene Fama.” Federal Reserve Bank of Minneapolis, https://www.minneapolisfed.org/publications/the-region/interview-with-eugene-fama. Cochrane, John H. 2001. “Review of Famous First Bubbles: The Fundamentals of Early Manias by Peter M. Garber.” Journal of Political Economy 109, no. 5: 1150–54. ________. 2013. “Bob Shiller’s Nobel.” The Grumpy Economist, October 15, http://johnhcochrane.blogspot.ca/2013/10/bob-shillers-nobel.html.

Capital Ideas Evolving
by Peter L. Bernstein
Published 3 May 2007

Swensen has achieved this remarkable track record by depending on Markowitz’s methods for optimizing the risk/return trade-off and out of deep respect for the Efficient Market Hypothesis. Yet he has done so by “establishing and maintaining an unconventional investment profile [requiring] acceptance of portfolios which frequently appear . . . imprudent in the eyes of conventional wisdom.” Today, it is Swensen’s approach that has become conventional wisdom. Before Eugene Fama of the University of Chicago Business School set forth the principles of the Efficient Market Hypothesis in 1965, there was no theory to explain why the market is so hard to beat and not even a recognition such a possibility might exist.

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Before Bill Sharpe’s bern_a03fpref.qxd 3/23/07 8:43 AM Page xiii Preface xiii articulation of the Capital Asset Pricing Model in 1964, there was no genuine theory of asset pricing in which risk plays a pivotal role—there were just rules of thumb and folklore. Before Franco Modigliani and Merton Miller’s work in 1958, there was no genuine theory of corporate finance and no understanding of what “equilibrium” means in financial markets—there were just rules of thumb and folklore.3 Before Eugene Fama set forth the principles of the Efficient Market Hypothesis in 1965, there was no theory to explain why the market is so hard to beat. There was not even a recognition that such a possibility might exist. Before Fischer Black, Myron Scholes, and Robert Merton confronted both the valuation and the essential nature of derivative securities in the early 1970s, there was no theory of option pricing—there were just rules of thumb and folklore.

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Finally, the proliferation of products, strategies, and innovation stemming from the options pricing model—what Eugene Fama has called “the biggest idea in economics of the century”—has been explosive, and may still have a long way to go.6 As just one example, the total notional amount of derivatives outstanding at the end of 2006 was $370 trillion, a number to make one’s head spin.*  The book begins by facing up front the attack on Capital Ideas by the proponents of Behavioral Finance—and especially on the idea of the Efficient Market Hypothesis. The next chapter describes the current views of Paul Samuelson, one of the great sages about market behavior and portfolio formation.

Toward Rational Exuberance: The Evolution of the Modern Stock Market
by B. Mark Smith
Published 1 Jan 2001

Black examined the investment recommendations made by the widely distributed Value Line Investment Survey and concluded that an investor who diligently followed Value Line’s advice would have outperformed the market by a statistically significant amount. In a truly efficient market, this should not be possible. Black effectively took up the challenge laid down in 1968 by Eugene Fama, who had said that the efficient market hypothesis could be assumed to be true if no trading methodology could be shown to systematically beat the market. Black seemed to have found such a market-beating approach, which consisted simply of following Value Line recommendations. He wryly noted, “It appears that most investment management organizations would improve their performance if they fired all but one of their securities analysts and then provided the remaining analyst with the Value Line service.”

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The behavioralists think that real-world investor behavior makes markets inefficient, thus allowing massive overvaluations, such as Shiller believed existed in late 1996, to occur. The behavioral school developed from a growing body of academic research, commencing in the 1970s, that uncovered “anomalies” that apparently contradicted the efficient market hypothesis. Recall that Eugene Fama, who originally coined the term “efficient market,” proposed that a market could be defined as “efficient” if it was impossible to devise trading strategies based on publicly available information that would enable an investor to earn a risk-adjusted rate of return greater than the market rate of return.

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GREENSPAN’S DILEMMA 1 Wall Street Journal, 8 May 2000. 2 Hersh Shefrin, Beyond Greed and Fear (Boston: Harvard Business School Press, 2000), p. 40. 3 Wall Street Journal, 8 May 2000. 4 Fischer Black, Journal of Finance 41, 1986. 5 Discussed at length in Shefrin. 6 Werner De Bondt and Richard Thaler, Journal of Finance 40, 1985. 7 Victor Bernard and Jacob Thomas, Journal of Accounting Research 27, 1989. 8 Lawrence Summers, Journal of Finance 41, 1986. 9 Narasimhan Jagadeesh and Sheridan Titman, Journal of Finance 48, 1993. 10 Eugene Fama and Kenneth French, Journal of Finance 47, 1992. 11 Eugene Fama, Journal of Financial Economics 49 (3), 1998. 12 Wall Street Journal, 7 January 1988. 13 Nicholas Dunbar, Inventing Money (New York: John Wiley & Sons, 2000), p. 130. 14 Ibid., p. 180. 15 Ibid., p. 188. 16 Ibid., p. 205. 17 Fama and French, Journal of Finance 47, 1992. 18 Robert Hagen, The New Finance (Englewood Cliffs, N.J.: Prentice Hall, 1995), p. 71. 19 Eugene Fama, Journal of Finance 46 (5), 1991. 20 Hagen, p. 71. 21 Wall Street Journal, 8 May 2000. 22 Ibid. 17.

The Power of Passive Investing: More Wealth With Less Work
by Richard A. Ferri
Published 4 Nov 2010

This work spawned many new ideas among academics and market researchers. Eugene Fama Eugene Fama was another early pioneer in portfolio theory. He received his undergraduate degree from Tufts University in 1960, and his Masters and Ph.D. from the University of Chicago in 1965. Fama’s meticulously researched Ph.D. thesis was published in 1965 and titled “The Behavior of Stock Market Prices.” The purpose of the paper was to test the theory that stock market prices are random and follow what’s commonly referred to today as a random walk.8 Fama’s work led to the formation of the efficient market hypothesis (EMH), which is a theory of efficient security pricing in free and open markets.

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As the number of actively managed funds increases, the odds that a portfolio will outperform decreases. In addition, the longer active funds are held, the worse the odds become for the active fund portfolio, until eventually there’s practically no chance of outperformance. Efficient Portfolios Eugene Fama coined the term efficient market hypothesis in his landmark 1965 thesis on the behavior of stock prices. Fama said that an efficient market exists when (1) information about the securities trading on a market is widely and cheaply available to all, (2) all known and available information is already reflected in security prices, (3) the current price of a security is agreed upon by a buyer and seller in a market, and it is the best estimate of the investment value of that security at the time, and (4) security prices will almost instantaneously change as new information about them appears in the market.1 Fama’s paper sparked a long debate over whether markets are efficient, and index fund advocates were naturally dragged into this debate.

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See Europe, Australasia, and Far East (EAFE) Early performance studies: Cowles Commission report mutual funds, rise of Nobel Prizes for quiet period and in roaring 60s Econometrica EDHEC Risk and Asset Management Research Centre Educator, advisor as Efficient Frontier Efficient market hypothesis Efficient market hypothesis (EMH) Ehrbar, A.F. Eisenhower, Dwight D. Ellis, Charles D. Ellison, Glenn Elton, Edwin EMH. See Efficient market hypothesis (EMH) Emotions, human Employee-directed retirement accounts Employee Retirement Income Securities Act (ERISA): breaches under, litigation and delegation of responsibility under fiduciary advisor types under purpose of safe harbor to 401(k) trustees section 3(38) Investment Manager small plans and Employer-sponsored retirement plans Endowment effect Endowment funds Equal-weighted index Equity mutual funds ERISA.

Quantitative Value: A Practitioner's Guide to Automating Intelligent Investment and Eliminating Behavioral Errors
by Wesley R. Gray and Tobias E. Carlisle
Published 29 Nov 2012

They agreed, however, on one very important point: both believed it was possible to outperform the stock market, a belief that flew in the face of the efficient market hypothesis. While it is true that Thorp's strategy was grounded in the random walk, a key component of the efficient market hypothesis, he disagreed with the efficient market believers that it necessarily implied that markets were efficient. Indeed, Thorp went so as far as to call his book Beat the Market. Buffett also thought the efficient market hypothesis was nonsense, writing in his 1988 Shareholder Letter15: This doctrine [the efficient market hypothesis] became highly fashionable—indeed, almost holy scripture in academic circles during the 1970s.

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TABLE 1.1 Long-Term Performance of Common Price Ratios (1964 to 2011) The counterargument to the empirical outperformance of value stocks is that these stocks are inherently more risky. In this instance, risk is defined as the additional volatility of the value stocks. Prolific finance researchers and founders of modern quantitative asset management analysis Eugene Fama and Ken French made this argument most forcefully in their 1992 paper, “The Cross-Section of Expected Stock Returns.” Behavioral finance researchers Joseph Lakonishok, Andrei Shleifer, and Robert Vishny argue in their 1994 paper, “Contrarian Investment, Extrapolation, and Risk,”25 that value strategies produce better returns, not because they are fundamentally riskier, but because they are contrarian to the “naïve” strategies followed by other investors.

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Quality and Price is the academic alternative to the Magic Formula because it draws its inspiration from academic research papers. We found the idea for the quality metric in an academic paper by Robert Novy-Marx called “The Other Side of Value: Good Growth and the Gross Profitability Premium.”10. The price ratio is drawn from the early research into value investment by Eugene Fama and Ken French. The Quality and Price strategy, like the Magic Formula, seeks to differentiate between stocks on the basis of … wait for it … quality and price. The difference, however, is that Quality and Price uses academically based measures for price and quality that seek to improve on the Magic Formula's factors, which might provide better performance.

Capital Ideas: The Improbable Origins of Modern Wall Street
by Peter L. Bernstein
Published 19 Jun 2005

They titled the paper “Capital Market Equilibrium and the Pricing of Corporate Liabilities.” At this point they received help from another quarter. Eugene Fama and Merton Miller had been aware of their work, had given them extensive comments on it, and were following their publishing ordeal. Now these two Chicago professors put in a good word for them at the Journal of Political Economy. That did the trick. Throughout this story, Merton Miller has played the role of power-broker. He had encouraged Eugene Fama, still a novice, to teach entirely new material. He had guided Scholes into finance. He had introduced Treynor to Modigliani.

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Hamilton repeatedly stressed a central idea of Dow Theory that prices on the New York Stock Exchange are “sufficient in themselves” to reveal everything worth knowing about business conditions. Here Hamilton was anticipating a radical concept that was to appear long after his death. In the 1960s, a group of college professors would develop the Efficient Market Hypothesis, based on the notion that stock prices reflect all available information about individual companies and about the economy as a whole. The Efficient Market Hypothesis, however, also looks back to Bachelier, for it assumes that information is so rapidly reflected in stock prices that no single investor can consistently know more than the market as a whole knows. Hamilton, on the contrary, believed that the market itself revealed what stock prices would do in the future.

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••• –Stephen Jay Gould Acknowledgments All authors who undertake projects like this need help from others. I have been unusually fortunate in having had such generous and essential assistance from the people named below. The book could never have taken shape without the participation of the people whose work it describes: Fischer Black, Eugene Fama, William Fouse, Hayne Leland, Harry Markowitz, John McQuown, Robert C. Merton, Merton Miller, Franco Modigliani, Barr Rosenberg, Mark Rubinstein, Paul Samuelson, Myron Scholes, William Sharpe, James Tobin, Jack Treynor, and James Vertin. Each of them spent long periods of time with me in interviews, and most of them engaged in voluminous correspondence and telephone conversations as well.

The Quants
by Scott Patterson
Published 2 Feb 2010

A quant touchstone, it soon became one of the most influential how-to books on investing ever written. It also flew in the face of an increasingly popular theory in academia that it was impossible to consistently beat the market. Spearheaded by University of Chicago finance professor Eugene Fama in the late 1960s, this theory was known as the efficient-market hypothesis (EMH). At bottom, EMH was based on the idea, as Bachelier had argued, that the market moves in a random fashion and that current prices reflect all known information about the market. That being the case, it’s impossible to know whether the market, or an individual stock, currency, bond, or commodity, will rise or fall in the future—the future is random, a coin flip.

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In the 1960s, Ed Thorp devised a mathematical method to price warrants that anticipated that Black-Scholes option-pricing formula. Efficient-market hypothesis: Based on the notion that the future movement of the market is random, the EMH claims that all information is immediately priced into the market, making it “efficient.” As a result, the hypothesis states, it’s not possible for investors to beat the market on a consistent basis. The chief proponent of the theory is University of Chicago finance professor Eugene Fama, who taught Cliff Asness and an army of quants who, ironically, went to Wall Street to try to beat the market in the 1990s and 2000s.

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“Everything I’m about to say isn’t true,” said Fama in a gruff voice tinged with the accent of his Boston youth. He walked to his chalkboard and wrote the following: Efficient-market hypothesis. “The market is efficient,” Fama said. “What do I mean by that? It means that at any given moment, stock prices incorporate all known information about them. If lots of people are drinking Coca-Cola, its stock is going to go up as soon as that information is available.” Students scribbled on their notepads, taking it all in. The efficient-market hypothesis, perhaps the most famous and long-lasting concept about how the market behaved in the past half century, was Fama’s baby.

Trillions: How a Band of Wall Street Renegades Invented the Index Fund and Changed Finance Forever
by Robin Wigglesworth
Published 11 Oct 2021

A onetime medical student who became one of the first programmer-economists, building on his mentor Markowitz’s work to demonstrate the power of a broad “market portfolio”—in other words, an index fund. EUGENE FAMA. A onetime jock turned legendary economist at the University of Chicago, whose efficient-markets hypothesis helped explain why markets are so hard to beat, and inspired the birth of passive investing. JOHN MCQUOWN. A ferociously determined, computer-obsessed banker who convinced Wells Fargo to establish a skunk works and assemble the biggest crew of economic superstars. They would go on to launch the first passive investment fund, which reshaped finance. REX SINQUEFIELD. A former Fama student who became the self-styled “Ayatollah” of the efficient-markets hypothesis, establishing the first S&P 500 index fund at American National Bank of Chicago.

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“A given investment in active may or may not be the best decision for an individual particular investor but for the system overall there is a benefit in the efficient allocation of capital,” Fraser-Jenkins argued.21 “Rather than looking at the real economy and seeking to understand its future development, passive allocation self-referentially looks to the financial economy to inform its asset allocation choices.” There is a conundrum at the heart of the efficient-markets hypothesis, often called the Grossman-Stiglitz Paradox after a seminal 1980 paper written by hedge fund manager Sanford Grossman and the Nobel laureate economist Joseph Stiglitz.22 “On the Impossibility of Informationally Efficient Markets” was a frontal assault on Eugene Fama’s theory, pointing out that if market prices truly perfectly reflected all relevant information—such as corporate data, economic news, or industry trends—then no one would be incentivized to collect the information needed to trade.

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Fama.” 16. Eugene Fama, “A Brief History of Finance and My Life at Chicago,” Chicago Booth Review, April 7, 2014, https://review.chicagobooth.edu/magazine/fall-2013/a-brief-history-of-finance. 17. The Nobel Prize, “Eugene F. Fama.” 18. Tyler Vigen, “Spurious Correlations,” www.tylervigen.com/spurious-correlations. 19. Eugene Fama, “The Behavior of Stock-Market Prices,” Journal of Business 38, no. 1 (January 1965). 20. Read, The Efficient Market Hypothesists, 102. 21. Institutional Investor, April 1968. 22. Roger Ibbotson, “Random Talks with Eugene Fama,” Ibbotson Associates, 2000. 23.

Misbehaving: The Making of Behavioral Economics
by Richard H. Thaler
Published 10 May 2015

However, in order to get such papers published at the time, one had to offer abject apologies for the results. Here is how Basu ended his paper: “In conclusion, the behavior of security prices over the fourteen-year period studied is, perhaps, not completely described by the efficient market hypothesis.” He stopped just short of saying “I am sorry.” Similarly, one of Eugene Fama’s students at the University of Chicago, Rolf Banz, discovered another anomalous finding, namely that portfolios of small firms outperformed portfolios of large firms. Here is his own apologetic conclusion in his paper published in 1981: “Given its longevity, it is not likely that it is due to a market inefficiency but it is rather evidence of a pricing model misspecification.”

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The results of this condition lie between the other two. 23 The Reaction to Overreaction With the facts confirmed—that “Loser” stocks did earn higher returns than the market—there was only one way to save the no-free-lunch component of the EMH, which says it is impossible to beat the market. The solution for the market efficiency folks was to fall back on an important technicality: it is not a violation of the efficient market hypothesis if you beat the market by taking on more risk. The difficulty comes in knowing how to measure risk. This subtlety was first articulated by Eugene Fama. He correctly pointed out that all tests of the no-free-lunch component of market efficiency were actually “joint tests” of two hypotheses: market efficiency and some model of risk and return. For example, suppose someone found that new firms have higher returns than old firms.

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Having made one correct prediction about the stock market, I am resolving not to make any more. 25 The Battle of Closed-End Funds Shiller’s work wounded the price-is-right component of the efficient market hypothesis, but it was not considered a fatal attack. Disputes about methodology still lingered. And, although it was hard to justify what happened that week in October 1987, efficient market advocates were unwilling to rule out a rational explanation. In the spring of 1988, the University of Chicago held a conference about the crash, and one panel included Eugene Fama and me. Gene spoke first and said the market should be congratulated for how quickly it had reached its new equilibrium, meaning that something must have happened to cause people to revise down their estimates of the future returns on the stock market, and prices had adjusted immediately, just as they “should.”

Transaction Man: The Rise of the Deal and the Decline of the American Dream
by Nicholas Lemann
Published 9 Sep 2019

But the truth was, he had now departed in a profound way from the core idea that financial markets are a healthy force because they always set prices efficiently. Back in 1978, in the introduction to a special issue of the Journal of Financial Economics devoted to his friend Eugene Fama’s efficient market hypothesis, Jensen wrote, “In the literature of finance, accounting, and the economics of uncertainty, the Efficient Market Hypothesis is accepted as a fact of life, and a scholar who purports to model behavior in a manner which violates it faces a difficult task of justification.” For Jensen to abandon this view was heresy to the minds of his old friends in financial economics.

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A few years earlier, two economists named Franco Modigliani and Merton Miller had published a paper arguing that the value of a company has nothing to do with the standard questions that professional investors had for years considered essential in deciding whether to buy a stock, such as how much debt the company is carrying and whether or not it pays dividends. In 1961, just before Jensen arrived, Miller moved to the University of Chicago, where one of his star graduate students was Eugene Fama. Fama developed, again through complicated statistical means, what he called the “efficient market hypothesis,” which holds that well-functioning financial markets will set the price of a stock accurately, and therefore analysts who try to learn about individual companies in detail in order to decide whether their stocks are overpriced or underpriced are essentially wasting their time.

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Rochester was self-consciously a Chicago outpost, maybe even more Chicago than Chicago itself, by virtue of its being so new and owing to the special zeal possessed by missionaries sent off to work some distance from the mother church. Jensen founded an academic journal there called the Journal of Financial Economics, with himself, Eugene Fama, and Robert Merton as coeditors. The world at large still thought of the corporation as the great, all-powerful father figure in the American economy, vast and impregnable, and of finance as a far more minor force. Adolf Berle routinely maintained that financial markets had become irrelevant because corporations no longer needed them—corporations were too rich.

End This Depression Now!
by Paul Krugman
Published 30 Apr 2012

By 1970 or so, however, the study of financial markets seemed to have been taken over by Voltaire’s Dr. Pangloss, who insisted that we live in the best of all possible worlds. Discussion of investor irrationality, of bubbles, of destructive speculation had virtually disappeared from academic discourse. The field was dominated by the “efficient-markets hypothesis,” promulgated by Eugene Fama of the University of Chicago, which claims that financial markets price assets precisely at their intrinsic worth, given all publicly available information. (The price of a company’s stock, for example, always accurately reflects the company’s value, given the information available on the company’s earnings, its business prospects, and so on.)

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The political scientist Henry Farrell, in a blog post, quickly responded by inviting readers to find other uses for the “notably rare exceptions” construction—for example, “With notably rare exceptions, Japanese nuclear reactors have been safe from earthquakes.” And the sad thing is that Greenspan’s response has been widely shared. There has been remarkably little rethinking on the part of finance theorists. Eugene Fama, the father of the efficient-markets hypothesis, has given no ground at all; the crisis, he asserts, was caused by government intervention, especially the role of Fannie and Freddie (which is the Big Lie I talked about in chapter 4). This reaction is understandable, though not forgivable. For either Greenspan or Fama to admit how far off the rails finance theory went would be to admit that they had spent much of their careers pursuing a blind alley.

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Right up to the crisis of 2008, movers and shakers insisted, as Greenspan did in the quotation that opened this chapter, that all was well. Moreover, they routinely claimed that financial deregulation had led to greatly improved overall economic performance. To this day it’s common to hear assertions like this one from Eugene Fama, a famous and influential financial economist at the University of Chicago: Beginning in the early 1980s, the developed world and some big players in the developing world experienced a period of extraordinary growth. It’s reasonable to argue that in facilitating the flow of world savings to productive uses around the world, financial markets and financial institutions played a big role in this growth.

Never Let a Serious Crisis Go to Waste: How Neoliberalism Survived the Financial Meltdown
by Philip Mirowski
Published 24 Jun 2013

In other words, economics tells us that economists will never be good predictors: One thing we are not going to have, now or ever, is a set of models that forecasts sudden falls in the value of financial assets, like the declines that followed the failure of Lehman Brothers in September. This is nothing new. It has been known for more than 40 years and is one of the main implications of Eugene Fama’s “efficient-market hypothesis” (EMH), which states that the price of a financial asset reflects all relevant, generally available information. If an economist had a formula that could reliably forecast crises a week in advance, say, then that formula would become part of generally available information and prices would fall a week earlier . . .

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This only served to pour gasoline on the blogosphere. The line quickly hardened within the counterreformation that the orthodox efficient-markets hypothesis had been confirmed by the crisis, and that economists had never borne the onus of predicting much of anything at all. This comes out quite clearly in the New Yorker interviews with Chicago economists: I asked Fama how he thought the theory, which says prices of financial assets accurately reflect all of the available information about economic fundamentals, had fared. Eugene Fama: I think it did quite well in this episode. Stock prices typically decline prior to and in a state of recession.

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How can that be consistent with the efficient markets hypothesis? Great, so now you know how to define “bubbles” for me. I’ve been looking for that for twenty years.30 If one imagines the faint echoes of the Seekers after they were left stranded by the flying saucers, then perhaps you begin to comprehend how complaints that economists didn’t predict or foresee the crisis are not going to change anyone’s mind in economics.31 Abortive Attempts to Close the Barn Door After the Horses Have Bolted As opposed to the out-and-out denial of a John Cochrane or a Eugene Fama or a John Taylor or a Robert Lucas, many neoclassical economists were sufficiently chastened or blindsided by events in the economic crisis to concede that “something” about orthodox theory needed to be changed.32 Of course, given the years that have elapsed, candidates for revision have tended to multiply.

Economics Rules: The Rights and Wrongs of the Dismal Science
by Dani Rodrik
Published 12 Oct 2015

All the steps in between—the reduction in interest rates as demand for dollar assets went up, the incentive of poorly supervised financial institutions to seek riskier instruments to maintain profits, the building up of financial fragility as portfolios expanded through short-term borrowing, the inability of shareholders to properly rein in bank CEOs, the bubble in housing prices—could be readily explained by existing frameworks. But economists had placed excessive faith in some models at the expense of others, and that turned out to be a big problem. Many of the favored models revolved around the “efficient-markets hypothesis” (EMH).7 The hypothesis had been formulated by Eugene Fama, a Chicago finance professor who would subsequently receive the Nobel Prize, somewhat awkwardly, in the same year as Robert Shiller. It says, in brief, that market prices reflect all information available to traders. For an individual investor, the EMH means that, without access to inside information, beating the market repeatedly is impossible.

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† Fama concedes that he doesn’t have a reason for why future economic prospects would have worsened so drastically, but he adds that he isn’t a macroeconomist, and macroeconomics has never been good at discerning when recessions are coming on. John Cassidy, “Interview with Eugene Fama,” New Yorker, January 13, 2010, http://www.newyorker.com/news/john-cassidy/interview-with-eugene-fama. ‡ Ninety percent of economists reportedly agree with the following proposition: “Fiscal policy (for example, tax cut and/or government expenditure increase) has a significant stimulative impact on a less than fully employed economy.” Greg Mankiw, “News Flash: Economists Agree,” February 14, 2009, Greg Mankiw’s Blog, http://gregmankiw.blogspot.com/2009/02/news-flash-economists-agree.html

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“fox” approaches in, 175 ignorant vs. calculating peasant hypotheses in, 75 individual behavior in, 17, 33, 39, 42, 49, 101, 102, 131, 137, 181–82 marginalists and, 119–22 models in, see models outsider views in, 6 pluralism in, 196–208 points of consensus in, 147–52, 194–95 power and responsibility and, 174–75 predictability in, 6, 26–28, 38, 40–41, 85, 104, 105, 108, 115, 132, 133, 139–40, 157, 175, 184–85, 202 progressive modeling in, 63–72 psychology and sociology of, 167–74 self-interest in, 21, 104, 158, 186–88, 190 shocks in, 130–31, 132 social sciences and, xii–xiii, 45, 181–82, 202–7 strengths and weaknesses of, xi supply and demand in, 3, 13–14, 20, 99, 119, 122, 128–30, 136–37, 170 trade-offs in, 193–94 twenty commandments for, 213–15 values in, 186–96 see also markets; models Economics, Education and Unlearning: Economics Education at the University of Manchester (PCES), 197n education: antipoverty programs and, 4, 55, 105–6 field experiments and variable factors in, 24 markets and, 198 models in, 36–37, 173 efficient-markets hypothesis (EMH), 156–58 Einstein, Albert, 80, 81, 113, 179 El Salvador, 86, 92–93 Elster, Jon, 79n emissions quotas, 188–90, 191–92 empirical method, models and, xii, 7, 46, 65, 72–76, 77–78, 137, 173–74, 183, 199–206 employment: in business cycles, 125–37 labor productivity and, 123 minimum wages and, 17–18, 28n, 114, 115, 124, 143, 150, 151 social and cultural considerations in, 181 see also unemployment endogenous growth models, 88 England, comparative advantage principle and, 52–53 entrepreneurs: corruption and, 91 taxation and, 74 Ethiopia, 86, 123 Europe: Great Recession in, 153, 156 income inequality in, 125, 139 trade agreements between U.S. and, 41 European Common Market, 59 European Union (EU), 76 evolution, theory of, 113–14 exchange rates, 2, 100, 149 experiments: economic models compared with, 21–25 field types of, 23–24, 105–8, 173, 202–5 Explaining Social Behavior: More Nuts and Bolts for the Social Sciences (Elster), 79n external validity, 23–24, 112 fables, models and, 18–21 factor endowments theory, 139–40 Fama, Eugene, 157, 159 Fassin, Didier, xiv Federalists, 187 Federal Reserve, U.S., 134–35, 151n, 158 Feenstra, Rob, 141 field experiments, 23–24, 105–8, 173, 202–5 financial costs, 70 financial industry: globalization of, 164–67 in Great Recession, 152–59, 184 financial markets, deregulation and, 143, 155, 158–59, 162 “Fine Is a Price, A” (Gneezy and Rustichini), 71n fines, 71 First Fundamental Theorem of Welfare Economics, 47–51, 54 fiscal policies, 75–76, 87, 88, 147–48, 149, 160–61, 171 Fischer, Stanley, 165–66 forward causation, 115 Foundations of Economic Analysis (Samuelson), 125 Fourcade, Marion, 79n, 200n France, comparative advantage principle and, 59–60 Freakonomics (Levitt and Dubner), 7 Free to Choose, 49 free trade, 11, 54, 141, 169, 170, 182–83, 194 Friedman, Milton: on assumptions in modeling, 25–26 on cigarette taxes, 27–28 on invisible hand theorem, 49 on liquidity and Great Depression, 134 on model complexity, 37 fuel subsidies, 193 functional distribution of income, 121 Galbraith, John Kenneth, 184 Galileo Galilei, 29 Gambetta, Diego, 34 game theory, 5, 14–15, 33, 36, 61–62, 103–4, 133 simultaneous vs. sequential moves in, 68 garment industry, general-equilibrium effects in, 57–58 Gelman, Andrew, 115 general-equilibrium interactions, 41, 56–58, 69n, 91, 120 General Theory of Second Best, 58–61 Germany, comparative advantage principle and, 59–60 Gibbard, Allan, 20 Gilboa, Itzhak, 72, 73 Gini coefficient, 138 globalization, 139–41, 143, 164–67, 184 Gneezy, Uri, 71n Gold Standard, 2, 127 goods and services, economic models and, 12 Gordon, Roger, 151n Grand Theory of Employment, Interest, and Money, The (Keynes), 128 greenback era, 127n Greenspan, Alan, 158, 159 gross domestic product (GDP), 151n labor productivity and, 123 growth diagnostics, 86–93, 90, 97, 110–11 Haldane, Andrew, 197 Hamilton, Alexander, 187 Hanna, Rema, 107 Hanson, Gordon, 141 Harvard University, xi, 111, 136, 149, 197, 198 Hausmann, Ricardo, 111 health care: in antipoverty programs, 4, 105–7 models and, 5, 36–37, 105–7 Heckscher, Eli, 139 Herndon, Thomas, 77 Hicks, John, 128, 133 Hiebert, Stephanie, xv Hirschman, Albert O., 144–45, 195, 210n–11n housing bubble, 153–54, 156 human capital, 87, 88, 92 Humphrey, Thomas M., 13n Hunting Causes and Using Them: Approaches in Philosophy and Economics (Cartwright), 22n import quotas, 149 incentives, 7, 170, 172, 188–92 income: functional distribution of, 121 military service and, 108 personal distribution of, 121 income inequality, 117, 124–25, 138–44, 147–49 deregulation in, 143 factor endowments theory in, 139–40 Gini coefficient and, 138 globalization in, 139–41, 143 in manufacturing, 141 offshoring in, 141 skill premium in, 138–40, 142 skill upgrading in, 140, 141, 142 technological change in, 141–43 trade in, 139–40 India, 107, 154 Indonesia, 166 industrial organization, 201 industrial revolution, 115 industry: developing economies and policies on, 75–76, 87, 88 government intervention and, 34–35 inflation, 185 in business cycles, 126–27, 130–31, 133, 135, 137 public spending and, 114 infrastructure, 87, 91, 111, 163 Institute for Advanced Study (IAS), xii–xiii, xiv School of Social Science at, xii Institute for International Economics, 159 institutions: development economics and, 98, 161, 202, 205–7 labor productivity and, 123 insurance, banking and, 155 interest rates, 39, 64, 110, 129–30, 156, 161 internal validity, 23–24 International Bank for Reconstruction and Development, 2 see also World Bank international economics, 201–2 International Monetary Fund (IMF), 1n, 2 Washington Consensus and, 160, 165 Internet, big data and, 38 “Interview with Eugene Fama” (Cassidy), 157n investment: business cycles and, 129–30, 136 foreign markets and, 87, 89, 90, 92, 165–67 income inequality and, 141 savings and, 129–30, 165–67 Invisible Hand Theorem, 48–50, 51n, 182, 186 Israel, 103, 188 day care study in, 71, 190–91 Japan: city growth models and, 108 income inequality and, 139 Jenkins, Holman W., Jr., 135n Jevons, William Stanley, 119 Kahneman, Daniel, 203 Kenya, 106–7 Keynes, John Maynard, 1–2, 31, 46, 165 on business cycles, 127–37 on liquidity traps, 130 see also models, Keynesian types of Klemperer, Paul, 36n Klinger, Bailey, 111n Korea, South, 163, 164, 166 Kremer, Michael, 106–7 Krugman, Paul, 136, 148 Kuhn, Thomas, 64n Kupers, Roland, 85 Kydland, Finn E., 101n labor markets, 41, 52, 56, 57, 92, 102, 108, 111, 119, 163 labor productivity, 123–24, 141 labor theory of value, 117–19 Lancaster, Kelvin, 59 Latin America, Washington Consensus and, 159–63, 166 Leamer, Edward, 139 learning, rule-based vs. case-based forms of, 72 Leijonhufvud, Axel, 9–10 Lepenies, Philipp H., 211n leverage, 154 Levitt, Steven, 7 Levy, Santiago, 3–4, 105–6 Lewis, W.

Smarter Investing
by Tim Hale
Published 2 Sep 2014

My reading of research on this subject would seem to suggest that a premium may exist, but that it is not certain, and it is less convincing than the value premium. An interview with Eugene Fama (one of the leading academic researchers of value and size effects) by Peter Tanous (1997) about the small cap effect included the following exchange: Fama: ‘The risk in my terms can’t be explained by the market. It means that because they move together, there is something about these small stocks that creates an undiversifiable risk. The undiversifiable risk is what you get paid for.’ Tanous: ‘What causes that risk?’ Fama: ‘You know, that’s an embarrassing question because I don’t know.’ Even Eugene Fama concludes the following: ‘The size premium is, however, weaker and less reliable than the value premium.’

…

It showed that in every year over the past five years (2007–2011) at least two-thirds of the stocks in the index exceeded or trailed the index return by more than 10 percentage points. This ranged from between about 65% to 80%. This research underlines just how important very broad diversification is, when trying to capture market returns. 6.5 Five key investment risk factors The CAPM model was refined by Professors Eugene Fama and Kenneth French, two renowned academics in the USA, who developed the idea based on empirical data that three main risk factors define the characteristics of equity risk more effectively (they explain around 95% of a portfolio’s risk) compared to Sharpe’s single market risk factor (explaining around 75% of a portfolio’s risk).

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As ever with market-timing decisions, the longevity with which value and growth styles can seem seriously out of kilter, combined with rapidity and magnitude of turnarounds, makes this a really tough game to play. Figure 11.8 A premium has existed for owning less healthy companies 1/1975 to 4/2013 Source: Data from Morningstar EnCorr. All rights reserved. Dimensional Fund Advisers. Why have value stocks outperformed growth stocks? That is a good and relevant question. Eugene Fama, a renowned academic explains (Tanous, 1997): ‘To me, stock prices are just the prices that produce the expected returns that people require to hold them. If they are growth companies, people are willing to hold them at a lower expected return … Value stocks may continue to take their knocks. Their prices reflect the fact that they are in poor times.

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing
by Burton G. Malkiel
Published 10 Jan 2011

The real estate bubble in the United States during 2006 and 2007 appeared to present convincing evidence that markets are not efficient. An increasing number of arguments against the efficient-market hypothesis appeared after the sharp sell-off in the real estate markets during 2008, and the associated collapse of the bonds that had been securitized by mortgages on single-family homes and on other real estate assets. In 2009, George Soros wrote that “the Efficient Market Hypothesis has been well and truly discredited by the crash of 2008.” The EMH was blamed as the villain for the financial crisis and was written off for dead by countless financial commentators.

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Is it true that high-beta portfolios will provide larger long-term returns than lower-beta ones, as the capital-asset pricing model suggests? Does beta alone summarize a security’s total systematic risk, or do we need to consider other factors as well? In short, does beta really deserve an alpha? These are subjects of intense current debate among practitioners and academics. In a study published in 1992, Eugene Fama and Kenneth French divided all traded stocks into deciles according to their beta measures over the 1963–90 period. Decile 1 contained the 10 percent of all stocks that had the lowest betas; decile 10 contained the 10 percent that had the highest betas. The remarkable result, shown in the chart below, is that there was essentially no relationship between the return of these decile portfolios and their beta measures.

…

Better explanations than those given by the CAPM can be obtained for the variation in returns among different securities by using, in addition to the traditional beta measure of risk, a number of systematic risk variables, such as sensitivity to changes in national income, in interest rates, and in the rate of inflation. Of course, the APT measures of risk are beset by some of the same problems faced by the CAPM beta measure. It is not yet certain how these new theories will stand up to more extensive examination. THE FAMA-FRENCH THREE-FACTOR MODEL Eugene Fama and Kenneth French have proposed a factor model, like arbitrage pricing theory, to account for risk. Two factors are used in addition to beta to describe risk. The factors derive from their empirical work showing that returns are related to the size of the company (as measured by the market capitalization) and to the relationship of its market price to its book value.

How Markets Fail: The Logic of Economic Calamities
by John Cassidy
Published 10 Nov 2009

If financial markets work properly, they help the economy to prosper: if they fail to provide financing for worthwhile capital projects, if they divert money to the worthless objects of speculative bubbles and fads, they are a hindrance to the economy. During the 1960s and ’70s, a group of economists, many of them associated with the University of Chicago, promoted the counterintuitive idea that the central processor works perfectly, and that speculative bubbles don’t exist. The efficient market hypothesis, which Eugene Fama, a student of Friedman, popularized, states that financial markets always generate the correct prices, taking into account all of the available information. What does this mean? In the case of an individual company, it implies that the stock price accurately reflects the best guesses of analysts, investors, and even the firm’s management about its future earnings prospects.

…

Arrow and Debreu had never intended for their work to be used in policy analysis: it was a purely theoretical analysis that explored the conditions under which a free market economy would display Pareto efficiency. Lucas and his followers claimed that a slightly modified version of the Arrow-Debreu model could be used to represent reality. It is in this sense that Lucas adopted the efficient market hypothesis to the entire economy. Eugene Fama and others had depicted the stock exchange and other financial exchanges as perfectly functioning markets. Lucas assumed that the market for consumer goods, the market for workers, and practically every other market were equally efficient and stable. The only imperfection in the entire economy that Lucas allowed for was a somewhat implausible one: he assumed that, for short periods, individual workers couldn’t distinguish between rises in their own wages and increases in the overall price level.

…

When the bubble burst, in March and April 2000, the Soros funds lost close to $2.5 billion; soon after that, Druckenmiller resigned. If rational herding is a big factor in financial markets, the prices of stocks and other securities should display some predictable patterns. As I explain in Part I, Eugene Fama and other defenders of the efficient market hypothesis claimed that stocks moved randomly, but during the 1980s and ’90s, strong evidence emerged that this wasn’t the case. Researchers showed that stocks did better in January than in other months, and did better on Mondays than on other days of the week. They also showed that small cap stocks outperform large cap stocks; and that value stocks—those with a low price-to-dividend ratio or price-to-earnings ratio—outperform growth stocks.

The Rise of the Quants: Marschak, Sharpe, Black, Scholes and Merton
by Colin Read
Published 16 Jul 2012

His mission was especially relevant following the economic discipline’s colossal inability to predict the Great Crash in 1929 or to solve the Great Depression during the 1930s. He actually produced original work on the random walk and lamented whether stock prices could be forecast.2 He was pondering the efficient market hypothesis as early as 1933, well before Eugene Fama helped coin the expression and a new finance paradigm in the 1960s. The grandson of Alfred Cowles, the founder of the Chicago Tribune newspaper, and the son of newspaperman and corporate board director Alfred Cowles Jr., Cowles III’s insights and his wealth motivated him to 14 The Rise of the Quants form the Econometric Society and fund its journal, Econometrica.

…

In particular, low-risk and low-beta stocks seem to offer higher returns than the model would predict. If finance wishes to preserve the belief that markets are efficient, then the CAPM model does not seem to work. On the other hand, if the CAPM model is preserved, then the efficient market hypothesis does not hold, despite Applications 73 the notion that the CAPM model is tautologically similar to the efficient market approach.6 The efficient market hypothesis will be described in greater detail in the next volume in this series. These various authors proposed a plot between returns against betas, or risk premium measures. There should be a strong correlation between the two, with an intercept term of zero that signifies that a zero beta is equivalent to the risk-free asset.

…

To help in the analysis and development of a ranking system, he assembled William Sharpe, then at the University of Washington and an obvious advocate of the CAPM way of viewing funds, and the young professor Michael Jensen, who brought to the mix the notion of the new efficient market hypothesis approach from his home institution, the University of Chicago. Obviously, three great minds bringing to bear three different techniques on one problem would release a great deal of intellectual energy. At the end of their collaboration, the efficient market hypothesis prevailed and they agreed that no strategy could consistently beat the market, even though their client wished to be told otherwise. Black wrote up his reasoning by building on insights from his collaboration and from past files, notes, and papers Treynor had left at Arthur D.

Fortune's Formula: The Untold Story of the Scientific Betting System That Beat the Casinos and Wall Street
by William Poundstone
Published 18 Sep 2006

The favored analogy was, you might as well choose stocks by throwing darts at the financial pages. This skepticism became formalized as the efficient market hypothesis. It claims that the market is so good at setting fair prices for stocks that no one can achieve better returns on their investment than anyone else, save by sheer luck. University of Chicago economist Eugene Fama developed the idea both theoretically and empirically. There is much truth in the efficient market hypothesis. The controversy has always been over just how far the claim can be pressed. Asking whether markets are efficient is like asking whether the world is round.

…

Over all, it would seem to be a moderately ‘long run’ with a high probability that the excess performance is more than chance.” Hong Kong Syndicate AT A 1998 UCLA CONFERENCE, Eugene Fama “pointed to me in the audience and called me a criminal,” said Robert Haugen. Haugen’s “crime” was that he was a prominent academic critic of the efficient market hypothesis. Fama “then said that he believed that God knew that the stock market was efficient.” The efficient market hypothesis is far from dead. The rhetoric, as strident as ever, provides scant evidence that the track records of a few successful hedge funds have changed many minds.

…

Information was nonetheless a key feature of Fama’s analysis. In a 1970 article, Fama used information sources to distinguish three versions of the efficient market hypothesis. Fama’s “weak form” of the hypothesis asserts that you can’t beat the market by predicting a stock’s future prices from knowledge of its past prices. This takes aim at technical analysts, people who look at charts of stock prices and try to spot patterns predictive of future movements. The weak form (in fact, all the forms of the efficient market hypothesis) says that technical analysis is worthless. The “semistrong form” says that you can’t beat the market by using any public information whatsoever.

Hubris: Why Economists Failed to Predict the Crisis and How to Avoid the Next One
by Meghnad Desai
Published 15 Feb 2015

Robert Lucas, the doyen of modern macroeconomics and a Nobel Prize winner (1995), said, One thing we are not going to have, now or ever, is a set of models that forecasts sudden falls in the value of financial assets, like the declines that followed the failure of Lehman Brothers in September. This is nothing new. It has been known for more than forty years and is one of the main implications of Eugene Fama’s “efficient-market hypothesis” (EMH) which states that the price of a financial asset reflects all relevant, generally available information. If an economist had a formula that could reliably forecast crises a week in advance, say, then that formula would become part of generally available information and prices would fall a week earlier.4 The discussion has since moved on to what to do about the Great Recession.

…

The implication was that experts could not outguess the market, which was the result of interaction among thousands of buyers and sellers of stocks. The market was generating “correct” prices and could not be beaten by predictive modeling. This insight led to the idea of the efficient market hypothesis (EMH). The idea is associated with the Chicago economist Eugene Fama, who did extensive statistical research on stock prices. The result was that the change in a stock price between today and tomorrow could not be predicted from the change over the previous 24 hours or earlier. When he was jointly awarded the Nobel Prize in 2013 with Lars Peter Hansen, also of University of Chicago, and Robert Shiller of Yale University, it was for “empirical analysis of asset prices.”

…

While some economists urge abandonment of the fancy models and going back to the older theories of Keynes with a policy of greater public spending, the bulk of the economics profession in the best universities is as smug as ever. The award of the Nobel (actually the Royal Bank of Sweden) Prize in Economics in recent years is a clue to how unshaken the profession is in its self image. Thus in 2013 the Nobel Prize was given to Eugene Fama (Chicago), Lars Peter Hansen (Chicago) and Robert Shiller (Yale). Only Shiller is at all unorthodox, though a fully paid member of the mathematical macromodeling club. Thomas Sargent (formerly Minnesota now New York University) and Christopher Sims (Princeton) received the Prize in 2011 and both are original contributors to the “new classical economics” paradigm which is thought to have been discredited by the recession.

The Four Pillars of Investing: Lessons for Building a Winning Portfolio
by William J. Bernstein
Published 26 Apr 2002

The late John Brooks, dean of the last generation of financial journalists, had an even more cynical interpretation: when a famous investor publishes a newsletter, it’s a sure tip-off that his techniques have stopped working. Eugene Fama Cries “Eureka!” If Irving Fisher towered over financial economics in the first half of the twentieth century, there’s no question about who did so in the second half: Eugene Fama. His story is typical of almost all of the recent great financial economists—he was not born to wealth, and his initial academic plans did not include finance. He majored in French in college and was a gifted athlete.

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There have been a large number of studies of the growth-versus-value question in many nations over long periods of time. They all show the same thing: unglamorous, unsafe value stocks with poor earnings have higher returns than glamorous growth stocks with good earnings. Probably the most exhaustive work in this area has been done by Eugene Fama at the University of Chicago and Kenneth French at MIT, in which they examined the behavior of growth and value stocks. They looked at value versus growth for both small and large companies and found that value stocks clearly had higher returns than growth stocks. Figure 1-18 and the data below summarize their work: Fama and French’s work on the value effect has had a profound influence on the investment community.

…

First, iShares does offer indexed ETFs for single nations. I’d recommend against them because of complexity and cost—these funds carry expense ratios of nearly 1%, far higher than those of the open-end funds. Second, there is Dimensional Fund Advisors (DFA). These folks are among the best and brightest in finance, with a strong connection to Eugene Fama and the University of Chicago. DFA indexes just about any asset class you might want, including small, value, and even small value foreign markets. They also have individual funds for small stocks from the U.K., Continental Europe, Japan, Pacific Rim, and emerging markets. Better yet, their index funds for the U.S. market have much more focused exposure to value and small stocks than Vanguard or the other indexers.

The Great Economists Ten Economists whose thinking changed the way we live-FT Publishing International (2014)
by Phil Thornton
Published 7 May 2014

The first was Samuelson’s discovery that in competitive markets, where participants have full access to information, price movements over time will be essentially random. This influenced the trend among the investor community towards index-based funds rather than striving to achieve superior performance by ‘beating’ the market. It also laid the foundation of the efficient-market hypothesis, the theory set out by Eugene Fama, who shared the Nobel Prize in 2013 for that work. Similarly his work on the pricing of warrants – options to buy, at a future date, stock issued by a company – laid the ground for research on how to price financial options. This earned Nobel Prizes for Robert Merton, Fischer Black and Myron Scholes, but also led indirectly to the massive growth in complex financial products. 188 The Great Economists Long-term legacy There is no doubt that Paul Samuelson has left a permanent imprint on the understanding and teaching of economics.

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The NAIRU has been used as a tool for guiding the setting of interest rates by central banks over the last few decades. The significant role and power that the Chicago School of economics has in the current macroeconomic debate can be traced back to the amount of effort Friedman put in to establishing the monetarist doctrine at the University of Chicago. In late 2013 two more economists from the university, Eugene Fama and Lars Peter Hansen, who had carried out separate research into the behaviour of asset prices in a way that followed Friedman’s logic, won the Nobel Prize. Economics in action The application of Friedman’s theories in economic policy has had a mixed track record. As hinted at earlier, Friedman’s thinking had a huge influence on the first administrations of both Ronald Reagan in the US and Margaret Thatcher in the UK.

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Bush 139 influence on Margaret Thatcher 138–9 influence on Ronald Reagan 139 influence on the monetarists 138–9 key economic theories 122–36 key ideas 142 libertarian views 134–6, 140 long-term legacy 137–41 nature of the free market system 131–3 Nobel Prize (1974) 137 opposition to central state planning 134–6, 140 out of fashion 129–31 prices and knowledge 131–3 Prices and Production (1931) 126, 130 rejection of government control of the economy 120 study of philosophy and economics 121–22 The Road to Serfdom (1944) 135, 138, 140 time and the value of capital 124–6 verdict 141–2 Hegel, Georg 51–2, 54 herd behaviour 105 heuristics and bias in decision making 222–5 Hicks, John 173 High Speed 2 train line from London to the North 125 hindsight bias 227 242Index Hobbes, Thomas 5 hubris hypothesis 227 human behaviour, Becker’s approach 212–15 human capital theory (Becker) 200–2, 210 human decision making processes (Kahneman) 221–5 Hume, David 4, 97 Hutcheson, Francis 3–4 illusion of validity concept 220, 224 income inequality in the present day 64–6 individualism, view of Friedman 155–7 industrial districts 84–6, 87 industrial economics 84–6, 87 Industrial Revolution 11 inflation 107, 110 actions of the central banks 161 and Keynesian policies 127 and money supply 151–2 relationship with unemployment 153–5 Institute of Economic Affairs 138, 161 interest rates effects of adjustments 103–4 effects of credit expansion 123–4 natural rate of interest (Hayek) 123 intergenerational economics 178–80 International Bank of Reconstruction and Development 109 international economics and trade, view of Samuelson 183–7 International Monetary Fund (IMF) 108–9, 113, 186 international trade and comparative advantage (Ricardo) 35–8 international trade theory 184–5 intervention during economic depression, view of Keynes 92–3, 94, 105–6 investment, volatility caused by uncertainty 104–5 invisible hand concept (Smith) 7–9 Johnson, Harry 94 Johnson, Lyndon B. 110, 190 joint-stock companies 86 Kahneman, Daniel (1934– ) 206, 217–36 behavioural economics 218–19, 233–6 biases and errors in financial decision making 225–32 cognitive biases 222–5 decision making under risk 228–32 early life and influences 219–20 economic writings and theories 221–32 from psychology to economics 225–32 gambler’s fallacy (misconception of chance) 224 heuristics and bias in decision making 222–5 human decision making processes 221–5 illusion of validity concept 220, 224 long-term legacy 233–4 loss aversion 230–2 multidisciplinary approach to economics 218 Nobel Prize for economic sciences (2002) 218, 220 optimism bias and overconfidence 226–7 Prospect Theory 228–32, 234 Thinking, Fast and Slow (2012) 226–7, 234 verdict 235–6 Kennedy, John F. 110, 190 Keynes, John Maynard (1883–1946) 19, 73, 86, 91–116, 171 aggregate demand and the role of government 102–4 Bretton Woods agreement 95, 108–9 causes of unemployment 101 challenging the classical consensus 99–106 Index243 clash with Hayek 120, 126–31 criticism from monetarists 110–11 criticism of self-correction of markets 99, 105–6 criticism of the gold standard 95, 98, 107 criticism of the quantity theory of money 97 drivers of recession 101 early life and influences 93–4 effects of changes in money supply 97 effects of interest rate adjustments 103–4 effects of reducing wages 101–2 elevation to the House of Lords 106 end of the Keynesian revival 113–14 First World War and aftermath 95–7 focus on demand side economics 127 General Theory 99–106 Great Crash (1929) 98, 99 Great Depression (1930s) 99–100 International Bank of Reconstruction and Development 109 International Monetary Fund 108–9 investments as King’s College Bursar 98, 114 investor expectations and uncertainty 104–5 key ideas 115–16 liquidity preference theory 105, 113 long-term legacy 109–14 marginal propensity to consume (MPC) 103 marginal propensity to save (MPS) 103 move into economics 94–8 multiplier concept 103 national economist to international statesman 106–9 paradox of thrift 101 periods in and out of favour 92–3 plans for post-WWII international economy 107–9 popularity of Keynesianism 109–10 revival in the 2008 financial crisis 111–13 savings and investment 100–1 Second World War and aftermath 106–9 severe falls in output 101–2 state intervention during economic depression 92–3, 94, 105–6 Treaty of Versailles 95–6 and investment volatility 104–5 unpopularity beginning in the 1970s 110–11 verdict 115 Keynes, John Neville 93 Klaus, Vaclav 140 Kotlikoff, Laurence 179 Krugman, Paul 180, 191 Kuznets, Simon 148 Laar, Mart 140 labour-intensive goods, effects of increase in wages 33 labour market, human capital concept 200–2, 210 laissez-faire economic system 9 rejection by Keynes 105–6 law of diminishing returns 31 Lehman Brothers collapse (2008) 42, 67 Leviathan (Hobbes) 5 Levitt, Steve 234 libertarian views Friedman 157 Hayek 134–6, 140 life choices, economic perspective 203–6 Lindbeck, Assar 168 liquidity preference theory 105, 113 London School of Economics (LSE) 122, 126, 128 loss aversion 230–2 Lucas, Robert 202 244Index Mackintosh, William 109 Malthus, Thomas Robert 31, 33, 169 marginal analysis 80–2 marginal change concept (Marshall) 80–2 marginal propensity to consume (MPC) 103 marginal propensity to save (MPS) 103 marginal rate of substitution 180 market equilibrium price 76–7 market mechanism (Smith) 15–16 market price, supply and demand factors 15–16 market self-correction, criticism by Keynes 99, 105–6 marriage, economic perspective 203–6 Marshall, Alfred (1842–1924) 71–89, 170 and the business world 84–6 ceteris paribus approach to economic analysis 79–80 concept of time in supply and demand 77–9 early life and influences 73–4 economics as a science 73, 86 economics theories 75–86 elasticity of demand 82–4 geographical effects in economics 84–6 industrial districts 84–6, 87 industrial economics 84–6, 87 influence on Keynes 93, 95 interaction between costs and value 75–7 key ideas 88–9 long-term legacy 86–8 marginal analysis 80–2 marginal change concept 80–2 mathematical approach to economics 72 microeconomics 72, 86 political economy 74 price as interaction of supply and demand 75–9 Principles of Economics (1890) 72, 76, 77–8, 87–8, 188 supply and demand model 75–84 verdict 88 Marx, Karl (1818–83) 19, 49–68 and the global financial crisis (2008) 61–3 capitalist exploitation of the working class 56–8, 62–3 capitalist production process 54–6 communism 50 Communist Manifesto (Marx and Engels) 52, 58–61 Das Kapital 52, 53–4, 59–61, 62, 67–8 distribution of economic value 54–6 downfall of capitalism 56–8, 61–3 early life and influences 51–3 economics theories 53–8 ‘fictitious capital’ concept 62 income inequality in the present day 64–6 key ideas 68 long-term legacy 63–7 surplus value of labour 54–6 verdict 67–8 view of Marxist governments 66 mass production 11 Massachusetts Institute of Technology (MIT) 170 mathematical approach to economics Marshall 72 Samuelson 169–70 mercantilism 7–8, 22–3 mergers and acquisitions 226–7 Merton, Robert 187 microeconomics 172–3, 174, 196 work of Marshall 72, 86 Microsoft 233 middle class, rise of 64 Mieses, Ludwig von 121–2 Mill, James 30–1 Mill, John Stuart 30, 181 The Principles of Political Economy (1848) 188 Modigliani, Franco 173 monetarism 110, 138–9, 146, 151–2 monetarist rule 152 Index245 money supply and the Great Depression (1930s) 150–2 effects of changes in (Keynes) 97 role in running the economy 151–2 monopolies evil of 10–11 regulation to prevent 21–2 multiplier effect 103, 174–5 Murphy, Kevin 201, 210–12 NAIRU (non-accelerating inflation of unemployment) 153–5 Nashat, Guity 206 neoclassical synthesis 174 neo-Keynesianism 168–9, 173–5 net profit 81 New Classical Economics 159 New Deal (Franklin D. Roosevelt) 148 New Keynesianism 159, 163 New Neoclassical Synthesis 111 Nicholas I, Tsar 52 NINJA (No Income, No Job, No Assets) homebuyers 61–2 Nixon, Richard 109, 146 Nobel laureates Kenneth Arrow (1972) 191, 213 Gary Becker (1992) 194, 195–6 Ronald Coase (1991) 73 Peter Diamond (2010) 179 Eugene Fama (2013) 160, 187 Milton Friedman (1976) 146, 147–8, 154, 161 Lars Peter Hansen (2013) 160 Friedrich Hayek (1974) 137 Daniel Kahneman (2002) 218, 220 Paul Krugman (2008) 180, 191 Simon Kuznets (1971) 148 Robert Lucas (1995) 202 Robert Merton (1997) 187 Edmund Phelps (2006) 213 Paul Samuelson (1970) 168 Myron Scholes (1997) 187 Vernon Smith (2002) 218 non-accelerating inflation of unemployment (NAIRU) 153–5 Nordhaus, William 171, 178 North American Free Trade Agreement 41, 187 North, Lord 23 Obama, Barack 162, 190 offshoring of jobs 41 OPEC 22 opportunity cost concept 201, 205 optimism bias and overconfidence 226–7 outsourcing 21 overlapping generations (OLG) model 178–80 Pareto, Vilfredo 182 Pareto efficiency 182 pensions and pension funds 178 permanent income hypothesis (Friedman) 148–50 Perot, Ross 41 Phelps, Edmund 154, 213 Philip, Prince 158 Pigou, A.C. 95 Pinochet, Augusto 161 political economy 28, 74, 93 population growth theories Malthus 31 Ricardo 31, 32–3 Posner, Richard 215 Predictably Irrational (Ariely, 2009) 234 prejudice economic perspective of Becker 196–7, 198–9 views of Friedman 157 price, as interaction of supply and demand (Marshall) 75–9 prices and knowledge (Hayek) 131–3 Prices and Production (Hayek, 1931) 126, 130 Principles of Economics (Marshall, 1890) 72, 76, 77–8, 87–8, 188 private savings, influence of taxation policy 43–4 private sector windfalls, impact of stimulus measures 43–4 privatisation of state-owned monopolies 21 246Index productivity, and division of labour 11–14 Prospect Theory (Kahneman) 228–32, 234 protectionism 22–3, 33–5, 41–2, 185 public goods economics 175–8 purchasing price parity (PPP) measures 186 quantitative easing 162, 163 quantity theory of money, criticism by Keynes 97 Rae, John 23 rational choice model (Becker) 197, 212–15, 216 challenge from Kahneman 221–33 rational expectations hypothesis 111, 137 Reagan, Ronald 19, 20, 139, 146, 158, 160 recession drivers of (Keynes) 101 see also Great Recession (2009) reflection effect 229 revealed preference theory 180–1 reverse elasticity 84 Ricardo, Abraham 28–9 Ricardo, David (1772–1823) 27–46, 183 attack on the Corn Laws 33–5 early life and influences 28–30 from finance to economics 30–1 global free trade 40–2 government debt 38–9 influence of Adam Smith 30 international trade and comparative advantage 35–8 key ideas 46 long-term legacy 40–4 on the general workings of the economy 31–3 on wealth creation and distribution 31–3 political career 30 population growth theories 31, 32–3 The Principles of Political Economy and Taxation (1817) 28, 31–3, 188 Ricardian equivalence 38–9 Ricardo effect 33 verdict 45–6 wine and cloth example 35, 37, 40–1 Ricardian equivalence 38–9 Ricardo effect 33 Robbins, Lionel 122, 129 Rogeberg, Ole 211 Rogoff, Kenneth 189–90 Roosevelt, Franklin D. 148 Samuelson, Paul (1915–2009) 37, 106, 137, 159, 167–92 autarky concept 184 early life and influences 169–70 economics in action 190–1 Economics: An Introductory Analysis (1948) 168, 171–3, 188–9 efficient markets 187 ethical judgements in economics 182–3 explaining trade imbalances 184–5 factor price equalisation theorem 186–7 financial economics 187 Foundations of Economic Analysis (1947) 168, 169–70 global public goods 177–8 influence of Keynes 171–2 influence on economic theory 189–90 intergenerational economics 178–80 international economics and trade 183–7 key economic theories and writings 171–87 long-term legacy 188–91 mathematical approach to economic issues 169–70 microeconomic market system 172–3, 174 multiplier effect 174–5 Index247 neoclassical synthesis 174 neo-Keynesianism 168–9, 173–5 Nobel Prize in economic sciences (1970) 168 oscillator model of business cycles 174–5 overlapping generations (OLG) model 178–80 public goods and public finance 175–8 public goods economics 175–8 revealed preference theory 180–1 understanding consumer behaviour 180–1 verdict 191–2 warrant pricing 187 welfare economics 181–3 Scholes, Myron 187 Schwartz, Anna 150–1, 162 Scottish Enlightenment 3 Second World War 95, 96 self-interest theory of Adam Smith 2–3, 6, 8–9, 20 Skidelsky, Robert 114, 128 slavery 10–11 Smith, Adam (1723–90) 1–25, 97, 230–1 A Theory of Moral Sentiments (1759) 2, 5–6 division of labour and productivity 11–14 drivers of rates of pay 12–13 early life and character 3–5 free-market mechanism of supply and demand 8–9 free international trade 13–14 from philosophy to economics 6–7 functions funded by general taxation 16 functions of the state 16–18 functions that users should pay for 16–17 idea of ‘natural liberty’ 8 idea of ‘sympathy’ of people for each other 6 key ideas 25 long-term legacy 19–23 market price of a commodity 15–16 on slavery 10–11 personal legacy 23 pin factory example 11–13 role of the state in the economy 9, 10 self-interest theory 2–3, 6, 8–9, 20 taxation principles 17–18 the evil of cartels and monopolies 10–11 the invisible hand 7–9 the market mechanism 15–16 The Wealth of Nations (1776) 2–3, 6, 7–25, 188 verdict 23–4 Smith, Vernon 218 Smoot-Hawley Tariff Act (US) 42 social security systems 179 social welfare function 182–3 socialism 134–6 sovereign debt crisis in Greece 113–14 Soviet Union, collapse of 140, 158 Sraffa, Piero 130–1 stagflation in the 1970s 154, 173–4 Standard Oil Company of New Jersey 21 state-owned monopolies, privatisation programmes 21 Statecraft (Thatcher, 2002) 19 status quo bias 227–8 stimulus measures, debate over effects of 43–4 stimulus versus austerity debate 43–4, 140–1 Stockholm School of Economics 168 Stolper, Wolfgang 184–5 Stolper–Samuelson theorem 184–5 Strachey, Lytton 94 structural unemployment 155 substitution effect, response to price change 82, 83 Summers, Anita 190 Summers, Lawrence 190 Summers, Robert 190 Sunstein, Cass 234 248Index supply and demand market mechanism 8–9, 15–16, 75–84 supply side economics 127, 201 surplus value of labour (Marx) 54–6 taxation policy influence on private savings 43–4 views of Adam Smith 16–18 taxpayers, view of government debt (Ricardo) 38–9 Thaler, Richard 232, 234, 235 Thatcher, Margaret 19, 138–9, 155, 160–1 The General Theory of Employment, Interest and Money (Keynes, 1936) 99–106 The Principles of Political Economy (Mill, 1848) 188 The Principles of Political Economy and Taxation (Ricardo, 1817) 28, 31–3, 188 The Road to Serfdom (Hayek, 1944) 135, 138, 140 The Wealth of Nations (Smith, 1776) 2–3, 6, 7–25, 188 Thinking, Fast and Slow (Kahneman, 2012) 226–7, 234 time factor and the value of capital (Hayek) 124–6 in the supply and demand model 77–9 Townshend, Charles 5, 6–7 Toyota, production systems 21 trade barriers 22–3, 41–2, 185 Corn Laws 33–5 trade imbalances, Samuelson’s explanation 184–5 trade unions 19 transient income concept 149 Treatise on Human Nature (Hume) 4 Treaty of Versailles 95–6 Tversky, Amos 218, 220, 221–5, 228–33, 235 Ulam, Stanislaw 37 uncertainty and investment volatility 104–5 unemployment causes of (Keynes) 101 frictional 155 ‘natural’ rate of (Friedman) 153–5 relationship with inflation 153–5 structural 155 United States housing market crisis (2008) 61–2, 112 import tariffs after the Wall Street Crash 42 savings and investment imbalance with China 113 trade imbalance with China 45 US Federal Reserve 111–12 action to control inflation 161 and the 2008 financial crisis 235 influence of monetary policy 159 money supply and the Great Depression (1930s) 150–2 quantitative easing (2009 onward) 162 role in the Great Depression (1930s) 159 utilitarianism 31, 182 value and costs of production 75–7 distribution of economic value (Marx) 54–6 surplus value of labour (Marx) 54–6 Voltaire 7 wages drivers of wage rates (Smith) 12–13 effects of reducing (Keynes) 101–2 relationship to rents and profits 32–3 surplus value of labour (Marx) 54–6 Wall Street Crash (1929) 23, 42 Wallich, Henry 190–1 warrant pricing (Samuelson) 187 wealth creation and distribution, view of Ricardo 31–3 Index249 welfare economics 181–3 White, Harry Dexter 108 Wilberforce, William 10 Wittgenstein, Ludwig 121 women in the workforce 202 Wood, Kingsley 106 Woolf, Leonard 94 World Bank Group 109 World Trade Organization (WTO) 22, 40–1, 185 

Capitalism: Money, Morals and Markets
by John Plender
Published 27 Jul 2015

Among the chief strands of their work has been the so-called efficient markets hypothesis, pioneered by Eugene Fama in the 1960s and 1970s. There are differing versions of the thesis, but the most potent of them holds that financial assets are always correctly priced because competition between profit-seeking market participants ensures that any divergence between price and value will be quickly eliminated. Prices in financial markets are said to be an accurate reflection of all available information. In effect, the efficient markets hypothesis asserts that the level of the stock market represents a good forecast of the present value of the future earnings of all the companies quoted there.

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The ‘Bubble Lady’, as the press called her, spent years in jail, along with her bank manager patrons.85 When markets reach astonishing heights with the help of a toad, and the bursting of a property bubble precipitates the biggest recession in history, as happened in 2008, it might seem that the efficient markets hypothesis has a problem – namely, that it asserts, like Dr Pangloss in Voltaire’s Candide, that all is for the best in the best of all possible worlds. Yet in an interview with John Cassidy in the New Yorker magazine, Eugene Fama, chief architect of the theory, flatly denies it.86 He even argues that the financial crisis was not the cause of the recession, while saying he has no idea what the real cause was.

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In an extraordinary U-turn in a recent interview in the Harvard Business Review, he declared: ‘You can spot a bubble. They’re obvious in every respect.’ But he added that it was impossible to quash a bubble in a democratic society because it would lead to the Fed’s independence being curtailed.76 As for efficient market theorists such as Eugene Fama, they, too, remain unrepentant. How do they justify themselves? Consider this, first, from the perspective of financial history. In an academic paper, the economist Peter Garber has examined three great bubbles in detail: the Dutch tulip mania, in which contract prices for bulbs soared to astronomical heights and then collapsed; the Mississippi Bubble in France, a scheme engineered by the Scottish adventurer John Law which enjoyed a monopoly over French colonial trade and ended in a speculative frenzy fuelled by the issue of paper money; and the South Sea Bubble in England, where speculation hinged on the South Sea Company’s modest trading rights in the West Indies and South America, together with its purchase of the national debt in exchange for an annual payment from the Exchequer.77 On the seventeenth-century tulip euphoria, Garber argues that Charles Mackay failed to discuss what the fundamental price of tulips should have been, pointing out that there is a standard pricing pattern for new varieties of flowers that holds even today.

A Mathematician Plays the Stock Market
by John Allen Paulos
Published 1 Jan 2003

Confidence, whether justified or not, is convincing, especially when there aren’t many “facts of the matter.” This may be why market pundits seem so much more certain than, say, sports commentators, who are comparatively frank in acknowledging the huge role of chance. Efficiency and Random Walks The Efficient Market Hypothesis formally dates from the 1964 dissertation of Eugene Fama, the work of Nobel prize-winning economist Paul Samuelson, and others in the 1960s. Its pedigree, however, goes back much earlier, to a dissertation in 1900 by Louis Bachelier, a student of the great French mathematician Henri Poincare. The hypothesis maintains that at any given time, stock prices reflect all relevant information about the stock.

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Thus, if most investors believe the Sluggish Market Hypothesis is true, they will by their actions make the Efficient Market Hypothesis true. We conclude that if the Efficient Market Hypothesis is false, then it’s not the case that most investors believe the Sluggish Market Hypothesis to be true. That is, if the Efficient Market Hypothesis is false, then most investors believe it (the EMH) to be true. (You may want to read over the last few sentences in a quiet corner.) In summary, if the Efficient Market Hypothesis is true, most investors won’t believe it, and if it’s false, most investors will believe it. Alternatively stated, the Efficient Market Hypothesis is true if and only if a majority believes it to be false.

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Warped perhaps by my study of mathematical logic and its emphasis on paradoxes and self-reference, I’m naturally interested in the paradoxical and self-referential aspects of the market, particularly of the Efficient Market Hypothesis. Can it be proved? Can it be disproved? These questions beg a deeper question. The Efficient Market Hypothesis is, I think, neither necessarily true nor necessarily false. The Paradoxical Efficient Market Hypothesis If a large majority of investors believe in the hypothesis, they would all assume that new information about a stock would quickly be reflected in its price. Specifically, they would affirm that since news almost immediately moves the price up or down, and since news can’t be predicted, neither can changes in stock prices.

Trend Commandments: Trading for Exceptional Returns
by Michael W. Covel
Published 14 Jun 2011

To understand the LTCM debacle, it starts with two academic legends: Merton Miller and Eugene F. Fama who developed the Efficient-Markets Hypothesis. The premise of their hypothesis was that stock prices were always right so you could not divine the market’s future direction. It assumed that everyone was rational.2 Miller and Fama believed that perfectly rational people would never pay more or less for a financial instrument than it was actually worth. A colleague, and fervent supporter of the Efficient-Markets Hypothesis, Myron Scholes was also certain that markets could not make mistakes. He and his associate, Robert Merton, saw the finance universe as tidy and predictable.

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He would rather die with honor than fall into the hands of superior market wisdom.6 If you don’t know who you are, the markets are an expensive place to find out.8 Having lived through the financial crisis of 2007–08, the man in the street knows markets are not efficient. But the Efficient-Market Hypothesis, like a Hollywood monster, has proved very hard to kill off.7 Fortunately for you, there is a way out. There is inspiration. The great trend followers are not academics, magicians, charlatans, or pedigreed investment bankers. They are self-starter entrepreneurs who, through concentration, drive, and fierce independent streaks, have cultivated that rare knowledge to mint money. Trend following proves daily that the Efficient-Markets Hypothesis has more in common with Scientology, versus any useful trading enlightenment.

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Nearly all share the common assumption: When it comes to money, we are highly rational.3 One of the foremost champions of that view is Gary Becker: “The most powerful theory we have, and I think it’s the most powerful theory in the social sciences, is economics as a theory of rational behavior at an individual level, and that’s the theory we rely on.”4 Other academics are not on board for obvious reasons: “The 2008 crash really matters because much of the behavior that led up to the crash is unexplained by the discipline of economics.”5 Beware of consensus. More Chicago academics ignore the 2008 crash: “I’m sorry, that’s such an empty argument. That’s just an insult, a pointless insult.”6 Eugene Fama, the father of so-called efficient markets, smirked: “I don’t see this as a failure of economics, but we need a whipping boy, and economists have always been whipping boys, so they’re used to it. It’s fine.”7 26 Tre n d C o m m a n d m e n t s Those economists defend their view no matter what.

Heads I Win, Tails I Win
by Spencer Jakab
Published 21 Jun 2016

Of course, there’s a gigantic venue out there that already knows that analysts and other purported seers are full of it and it’s called the stock market. It takes thousands of pieces of information and millions of opinions and factors them into prices instantly, for better or worse. That’s the crux of the efficient market hypothesis put forward by Nobel Prize–winning economist Eugene Fama in his PhD dissertation a half century ago. The idea was popularized in the 1970s in a bestseller by Professor Burton Malkiel, A Random Walk Down Wall Street—a book I recommend highly to any active investor. It’s no coincidence that index funds debuted around the time it was published.

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A client goes down to Manhattan’s financial district and admires all of the fancy boats in the nearby marina, only to learn, after asking that naïve question, that they belong to the people who work there. Their customers can’t afford such luxuries. Aside from the title, Schwed was way ahead of his time. For example, he explained, using anecdotes, what would win another man, Eugene Fama, the Nobel Prize for a paper written thirty years later on the efficient-market hypothesis. And, thirty-five years before the first low-cost index fund was launched, he tore apart the rationale for investment trusts, a predecessor to today’s high-fee, actively managed mutual funds. Throughout the book he laments, using anecdotes and even cartoons, how savers are parted from their money.

…

To cite just one example of studies that say active management may be worth it, a recent one by researchers at Japanese investment bank Nomura showed that the stocks favored by active funds did slightly better and those shunned did slightly worse than the market.7 But what matters is your bottom line, not some measure that shows some modicum of stock-picking ability. A longer study by two of the most distinguished finance professors around, Nobel laureate Eugene Fama and Kenneth French, found that fund managers eked out alpha, or extra return, of 0.1 percent a year. Unfortunately, their net result after accounting for the expense of running a fund was negative 0.8 percent a year. We didn’t need these brilliant men to do thousands of calculations to tell us that, because common sense would dictate the same conclusion.

The Little Book of Hedge Funds
by Anthony Scaramucci
Published 30 Apr 2012

We also believe that hedge fund investors will continue to commit capital to mortgage strategies to seek out uncorrelated return streams, improve portfolio diversification, and achieve high risk-adjusted returns. Chapter Six Ironing Out Inefficiencies Exploiting the Efficient Market Theory If the efficient markets hypothesis was a publicly traded security, its price would be enormously volatile. —Andrei Shleifer and Lawrence H. Summers, The Noise Trader Approach to Finance In 1990, Andrei Shleifer and Larry Summers mockingly made the comment that begins this chapter, adding that the “stock in the efficient markets hypothesis—at least as it has been traditionally formulated—crashed along with the rest of the market on October 19, 1987 . . . and its recovery has been less dramatic than that of the rest of the market.”1 Pretty fun for a pair of economists from Harvard, especially for one who would serve as President Clinton’s Secretary of the Treasury and President Obama’s Director of the White House National Economic Council.

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It simply requires the ability to look at things in a different way . . . a contrarian way. A Kid in a Candy Store From the time of A.W. Jones until the mid 1980s, the overall sentiment in the marketplace was that hedge fund performance was mainly dictated by luck rather than strategy or skill. Why? The world of finance was operating under Eugene Fama’s efficient market theory, which was developed in the 1960s at the University of Chicago. Here is the gist of it. If markets were rendered efficient, it followed that prices would move in a random pattern, and consequently those who achieved high levels of success would be investors who most quickly acted upon the fundamental news that was available to everybody.

…

Hedge fund managers, being the contrarian investors that they are, would not just sit there and allow themselves to be the victim of such erratic behavior—especially in moments of crisis like that of Black Monday. Instead, they would discover ways in which to iron out the kinks . . . albeit with a little help from the same academics who told them the market was efficient in the first place! Living on the Edge Considered the father of the efficient market theory, Professor Eugene Fama ironically led the charge against it, diving headfirst into a theory that postulated that markets were—you guessed it—inefficient. Along with fellow economist Kenneth French, he discovered nonrandom patterns in the market that traders could pounce on to generate positive returns. And as they continued to study the long-term returns from the stock market, their research exposed certain market anomalies that hedge fund managers could exploit in order to correct inefficiencies and produce absolute returns. 1.

The Intelligent Asset Allocator: How to Build Your Portfolio to Maximize Returns and Minimize Risk
by William J. Bernstein
Published 12 Oct 2000

It is a recurring theme of almost all studies of “consensus” or “expert” opinion that it underperforms the market about three-fourths of the time. Mr. Dreman argues that this is a powerful argument against the efficient market hypothesis: how can the markets be efficient when the experts lose with such depressing regularity? All of this evidence falls under the rubric of what is known as market efficiency. A detailed discussion of the efficient market hypothesis is beyond the scope of this book, but what it means is this: it’s futile to analyze the prospects for an individual stock (or the entire market) on the basis of publicly available information, since that information has already been accounted for in the price of the stock (or market).

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We’ll come to the reason why in a minute. 98 The Intelligent Asset Allocator Math Details: The Ultimate Benchmark If you’re really serious about benchmarking a fund, as well as looking for skill, you perform a three-factor regression on fund returns. Here’s how it works. Developed by Ken French of MIT and Eugene Fama of University of Chicago, the regression starts with monthly returns for the broad stock market, as well as monthly return contributions for small-stock and value-stock exposure. You then lay the monthly returns for the fund or manager in question side by side with these three benchmark series and perform a multiple regression.This statistical technique, available on most spreadsheet packages, produces the “best fit” of the three factors to the manager returns series and spits out a blizzard of output numbers.The most- important of these is the residual return (the intercept of the regression),or alpha.The alpha is the excess return left after exposure to the market, size, and value have been taken into account.

…

Yin, Yang Rather than being polar opposites, momentum investing and fixedasset allocation with contrarian rebalancing are simply two sides of the same coin. Momentum in foreign and domestic equity asset classes exists, resulting in periodic asset overvaluation and undervaluation. Eventually long-term mean reversion occurs to correct these excesses. Over 2 decades ago, Eugene Fama made a powerful case that security price changes could not be predicted, and Burton Malkiel introduced the words “random walk” into the popular investing lexicon. Unfortunately, in a truly random-walk world, there is no advantage to portfolio rebalancing. If you rebalance, you profit only when the frogs in your portfolio turn into princes, and vice versa.

Money and Government: The Past and Future of Economics
by Robert Skidelsky
Published 13 Nov 2018

This is unsustainable and costly to society, as it amounts to resource misallocation and sows the seeds of the next banking crisis.10 One hugely important macroeconomic implication arises from treating banks as mere intermediaries between savers and investors. This is that markets determine a natural rate of interest which delivers full employment – precisely the claim which Keynes set out to refute. ‘Financial markets price risks correctly on average’ The efficient market hypothesis (EMH), made popular by Eugene Fama (1970, 1976) is the application of rational expectations to financial markets. The rational expectations hypothesis (REH) says that agents optimally utilize all available information about the economy and policy instantly to adjust their expectations. The 311 M ac roe c onom ic s i n t h e C r a s h a n d A f t e r , 2 0 0 7 – implication of this is that shares are always correctly priced on average, because investors adjust their buy/sell actions instantaneously and accurately to any newly released information.

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If there happened to be over-valued or under-valued assets, the very action of investors trying to sell/buy them to make a profit would work as a self-correcting mechanism. This important feature of the efficient market hypothesis postulates that markets are self-correcting and thus self-regulating, with government attempts to improve on this bound to be distorting.13 In this way, the efficient market hypothesis is essentially the modern manifestation of Adam Smith’s ‘invisible hand’. There is a paradox here. On the one hand, the theory says that 312 w h at wa s w rong w i t h t h e b a n k s? there is no point in trying to profit from speculation, because shares are always correctly priced and their movements cannot be predicted.

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The relationship between theory, practice and policy is a perennial issue in political economy. In the case of banking, this relationship turned toxic, as neo-classical economics, deregulation and financial ‘innovation’ worked together to precipitate financial crisis. The efficient market hypothesis discounted the possibility of financial crises happening. Regulators turned a blind eye to the build-up of stress in the banking system because they believed in the efficient market hypothesis. Banks used their new freedom from control to create evermore opaque financial instruments (‘securitization’). All three pledged themselves to the service of mankind. Spiralling out of control, the financial system collapsed.

Arguing With Zombies: Economics, Politics, and the Fight for a Better Future
by Paul Krugman
Published 28 Jan 2020

By 1970 or so, however, the study of financial markets seemed to have been taken over by Voltaire’s Dr. Pangloss, who insisted that we live in the best of all possible worlds. Discussion of investor irrationality, of bubbles, of destructive speculation had virtually disappeared from academic discourse. The field was dominated by the “efficient-market hypothesis,” promulgated by Eugene Fama of the University of Chicago, which claims that financial markets price assets precisely at their intrinsic worth given all publicly available information. (The price of a company’s stock, for example, always accurately reflects the company’s value given the information available on the company’s earnings, its business prospects, and so on.)

…

But there was something else going on: a general belief that bubbles just don’t happen. What’s striking, when you reread Greenspan’s assurances, is that they weren’t based on evidence—they were based on the a priori assertion that there simply can’t be a bubble in housing. And the finance theorists were even more adamant on this point. In a 2007 interview, Eugene Fama, the father of the efficient-market hypothesis, declared that “the word ‘bubble’ drives me nuts,” and went on to explain why we can trust the housing market: “Housing markets are less liquid, but people are very careful when they buy houses. It’s typically the biggest investment they’re going to make, so they look around very carefully and they compare prices.

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Behavioral finance, drawing on the broader movement known as behavioral economics, tries to answer that question by relating the apparent irrationality of investors to known biases in human cognition, like the tendency to care more about small losses than small gains or the tendency to extrapolate too readily from small samples (e.g., assuming that because home prices rose in the past few years, they’ll keep on rising). Until the crisis, efficient-market advocates like Eugene Fama dismissed the evidence produced on behalf of behavioral finance as a collection of “curiosity items” of no real importance. That’s a much harder position to maintain now that the collapse of a vast bubble—a bubble correctly diagnosed by behavioral economists like Robert Shiller of Yale, who related it to past episodes of “irrational exuberance”—has brought the world economy to its knees.

Stocks for the Long Run, 4th Edition: The Definitive Guide to Financial Market Returns & Long Term Investment Strategies
by Jeremy J. Siegel
Published 18 Dec 2007

If beta is greater than 1, the stock requires a return greater than the market, and if it is less than 1, a lesser return is required. Risk that can be eliminated through diversification (called diversifiable or residual risk) does not warrant a higher return. The “efficient market hypothesis” and the CAPM became the basis for stock return analysis in the 1970s and 1980s. Unfortunately, as more data were analyzed, beta did not prove successful at explaining the differences in returns among individual stocks or portfolios of stocks. In 1992, Eugene Fama and Ken French wrote an article, published in the Journal of Finance, which determined that there are two factors, one relating to the size of the stocks and the other to the valuation of stocks, that are far more important in determining a stock’s return than the beta of a stock.4 After further analyzing returns, they claimed that the evidence against the CAPM was “compelling” and that “the average return anomalies . . . are serious enough to infer that the [CAPM] model is not a useful approximation” of a stock’s return, and they suggested researchers investigate “alternative” asset pricing models or “irrational asset pricing stories.”5 2 The capital asset pricing model was developed by William Sharpe and John Lintner in the 1960s.

…

Beta, the second coefficient, is calculated from the correlation of an individual stock’s (or portfolio’s) return with a capitalization-weighted market portfolio. The first coefficient, alpha, is the average historical return on the stock or portfolio above the return on the market. 4 Eugene Fama and Ken French, “The Cross Section of Expected Stock Returns,” Journal of Finance, vol. 47 (1992), pp. 427–466. 5 Eugene Fama and Ken French, “The CAPM Is Wanted, Dead or Alive,” Journal of Finance, vol. 51, no. 5 (December 1996), pp. 1947–1958. CHAPTER 9 Outperforming the Market 141 Fama and French’s findings have prompted financial economists to classify the stock universe along two dimensions: size, measured by the market value of the stock, and valuation, or the price relative to “fundamentals” such as earnings and dividends.

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Further research has supported this contention. The chapter on the history of the S&P 500 Index shows that the new firms added to the index have generally had lower returns than the original firms that were chosen in 1957. In this edition, I introduce the “noisy market hypothesis,” an alternative to the efficient market hypothesis that explains why value stocks outperform growth stocks. In Chapter 20, I describe “fundamentally weighted” indexes as an efficient alternative to capitalization-weighted indexes for capturing the value premium. Any analysis of the stock market today must be international in scope, and in this edition I have greatly expanded the material on international markets.

More Money Than God: Hedge Funds and the Making of a New Elite
by Sebastian Mallaby
Published 9 Jun 2010

If markets were inefficient, there was money to be made, and the finance professors saw no reason why they should not be the ones to profit. Cliff Asness was fairly typical of the new wave. At the University of Chicago’s Graduate School of Business, his thesis adviser was Eugene Fama, one of the fathers of the efficient-market hypothesis. But by 1988, when Asness arrived in Chicago, Fama was leading the revisionist charge: Along with a younger colleague, Kenneth French, Fama discovered non-random patterns in markets that could be lucrative for traders. After contributing to this literature, Asness headed off to Wall Street and soon opened his hedge fund.

…

The recasting of the academic consensus had three parts to it. The efficient-market hypothesis had always been based on a precarious assumption: that price changes conformed to a “normal” probability distribution—the one represented by the familiar bell curve, in which numbers at and near the median crop up frequently while numbers in the tails of the distribution are rare to the point of vanishing. Even in the early 1960s, a maverick mathematician named Benoit Mandelbrot argued that the tails of the distribution might be fatter than the normal bell curve assumed; and Eugene Fama, the father of efficient-market theory, who got to know Mandelbrot at the time, conducted tests on stock-price changes that confirmed Mandelbrot’s assertion.

…

The crash of 1987 underlined these doubts: When the market’s valuation of corporate America changed by a fifth in a single trading day, it was hard to believe that the valuation deserved much deference. “If the efficient markets hypothesis was a publicly traded security, its price would be enormously volatile,” the Harvard economists Andrei Shleifer and Lawrence Summers wrote mockingly in 1990. “But the stock in the efficient markets hypothesis—at least as it has traditionally been formulated—crashed along with the rest of the market on October 19, 1987.”8 The acknowledgment of the limits to market efficiency had a profound effect on hedge funds.

Stocks for the Long Run 5/E: the Definitive Guide to Financial Market Returns & Long-Term Investment Strategies
by Jeremy Siegel
Published 7 Jan 2014

Risk that is not correlated to the market can be eliminated through diversification (called diversifiable or residual risk) and does not warrant a higher return. The efficient market hypothesis and the CAPM became the basis for stock return analysis in the 1970s and 1980s. Unfortunately, as more data were analyzed, beta did not prove effective in explaining the differences in returns among individual stocks. In fact, the beta of Standard Oil of New Jersey was far lower than the beta of IBM, although Standard Oil’s return was greater.4 In 1992, Eugene Fama and Ken French wrote an article, published in the Journal of Finance, that showed that there are two factors, one relating to the market capitalization of the firm and the other to the valuation of stocks, that are far more important in determining a stock’s return than the beta of a stock.5 After further analyzing returns, they claimed that the evidence against the CAPM was “compelling” and that “the average return anomalies . . . are serious enough to infer that the [CAPM] model is not a useful approximation” of a stock’s return, and they suggested researchers investigate “alternative” asset pricing models or “irrational asset pricing stories.”6 Fama and French’s findings prompted financial economists to classify the stock universe along two dimensions: size, measured by the market value of the stock, and valuation, or the price relative to “fundamentals” such as earnings and dividends.

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See William Sharpe, “Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk,” Journal of Finance, vol. 19, no. 3 (September 1964), p. 442, and John Lintner, “The Valuation of Risk Assets and the Selection of Risky Investment in Stock Portfolios and Capital Budgets,” Review of Economics and Statistics, vol. 47, no. 1 (1965), pp. 221-245. 4. From 1980 the beta of Exxon-Mobil was 0.60 versus 0.93 for IBM. 5. Eugene Fama and Ken French, “The Cross Section of Expected Stock Returns,” Journal of Finance, vol. 47 (1992), pp. 427-466. 6. Eugene Fama and Ken French, “The CAPM Is Wanted, Dead or Alive,” Journal of Finance, vol. 51, no. 5 (December 1996), pp. 1947-1958. 7. Benjamin Graham and David Dodd, Security Analysis, New York: McGraw Hill, 1934. 8. Rolf Banz, “The Relationship Between Return and Market Value of Common Stock,” Journal of Financial Economics, vol. 9 (1981), pp. 3-18. 9.

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Their transactions may be motivated by taxes, fiduciary responsibilities, rebalancing of their portfolio, or other personal reasons. In order to explain the value and size effects we see in the historical data, another assumption needs to be added: that price movements caused by these liquidity traders are not immediately reversed by those trading on fundamental information. This assumption is a deviation from the efficient market hypothesis that claims that at all times the price of a security is the best unbiased estimate of the underlying value of the enterprise. I have called the alternative assumption the “noisy market hypothesis” because the buying and selling by noise or liquidity traders often obscure the fundamental value of the firm.29 The noisy market hypothesis can provide an explanation for the size and value effects.30 A positive liquidity shock raises the price of the stock above its fundamental value and makes that stock more likely to be classified as a “large” or “growth” stock.

Capitalism 4.0: The Birth of a New Economy in the Aftermath of Crisis
by Anatole Kaletsky
Published 22 Jun 2010

See Frank Knight, Risk, Uncertainty, and Profit. 9 David Ricardo, “Essay on the Funding System,” in The Works of David Ricardo , 513-548. 10 David Viniar quoted in Emiko Terazono, “Bean in Barcelona,” Financial Times, August 26, 2009. 11 When asked by John Cassidy of the New Yorker how the theory of efficient markets had held up in the crisis, Chicago economist Eugene Fama responded, “I think it did quite well in this episode. . . . [This] was exactly what you would expect if markets are efficient.” He went on to suggest, “I don’t know what a credit bubble means. . . . I don’t even know what a bubble means. These words have become popular. I don’t think they have any meaning.” Eugene Fama quoted in John Cassidy, “After the Blowup: Laissez-faire Economists Do Some Soul-searching—and Finger-pointing,” New Yorker ( January 11, 2010): 30. 12 The Joint Hypothesis problem arises because any test of market efficiency is actually a simultaneous test of two hypotheses: One, that markets are efficient, and two, that our models of the market are accurate.

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The Normal distribution is a wonderful mathematical construct because it can be analyzed with extraordinary precision. The assumptions made by the Efficient Market Hypothesis thus allowed very precise formulas to be developed for pricing options and complex financial instruments of all kinds. And these formulas, because of their mathematical precision, appeared to justify the enormous increases in leverage and reliance on risk-management systems that so spectacularly failed. In this sense, the 2007-09 crisis could fairly be described as a failure of mathematical economics and nothing more. If the Efficient Market Hypothesis had been valid, fairly simple and logically irrefutable mathematical calculations could have been used to show that most of the financial crises of the past twenty years were literally impossible.

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By normal intellectual standards, such spectacular empirical falsification would have completely demolished the Efficient Market Hypothesis as a serious scientific theory. But as in the case of rational expectations, most economists in the wake of the crisis have been so attached to their theories that the facts had to be rejected instead.11 The financial establishment, too, was quick to regroup in defense of EMH, since its abandonment would mean the collapse of some extremely profitable, though very risky, business models. Without the Efficient Market Hypothesis, most of the trading and risk models used by major financial institutions would have to be junked.

Work Less, Live More: The Way to Semi-Retirement
by Robert Clyatt
Published 28 Sep 2007

See Appendix B for details on how to access these and other studies: chapter 3 | Put Your Investing on Autopilot | 187 • “The Efficient Market Hypothesis,” by Eugene Fama and Burton Malkiel, holds that although prices in the market may certainly be inefficient— that is, too high or too low—they are mispriced randomly, and there is no method to make use of this information to consistently beat the market • “Modern Portfolio Theory,” by Harry Markowitz and Merton Miller, proves how investing across less-correlated asset classes can produce a portfolio with lower risk for a given return, and • “The 3-Factor Model,” by Eugene Fama and Kenneth French, identifies and explains the premiums paid to holders of small and value stocks, with subsequent studies showing how these premiums persist through time and across multiple markets.

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Stocks, Value Tilt Large U.S. Stocks make up a big proportion of the world’s stock markets and should be well-represented in your portfolio. By favoring value stocks, you put historical returns on your side, as these shares have tended to outperform the average large stock over time. This was first shown by Eugene Fama of the University of Chicago and DFA and Kenneth French, now at Dartmouth, in their widely cited Three-Factor Model documenting the persistence of premiums for owning high book-to-market or value stocks. Over the years, this disquieting theory that provides a sound theoretical rationale for bad companies’ stocks outperforming good companies’ stocks has withstood sustained assault and, with minor modifications, still stands.

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Thus, if you hold TIPS outside a Roth IRA, you will owe taxes on the inflation adjustment either annually for taxable accounts, or whenever you withdraw from a traditional IRA. TIPS funds, however, do not have this problem, as the inflationadjustment component is added to the interest payment and distributed as a dividend. Medium-Term U.S. Bonds Financial researchers Eugene Fama and David Plecha have shown that the slightly higher yield from Long Maturity Bonds is not fair compensation for their much higher volatility and risk when interest rates change. Also, Medium-Term Bonds are less correlated with equities than longer-term bonds. By sticking with a blend of 2-Year and 5-Year Average Maturity Bonds, you can capture the bulk of the yield while still ensuring reasonable protection from rising interest rates.

Investment: A History
by Norton Reamer and Jesse Downing
Published 19 Feb 2016

Jensen’s initial study of mutual funds from 1945 to 1964 revealed that very few managers had effectively produced a greater return than one would expect, given the level of risk of the portfolio.40 Investors finally had a mechanism by which they could parse out the riskadjusted effects of active money management. Samuelson and Fama: Formalizations of the Efficient Market Hypothesis The question of whether managers can successfully add alpha remains a consistent and contentious debate in the academic literature. There are many who believe managers cannot consistently add value over the long term because markets are efficient. One of the theorists behind this “efficient market hypothesis” was Eugene Fama, discussed previously in the context of his three-factor model with French. In his 1970 paper entitled “Efficient Capital Markets: A Review of Theory and Empirical Work,” Fama effectively defined three different types of efficiency.

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Last is strong-form efficiency, which implies that all information, both public and private, is reflected in stock prices.41 (Of course, a multitude of legal constraints exist in most regulatory environments to prevent the purest incarnation of strong-form efficiency, particularly laws prohibiting insider trading. Indeed, it is the divergence of the market from strong-form efficiency that makes insider trading profitable.) The critical implication of the efficient market hypothesis is that the market cannot be beaten if it is truly efficient. 250 Investment: A History To understand the efficient market hypothesis more completely, it is worth discussing perhaps one of its staunchest opponents: the school of value investing, which began with Benjamin Graham and David Dodd’s publication of the famed book Security Analysis in 1934.

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He went on to say that he agreed instead with those who believed the market had almost always priced securities correctly: “To that very limited extent I’m on the side of the ‘efficient market’ school of thought now generally accepted by the professors.”44 While Benjamin Graham may have given up on his work, many adherents of the philosophy of value investing have not. One may consider Warren Buffett’s primary objection to the efficient market hypothesis to illustrate this point: value investors, he claims, seem to have outperformed the market over time. The response of most proponents of the efficient market hypothesis has been that given the The Emergence of Investment Theory 251 number of money managers in the market, statistically some will seem to outperform the market. Buffett’s response in a 1984 speech to the Columbia Business School was to discuss the records of nine investors he had known since fairly early in his career who did value investing and who he said had consistently outperformed the market on a riskadjusted basis.

Adaptive Markets: Financial Evolution at the Speed of Thought
by Andrew W. Lo
Published 3 Apr 2017

Because of studies like this, FFJR’s coauthor Michael Jensen boasted in 1978 that “there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.”29 Fama has become one of the most influential financial economists of his generation through his work on the Efficient Markets Hypothesis. The free market Chicago School of economics is usually associated with its most eloquent champion, Milton Friedman, but the Efficient Markets Hypothesis has become at least as prominent a hallmark, thanks to Gene Fama. EFFICIENT MARKETS UNPACKED Two economists with very dissimilar styles of thought, Paul Samuelson and Eugene Fama, reached the same conclusion about efficient markets.

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If prices already reflected all available information, what was the point of hiring an industry analyst or a fund manager? No wonder Wall Street was so slow to embrace modern financial economics. Over the years, Eugene Fama and his disciples unleashed a flood of Ph.D. theses, journal articles, and test after empirical test of efficiency that seemed to support the Efficient Markets Hypothesis, in all of its three forms.27 In academia, a paper’s importance is often judged by how many times other researchers cite it. One of Fama’s most highly cited publications was coauthored with Larry Fisher, Michael Jensen, and Richard Roll in 1969, and is often referred to as the FFJR paper.28 FFJR’s simple but brilliant analysis captivated the academic finance community, but it appalled Wall Street professionals, for reasons that are worth describing in some detail.

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It was known as “political economy,” and it was studied largely by philosophers and theologians, not mathematicians. But a sharp break from this tradition occurred in 1947, thanks to none other than Paul Samuelson, the single most important economist of the twentieth century. As we saw in chapter 1, Samuelson played a critical role in formulating the Efficient Markets Hypothesis, even before Eugene Fama’s important contribution. However, decades before he began thinking about finance, Samuelson played an even more significant role in changing the way economists plied their trade—as a mere graduate student. Samuelson changed the course of economics, and in the process he gave everyone in the field a case of physics envy, for better or worse.

Frequently Asked Questions in Quantitative Finance
by Paul Wilmott
Published 3 Jan 2007

References and Further Reading Wilmott, P 2006 Paul Wilmott On Quantitative Finance, second edition. John Wiley & Sons What is the Efficient Markets Hypothesis? Short Answer An efficient market is one where it is impossible to beat the market because all information about securities is already reflected in their prices. Example Or rather a counter-example, “I’d be a bum in the street with a tin cup if the markets were efficient,” Warren Buffett. Long Answer The concept of market efficiency was proposed by Eugene Fama in the 1960s. Prior to that it had been assumed that excess returns could be made by careful choice of investments.

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The work later won Markowitz a Nobel Prize for Economics but is rarely used in practice because of the difficulty in measuring the parameters volatility, and especially correlation, and their instability. 1963 Sharpe, Lintner and Mossin William Sharpe of Stanford, John Lintner of Harvard and Norwegian economist Jan Mossin independently developed a simple model for pricing risky assets. This Capital Asset Pricing Model (CAPM) also reduced the number of parameters needed for portfolio selection from those needed by Markowitz’s Modern Portfolio Theory, making asset allocation theory more practical. See Sharpe (1963), Lintner (1963) and Mossin (1963). 1966 Fama Eugene Fama concluded that stock prices were unpredictable and coined the phrase “market efficiency.” Although there are various forms of market efficiency, in a nutshell the idea is that stock market prices reflect all publicly available information, that no person can gain an edge over another by fair means.

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References and Further Reading What is Cointegration? References and Further Reading What is the Kelly criterion? References and Further Reading Why Hedge? References and Further Reading What is Marking to Market and How Does it Affect Risk Management in Derivatives Trading? References and Further Reading What is the Efficient Markets Hypothesis? References and Further Reading What are the Most Useful Performance Measures? References and Further Reading What is a Utility Function and How is it Used? References and Further Reading What is Brownian Motion and What are its Uses in Finance? References and Further Reading What is Jensen’s Inequality and What is its Role in Finance?

The Misbehavior of Markets: A Fractal View of Financial Turbulence
by Benoit Mandelbrot and Richard L. Hudson
Published 7 Mar 2006

And now comes the increasingly accepted but still confusing evidence of long-term dependence. Some economists, when thinking about long memory, are concerned that it undercuts the Efficient Market Hypothesis that prices fully reflect all relevant information; that the random walk is the best metaphor to describe such markets; and that you cannot beat such an unpredictable market. Well, the Efficient Market Hypothesis is no more than that, a hypothesis. Many a grand theory has died under the onslaught of real data. Coda: Looney ’Toons of Long Dependence As an aid to understanding, it is cartoon time again.

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The paper, one of the most widely read and cited in economics, sparked others to look at the price data with fresh eyes. Because of its import, I will come back to this tale. Stocks The inquiry quickly broadened beyond cotton. Whatever the stock index, whatever the country, whatever the security, prices only rarely follow the predicted normal pattern. My student, Eugene Fama, investigated this for his doctoral thesis. Rather than examine a broad market index, he looked one-by-one at the thirty blue-chip stocks in the Dow. He found the same, disturbing pattern: Big price changes were far more common than the standard model allowed. Large changes, of more than five standard deviations from the average, happened two thousand times more often than expected.

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Because expressing a number in logarithms rescales it so that, rather than focusing on the size of the number as we normally do, we can more easily compare it to other numbers nearby. Thus, $1 price jumps from $10 to $11and from $1,000 to $1,001 are equal on the dollars scale but the logarithmic scale shows the former to be more important than the latter. 95 “When Cootner of MIT…” Cootner 1964. 96 “My student, Eugene Fama…” Fama 1964, revised and published as Fama 1965b. 96 “They call it kurtosis…” Kurtosis is one of the founders of the standard measures of a distribution curve’s shape, which are based on the first four “moments.” The first moment is the average value; the second is the variance; third is the skewness—a measure of how asymmetrically the data are distributed around the average; and fourth is kurtosis, a measure of how tall or squat the curve is.

The Physics of Wall Street: A Brief History of Predicting the Unpredictable
by James Owen Weatherall
Published 2 Jan 2013

It’s a necessary part of what makes markets run. This way of looking at markets is now known as the efficient market hypothesis. The basic idea is that market prices always reflect the true value of the thing being traded, because they incorporate all available information. Bachelier was the first to suggest it, but, as was true of many of his deepest insights into financial markets, few of his readers noted its importance. The efficient market hypothesis was later rediscovered, to great fanfare, by University of Chicago economist Eugene Fama, in 1965. Nowadays, of course, the hypothesis is highly controversial. Some economists, particularly members of the so-called Chicago School, cling to it as an essential and irrefutable truth.

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For more on these other pioneers in finance, see Poitras (2006) (especially Jovanovic [2006] and Zimmermann and Hafner [2006]) and Girlich (2002). “The efficient market hypothesis was later rediscovered . . .”: See Fama (1965). The efficient market hypothesis is now a central part of modern economic thought; it is described in detail in any major textbook, such as Mankiw (2012) or Krugman and Wells (2009). For a history of the efficient market hypothesis, see Sewell (2011) and Lim (2006). See also the dozens of recent books and articles attacking the idea that markets are in fact efficient, such as Taleb (2004, 2007a), Fox (2009), Cassidy (2010a, b), Stiglitz (2010), and Krugman (2009)

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Despite the early setbacks, however, Black and Scholes were not destined to labor in obscurity. Powerful forces in academia, in finance, and in politics were aligning in their favor. And some of the then-reigning academic gods were ready to intervene. After the second rejection, University of Chicago professors Eugene Fama and Merton Miller, two of the most influential economists at the time and leaders of the then-nascent Chicago School of economics, successfully urged the Journal of Political Economy to reconsider, and in August 1971 the article was accepted for publication, pending revisions. In the meantime, Fischer Black had attracted attention at the University of Chicago.

Traders, Guns & Money: Knowns and Unknowns in the Dazzling World of Derivatives
by Satyajit Das
Published 15 Nov 2006

Nuclear physicists of a different era had asked: ‘What is Copenhagen’s view of this?’ In the 1970s, financial economists around the globe wondered: ‘What is Chicago’s view of this?’ DAS_C02.QXP 8/7/06 22 4:22 PM Page 22 Tr a d e r s , G u n s & M o n e y In Chicago, Eugene Fama and his colleagues developed the efficient markets hypothesis. Merton Miller developed theories on dividends, borrowing by companies and the effect of taxes. Against this background of febrile activity, in 1973, three academics – Fischer Black, Myron Scholes and Robert Merton – developed a model to price options. Scholes and Merton were to receive the Swedish Central Bank’s Prize for achievement in economics (often mistakenly referred to as the Nobel Prize).

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Warren Buffet continues to defy this DAS_C04.QXP 8/7/06 8:39 PM Page 111 3 N Tr u e l i e s – t h e ‘ b u y ’ s i d e 111 successfully. He argues that you are better off putting your money into a few things you know and understand, and that are cheap. He doesn’t like the thought of buying all the stuff you know nothing about. 2 Efficient markets – Eugene Fama and his colleagues hypothesized that prices follow a random walk. Prices do not follow specific discernible patterns, at least from past prices. All known information is already built into the price. Dealers and investors exist to exploit market inefficiency. If markets are truly efficient, then where is the boodle coming from?

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Black believed that the the paper was rejected because he was not an academic – he had been a consultant at Arthur D. Little, a Boston consulting firm. Throughout his life, he remained deeply sceptical and cautious about scholarly life. Eventually, after the intervention of noted academics such as Merton Miller and Eugene Fama, Black and Scholes’ model was eventually published in 1973 as ‘The Pricing of Options and Corporate Liabilities’.4 Merton published a separate paper entitled ‘The Theory of Rational Option Pricing’5 shortly afterwards. The Black and Scholes option pricing model is the following equation: Pce = S.

The Signal and the Noise: Why So Many Predictions Fail-But Some Don't
by Nate Silver
Published 31 Aug 2012

Thaler, although a friend and colleague of Fama’s, has been at the forefront of a discipline called behavioral economics that has been a thorn in the side of efficient-market hypothesis. Behavioral economics points out all the ways in which traders in the real-world are not as well-behaved as in the model. “Efficient-market hypothesis has two components,” Thaler told me between bites of toro. “One I call the No Free Lunch component, which is that you can’t beat the market. Eugene Fama and I mostly agree about this component. The part he doesn’t like to talk about is the Price Is Right component.” There is reasonably strong evidence for what Thaler calls No Free Lunch—it is difficult (although not literally impossible) for any investor to beat the market over the long-term.

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I’d think it would be difficult. Can they do so right now? My educated guess21 is that some of us still can, if we select our bets carefully.22 Then again, a lot of smart people have failed miserably when they thought they could beat the market. The Origin of Efficient-Market Hypothesis In 1959, a twenty-year-old college student named Eugene Fama, bored with the Tufts University curriculum of romance languages and Voltaire, took a job working for a professor who ran a stock market forecasting service.23 The job was a natural fit for him; Fama was a fierce competitor who had been the first in his family to go to college and who had been a star athlete at Boston’s Malden Catholic High School despite standing at just five feet eight.

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FIGURE 11-4: RANDOM-WALK AND ACTUAL STOCK-MARKET CHARTS Three Forms of Efficient-Market Hypothesis After looking at enough of this type of data, Fama refined his hypothesis to cover three distinct cases,31 each one making a progressively bolder claim about the predictability of markets. First, there is the weak form of efficient-market hypothesis. What this claims is that stock-market prices cannot be predicted from analyzing past statistical patterns alone. In other words, the chartist’s techniques are bound to fail. The semistrong form of efficient-market hypothesis takes things a step further. It argues that fundamental analysis—meaning, actually looking at publicly available information on a company’s financial statements, its business model, macroeconomic conditions and so forth—is also bound to fail and will also not produce returns that consistently beat the market.

13 Bankers: The Wall Street Takeover and the Next Financial Meltdown
by Simon Johnson and James Kwak
Published 29 Mar 2010

But it was perhaps even more important for the ideology it created. A central assertion of the academic finance movement in the 1960s and 1970s became known as the Efficient Market Hypothesis: precisely because traders are looking for and exploiting inefficiencies in asset prices, those inefficiencies cannot last for more than a brief period of time; as a result, prices are always “right.” As outlined by Eugene Fama in 1970, the Efficient Market Hypothesis comes in a weak form, a semi-strong form, and a strong form. The weak form holds that future prices cannot be predicted from past prices; the semi-strong form holds that prices adjust quickly to all publicly available information (meaning that by the time you read the news in the newspaper, it is too late to make money on the news); and the strong form holds that no one has any information that can be used to predict future prices, so market prices are always right.

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At the time, a movement was growing in the halls of America’s leading universities that would help transform the financial sector. This movement was the discipline of academic finance, pioneered by economists such as Paul Samuelson, Franco Modigliani, Merton Miller, Harry Markowitz, William Sharpe, Eugene Fama, Fischer Black, Robert Merton, and Myron Scholes, most of whom went on to win the Nobel Prize. These scholars brought sophisticated mathematics to bear on such problems as determining the optimal capital structure of a firm (the ratio between debt and equity), pricing financial assets, and separating and hedging risks.40 Academic finance had a tremendous impact on the way business is done around the globe.

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(Or, as Goldman Sachs CEO Lloyd Blankfein recently asserted in defense of his bankers’ high pay, “If you examine our practices on compensation, you will see a complete correlation throughout our history of having remuneration match performance over the long term.”)43 These were not mathematical consequences of the Efficient Market Hypothesis, but they flowed naturally from it. The basic belief was that if a financial transaction was taking place, it was a good thing. This belief reflects a general economic principle; given perfectly rational actors with perfect information and no externalities, all transactions should be beneficial for both parties.

A Random Walk Down Wall Street: The Time-Tested Strategy for Successful Investing (Eleventh Edition)
by Burton G. Malkiel
Published 5 Jan 2015

THE SEMI-STRONG AND STRONG FORMS OF THE EFFICIENT-MARKET HYPOTHESIS (EMH) The academic community has rendered its judgment. Fundamental analysis is no better than technical analysis in enabling investors to capture above-average returns. Nevertheless, given its propensity for splitting hairs, the academic community soon fell to quarreling over the precise definition of fundamental information. Some said it was what is known now; others said it extended to the hereafter. It was at this point that what began as the strong form of the efficient-market hypothesis split into two. The “semi-strong” form says that no public information will help the analyst select undervalued securities.

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Did the stock market reflect all available information in March 2008, and could anyone reasonably argue that stocks were efficiently priced? For many observers, the collapse of 2008–09 and the subsequent world financial crisis sounded the death knell for the efficient-market hypothesis. In 2009, George Soros wrote that “the Efficient Market Hypothesis has been truly discredited by the crash of 2008.” The EMH was blamed as the villain in the financial crisis and was written off for dead by countless financial commentators. For example, the respected market strategist Jeremy Grantham opined that the EMH “is more or less directly responsible for the financial crisis.”

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Is it true that high-beta portfolios will provide larger long-term returns than lower-beta ones, as the capital-asset pricing model suggests? Does beta alone summarize a security’s total systematic risk, or do we need to consider other factors as well? In short, does beta really deserve an alpha? These are subjects of intense current debate among practitioners and academics. In a study published in 1992, Eugene Fama and Kenneth French divided all traded stocks into deciles according to their beta measures over the 1963–90 period. Decile 1 contained the 10 percent of all stocks that had the lowest betas; decile 10 contained the 10 percent that had the highest betas. The remarkable result, shown in the chart below, is that there was essentially no relationship between the return of these decile portfolios and their beta measures.

The Economics Anti-Textbook: A Critical Thinker's Guide to Microeconomics
by Rod Hill and Anthony Myatt
Published 15 Mar 2010

Perhaps unsurprisingly there is a long-held view that asset markets are effi­ cient, because they are competitive markets where information is conveyed very rapidly. This ‘efficient market hypothesis’ was developed by Eugene Fama (1965), and was the dominant view until the 1990s. It is still very influential today.10 i The efficient market hypothesis (EMH) In theory, the real value of any asset is determined by its discounted stream 145 6  |  Market structure and efficiency Suggestions for further reading of future earnings. So if you are trying to determine the real value of IBM stock, you should look at its fundamentals – the underlying determinants of the company’s future profits.11 According to the efficient market hypothesis, if you do this accurately enough using all currently available information, your calculated fundamental value will equal the actual price at which IBM stock is already selling in the market.

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The polite one is ‘data mining’ and, according to an article by Denton (1985), it’s a pretty prolific industry. 7 William Broad and Nicholas Wade, in Betrayers of the Truth (1983), present examples where the inability of other researchers to replicate published scientific findings revealed both inadvertent errors and outright fraud. On the other hand, Dewald et al. found that the errors did not significantly affect the conclusions in the majority of cases. 8 Another example would be whether asset markets are efficient. There has been a long-running battle between Eugene Fama and his associates in support of the efficient market hypothesis, and Andrei Shleifer, Richard Thaler and others in support of the inefficient market hypothesis. 9 Donald McCloskey and Deirdre McCloskey are the same person, the transition occurring (from Donald to Deirdre) in 1995. 10 A good Internet source is the History of Economic Thought website developed through the New School of Economic Research.

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The best mutual fund this year will prove to be randomly located in the pack of mutual funds next year. ii The efficient market hypothesis and the behavioural economists Markets can be efficient only if market participants are rational calculating machines that do not make systematic mistakes. But as discussed in Chapter 1 (Section 2.6), behavioural economists have shown, at least in laboratory conditions, that we do make systematic mistakes. Of course, you can fool some of the people all of the time. Believers in the efficient market hypothesis would counter that evidence of systematic mistakes by some does not show that the 146 1600 S&P 500 index value 1400 1200 1000 800 The 1987 crash 600 400 200 2009 2007 2005 2003 2001 1999 1997 1995 1993 1991 1989 1987 1985 1983 1981 0 figure 6.11 Aggregate stock price bubbles market as a whole is inefficient.

Doughnut Economics: Seven Ways to Think Like a 21st-Century Economist
by Kate Raworth
Published 22 Mar 2017

There is no need to look at what goes on in their factories and farms, so long as they play within the legal rules of the game. FINANCE, which is infallible – so trust in its ways. Banks take people’s savings and dutifully turn them into profitable investments. Furthermore, according to Eugene Fama’s influential ‘efficient-market hypothesis’ of 1970, the price of financial assets always fully reflects all relevant information.9 Hence financial markets are ever adjusting but always ‘right’ – and their smooth operation should not be distorted by regulation. TRADE, which is win–win – so open your borders. David Ricardo’s nineteenth-century theory of comparative advantage demonstrates that countries should focus on what they are relatively good at doing and then trade: if they do, both parties will gain from it, no matter how unequal they are.10 Hence trade barriers should be dismantled because they only distort the efficient workings of the international market.

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Thanks to financial deregulation, said US Federal Reserve Chair Alan Greenspan in 2004, ‘not only have individual financial institutions become less vulnerable to shocks from underlying risk factors, but also the financial system as a whole has become more resilient.’45 Four years later, the financial crash disproved that claim in a fairly decisive way. At the same time, Eugene Fama’s efficient-market hypothesis – that financial markets are inherently efficient – lost credibility and has been countered by Hyman Minsky’s financial-instability hypothesis – that financial markets are inherently volatile – as we will see in Chapter 4. Lastly, far from playing a supporting role to the productive economy, finance has come to dominate it.

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Page numbers in italics denote illustrations A Aalborg, Denmark, 290 Abbott, Anthony ‘Tony’, 31 ABCD group, 148 Abramovitz, Moses, 262 absolute decoupling, 260–61 Acemoglu, Daron, 86 advertising, 58, 106–7, 112, 281 Agbodjinou, Sénamé, 231 agriculture, 5, 46, 72–3, 148, 155, 178, 181, 183 Alaska, 9 Alaska Permanent Fund, 194 Alperovitz, Gar, 177 alternative enterprise designs, 190–91 altruism, 100, 104 Amazon, 192, 196, 276 Amazon rainforest, 105–6, 253 American Economic Association, 3 American Enterprise Institute, 67 American Tobacco Corporation, 107 Andes, 54 animal spirits, 110 Anthropocene epoch, 48, 253 anthropocentrism, 115 Apertuso, 230 Apple, 85, 192 Archer Daniels Midland (ADM), 148 Arendt, Hannah, 115–16 Argentina, 55, 274 Aristotle, 32, 272 Arrow, Kenneth, 134 Articles of Association and Memoranda, 233 Arusha, Tanzania, 202 Asia Wage Floor Alliance, 177 Asian financial crisis (1997), 90 Asknature.org, 232 Athens, 57 austerity, 163 Australia, 31, 103, 177, 180, 211, 224–6, 255, 260 Austria, 263, 274 availability bias, 112 AXIOM, 230 Axtell, Robert, 150 Ayres, Robert, 263 B B Corp, 241 Babylon, 13 Baker, Josephine, 157 balancing feedback loops, 138–41, 155, 271 Ballmer, Steve, 231 Bangla Pesa, 185–6, 293 Bangladesh, 10, 226 Bank for International Settlements, 256 Bank of America, 149 Bank of England, 145, 147, 256 banking, see under finance Barnes, Peter, 201 Barroso, José Manuel, 41 Bartlett, Albert Allen ‘Al’, 247 basic income, 177, 194, 199–201 basic personal values, 107–9 Basle, Switzerland, 80 Bauwens, Michel, 197 Beckerman, Wilfred, 258 Beckham, David, 171 Beech-Nut Packing Company, 107 behavioural economics, 11, 111–14 behavioural psychology, 103, 128 Beinhocker, Eric, 158 Belgium, 236, 252 Bentham, Jeremy, 98 Benyus, Janine, 116, 218, 223–4, 227, 232, 237, 241 Berger, John, 12, 281 Berlin Wall, 141 Bermuda, 277 Bernanke, Ben, 146 Bernays, Edward, 107, 112, 281–3 Bhopal gas disaster (1984), 9 Bible, 19, 114, 151 Big Bang (1986), 87 billionaires, 171, 200, 289 biodiversity, 10, 46, 48–9, 52, 85, 115, 155, 208, 210, 242, 299 as common pool resource, 201 and land conversion, 49 and inequality, 172 and reforesting, 50 biomass, 73, 118, 210, 212, 221 biomimicry, 116, 218, 227, 229 bioplastic, 224, 293 Birmingham, West Midlands, 10 Black, Fischer, 100–101 Blair, Anthony ‘Tony’, 171 Blockchain, 187, 192 blood donation, 104, 118 Body Shop, The, 232–4 Bogotá, Colombia, 119 Bolivia, 54 Boston, Massachusetts, 3 Bowen, Alex, 261 Bowles, Sam, 104 Box, George, 22 Boyce, James, 209 Brasselberg, Jacob, 187 Brazil, 124, 226, 281, 290 bread riots, 89 Brisbane, Australia, 31 Brown, Gordon, 146 Brynjolfsson, Erik, 193, 194, 258 Buddhism, 54 buen vivir, 54 Bullitt Center, Seattle, 217 Bunge, 148 Burkina Faso, 89 Burmark, Lynell, 13 business, 36, 43, 68, 88–9 automation, 191–5, 237, 258, 278 boom and bust, 246 and circular economy, 212, 215–19, 220, 224, 227–30, 232–4, 292 and complementary currencies, 184–5, 292 and core economy, 80 and creative destruction, 142 and feedback loops, 148 and finance, 183, 184 and green growth, 261, 265, 269 and households, 63, 68 living metrics, 241 and market, 68, 88 micro-businesses, 9 and neoliberalism, 67, 87 ownership, 190–91 and political funding, 91–2, 171–2 and taxation, 23, 276–7 workers’ rights, 88, 91, 269 butterfly economy, 220–42 C C–ROADS (Climate Rapid Overview and Decision Support), 153 C40 network, 280 calculating man, 98 California, United States, 213, 224, 293 Cambodia, 254 Cameron, David, 41 Canada, 196, 255, 260, 281, 282 cancer, 124, 159, 196 Capital Institute, 236 carbon emissions, 49–50, 59, 75 and decoupling, 260, 266 and forests, 50, 52 and inequality, 58 reduction of, 184, 201, 213, 216–18, 223–7, 239–41, 260, 266 stock–flow dynamics, 152–4 taxation, 201, 213 Cargill, 148 Carney, Mark, 256 Caterpillar, 228 Catholic Church, 15, 19 Cato Institute, 67 Celts, 54 central banks, 6, 87, 145, 146, 147, 183, 184, 256 Chang, Ha-Joon, 82, 86, 90 Chaplin, Charlie, 157 Chiapas, Mexico, 121–2 Chicago Board Options Exchange (CBOE), 100–101 Chicago School, 34, 99 Chile, 7, 42 China, 1, 7, 48, 154, 289–90 automation, 193 billionaires, 200, 289 greenhouse gas emissions, 153 inequality, 164 Lake Erhai doughnut analysis, 56 open-source design, 196 poverty reduction, 151, 198 renewable energy, 239 tiered pricing, 213 Chinese Development Bank, 239 chrematistics, 32, 273 Christianity, 15, 19, 114, 151 cigarettes, 107, 124 circular economy, 220–42, 257 Circular Flow diagram, 19–20, 28, 62–7, 64, 70, 78, 87, 91, 92, 93, 262 Citigroup, 149 Citizen Reaction Study, 102 civil rights movement, 77 Cleveland, Ohio, 190 climate change, 1, 3, 5, 29, 41, 45–53, 63, 74, 75–6, 91, 141, 144, 201 circular economy, 239, 241–2 dynamics of, 152–5 and G20, 31 and GDP growth, 255, 256, 260, 280 and heuristics, 114 and human rights, 10 and values, 126 climate positive cities, 239 closed systems, 74 coffee, 221 cognitive bias, 112–14 Colander, David, 137 Colombia, 119 common-pool resources, 82–3, 181, 201–2 commons, 69, 82–4, 287 collaborative, 78, 83, 191, 195, 196, 264, 292 cultural, 83 digital, 82, 83, 192, 197, 281 and distribution, 164, 180, 181–2, 205, 267 Embedded Economy, 71, 73, 77–8, 82–4, 85, 92 knowledge, 197, 201–2, 204, 229, 231, 292 commons and money creation, see complementary currencies natural, 82, 83, 180, 181–2, 201, 265 and regeneration, 229, 242, 267, 292 and state, 85, 93, 197, 237 and systems, 160 tragedy of, 28, 62, 69, 82, 181 triumph of, 83 and values, 106, 108 Commons Trusts, 201 complementary currencies, 158, 182–8, 236, 292 complex systems, 28, 129–62 complexity science, 136–7 Consumer Reaction Study, 102 consumerism, 58, 102, 121, 280–84 cooking, 45, 80, 186 Coote, Anna, 278 Copenhagen, Denmark, 124 Copernicus, Nicolaus, 14–15 copyright, 195, 197, 204 core economy, 79–80 Corporate To Do List, 215–19 Costa Rica, 172 Council of Economic Advisers, US, 6, 37 Cox, Jo, 117 cradle to cradle, 224 creative destruction, 142 Cree, 282 Crompton, Tom, 125–6 cross-border flows, 89–90 crowdsourcing, 204 cuckoos, 32, 35, 36, 38, 40, 54, 60, 159, 244, 256, 271 currencies, 182–8, 236, 274, 292 D da Vinci, Leonardo, 13, 94–5 Dallas, Texas, 120 Daly, Herman, 74, 143, 271 Danish Nudging Network, 124 Darwin, Charles, 14 Debreu, Gerard, 134 debt, 37, 146–7, 172–3, 182–5, 247, 255, 269 decoupling, 193, 210, 258–62, 273 defeat device software, 216 deforestation, 49–50, 74, 208, 210 degenerative linear economy, 211–19, 222–3, 237 degrowth, 244 DeMartino, George, 161 democracy, 77, 171–2, 258 demurrage, 274 Denmark, 180, 275, 290 deregulation, 82, 87, 269 derivatives, 100–101, 149 Devas, Charles Stanton, 97 Dey, Suchitra, 178 Diamond, Jared, 154 diarrhoea, 5 differential calculus, 131, 132 digital revolution, 191–2, 264 diversify–select–amplify, 158 double spiral, 54 Doughnut model, 10–11, 11, 23–5, 44, 51 and aspiration, 58–9, 280–84 big picture, 28, 42, 61–93 distribution, 29, 52, 57, 58, 76, 93, 158, 163–205 ecological ceiling, 10, 11, 44, 45, 46, 49, 51, 218, 254, 295, 298 goal, 25–8, 31–60 and governance, 57, 59 growth agnosticism, 29–30, 243–85 human nature, 28–9, 94–128 and population, 57–8 regeneration, 29, 158, 206–42 social foundation, 10, 11, 44, 45, 49, 51, 58, 77, 174, 200, 254, 295–6 systems, 28, 129–62 and technology, 57, 59 Douglas, Margaret, 78–9 Dreyfus, Louis, 148 ‘Dumb and Dumber in Macroeconomics’ (Solow), 135 Durban, South Africa, 214 E Earning by Learning, 120 Earth-system science, 44–53, 115, 216, 288, 298 Easter Island, 154 Easterlin, Richard, 265–6 eBay, 105, 192 eco-literacy, 115 ecological ceiling, 10, 11, 44, 45, 46, 49, 51, 218, 254, 295, 298 Ecological Performance Standards, 241 Econ 101 course, 8, 77 Economics (Lewis), 114 Economics (Samuelson), 19–20, 63–7, 70, 74, 78, 86, 91, 92, 93, 262 Economy for the Common Good, 241 ecosystem services, 7, 116, 269 Ecuador, 54 education, 9, 43, 45, 50–52, 85, 169–70, 176, 200, 249, 279 economic, 8, 11, 18, 22, 24, 36, 287–93 environmental, 115, 239–40 girls’, 57, 124, 178, 198 online, 83, 197, 264, 290 pricing, 118–19 efficient market hypothesis, 28, 62, 68, 87 Egypt, 48, 89 Eisenstein, Charles, 116 electricity, 9, 45, 236, 240 and Bangla Pesa, 186 cars, 231 Ethereum, 187–8 and MONIAC, 75, 262 pricing, 118, 213 see also renewable energy Elizabeth II, Queen of the United Kingdom, 145 Ellen MacArthur Foundation, 220 Embedded Economy, 71–93, 263 business, 88–9 commons, 82–4 Earth, 72–6 economy, 77–8 finance, 86–8 household, 78–81 market, 81–2 power, 91–92 society, 76–7 state, 84–6 trade, 89–90 employment, 36, 37, 51, 142, 176 automation, 191–5, 237, 258, 278 labour ownership, 188–91 workers’ rights, 88, 90, 269 Empty World, 74 Engels, Friedrich, 88 environment and circular economy, 220–42, 257 conservation, 121–2 and degenerative linear economy, 211–19, 222–3 degradation, 5, 9, 10, 29, 44–53, 74, 154, 172, 196, 206–42 education on, 115, 239–40 externalities, 152 fair share, 216–17 and finance, 234–7 generosity, 218–19, 223–7 green growth, 41, 210, 243–85 nudging, 123–5 taxation and quotas, 213–14, 215 zero impact, 217–18, 238, 241 Environmental Dashboard, 240–41 environmental economics, 7, 11, 114–16 Environmental Kuznets Curve, 207–11, 241 environmental space, 54 Epstein, Joshua, 150 equilibrium theory, 134–62 Ethereum, 187–8 ethics, 160–62 Ethiopia, 9, 226, 254 Etsy, 105 Euclid, 13, 15 European Central Bank, 145, 275 European Commission, 41 European Union (EU), 92, 153, 210, 222, 255, 258 Evergreen Cooperatives, 190 Evergreen Direct Investing (EDI), 273 exogenous shocks, 141 exponential growth, 39, 246–85 externalities, 143, 152, 213 Exxon Valdez oil spill (1989), 9 F Facebook, 192 fair share, 216–17 Fama, Eugene, 68, 87 fascism, 234, 277 Federal Reserve, US, 87, 145, 146, 271, 282 feedback loops, 138–41, 143, 148, 155, 250, 271 feminist economics, 11, 78–81, 160 Ferguson, Thomas, 91–2 finance animal spirits, 110 bank runs, 139 Black–Scholes model, 100–101 boom and bust, 28–9, 110, 144–7 and Circular Flow, 63–4, 87 and complex systems, 134, 138, 139, 140, 141, 145–7 cross-border flows, 89 deregulation, 87 derivatives, 100–101, 149 and distribution, 169, 170, 173, 182–4, 198–9, 201 and efficient market hypothesis, 63, 68 and Embedded Economy, 71, 86–8 and financial-instability hypothesis, 87, 146 and GDP growth, 38 and media, 7–8 mobile banking, 199–200 and money creation, 87, 182–5 and regeneration, 227, 229, 234–7 in service to life, 159, 234–7 stakeholder finance, 190 and sustainability, 216, 235–6, 239 financial crisis (2008), 1–4, 5, 40, 63, 86, 141, 144, 278, 290 and efficient market hypothesis, 87 and equilibrium theory, 134, 145 and financial-instability hypothesis, 87 and inequality, 90, 170, 172, 175 and money creation, 182 and worker’s rights, 278 financial flows, 89 Financial Times, 183, 266, 289 financial-instability hypothesis, 87, 146 First Green Bank, 236 First World War (1914–18), 166, 170 Fisher, Irving, 183 fluid values, 102, 106–9 food, 3, 43, 45, 50, 54, 58, 59, 89, 198 food banks, 165 food price crisis (2007–8), 89, 90, 180 Ford, 277–8 foreign direct investment, 89 forest conservation, 121–2 fossil fuels, 59, 73, 75, 92, 212, 260, 263 Foundations of Economic Analysis (Samuelson), 17–18 Foxconn, 193 framing, 22–3 France, 43, 165, 196, 238, 254, 256, 281, 290 Frank, Robert, 100 free market, 33, 37, 67, 68, 70, 81–2, 86, 90 free open-source hardware (FOSH), 196–7 free open-source software (FOSS), 196 free trade, 70, 90 Freeman, Ralph, 18–19 freshwater cycle, 48–9 Freud, Sigmund, 107, 281 Friedman, Benjamin, 258 Friedman, Milton, 34, 62, 66–9, 84–5, 88, 99, 183, 232 Friends of the Earth, 54 Full World, 75 Fuller, Buckminster, 4 Fullerton, John, 234–6, 273 G G20, 31, 56, 276, 279–80 G77, 55 Gal, Orit, 141 Gandhi, Mohandas, 42, 293 Gangnam Style, 145 Gardens of Democracy, The (Liu & Hanauer), 158 gender equality, 45, 51–2, 57, 78–9, 85, 88, 118–19, 124, 171, 198 generosity, 218–19, 223–9 geometry, 13, 15 George, Henry, 149, 179 Georgescu-Roegen, Nicholas, 252 geothermal energy, 221 Gerhardt, Sue, 283 Germany, 2, 41, 100, 118, 165, 189, 211, 213, 254, 256, 260, 274 Gessel, Silvio, 274 Ghent, Belgium, 236 Gift Relationship, The (Titmuss), 118–19 Gigerenzer, Gerd, 112–14 Gintis, Herb, 104 GiveDirectly, 200 Glass–Steagall Act (1933), 87 Glennon, Roger, 214 Global Alliance for Tax Justice, 277 global material footprints, 210–11 Global Village Construction Set, 196 globalisation, 89 Goerner, Sally, 175–6 Goffmann, Erving, 22 Going for Growth, 255 golden rule, 91 Goldman Sachs, 149, 170 Gómez-Baggethun, Erik, 122 Goodall, Chris, 211 Goodwin, Neva, 79 Goody, Jade, 124 Google, 192 Gore, Albert ‘Al’, 172 Gorgons, 244, 256, 257, 266 graffiti, 15, 25, 287 Great Acceleration, 46, 253–4 Great Depression (1929–39), 37, 70, 170, 173, 183, 275, 277, 278 Great Moderation, 146 Greece, Ancient, 4, 13, 32, 48, 54, 56–7, 160, 244 green growth, 41, 210, 243–85 Greenham, Tony, 185 greenhouse gas emissions, 31, 46, 50, 75–6, 141, 152–4 and decoupling, 260, 266 and Environmental Kuznets Curve, 208, 210 and forests, 50, 52 and G20, 31 and inequality, 58 reduction of, 184, 201–2, 213, 216–18, 223–7, 239–41, 256, 259–60, 266, 298 stock–flow dynamics, 152–4 and taxation, 201, 213 Greenland, 141, 154 Greenpeace, 9 Greenspan, Alan, 87 Greenwich, London, 290 Grenoble, France, 281 Griffiths, Brian, 170 gross domestic product (GDP), 25, 31–2, 35–43, 57, 60, 84, 164 as cuckoo, 32, 35, 36, 38, 40, 54, 60, 159, 244, 256, 271 and Environmental Kuznets Curve, 207–11 and exponential growth, 39, 53, 246–85 and growth agnosticism, 29–30, 240, 243–85 and inequality, 173 and Kuznets Curve, 167, 173, 188–9 gross national product (GNP), 36–40 Gross World Product, 248 Grossman, Gene, 207–8, 210 ‘grow now, clean up later’, 207 Guatemala, 196 H Haifa, Israel, 120 Haldane, Andrew, 146 Han Dynasty, 154 Hanauer, Nick, 158 Hansen, Pelle, 124 Happy Planet Index, 280 Hardin, Garrett, 69, 83, 181 Harvard University, 2, 271, 290 von Hayek, Friedrich, 7–8, 62, 66, 67, 143, 156, 158 healthcare, 43, 50, 57, 85, 123, 125, 170, 176, 200, 269, 279 Heilbroner, Robert, 53 Henry VIII, King of England and Ireland, 180 Hepburn, Cameron, 261 Herbert Simon, 111 heuristics, 113–14, 118, 123 high-income countries growth, 30, 244–5, 254–72, 282 inequality, 165, 168, 169, 171 labour, 177, 188–9, 278 overseas development assistance (ODA), 198–9 resource intensive lifestyles, 46, 210–11 trade, 90 Hippocrates, 160 History of Economic Analysis (Schumpeter), 21 HIV/AIDS, 123 Holocene epoch, 46–8, 75, 115, 253 Homo economicus, 94–103, 109, 127–8 Homo sapiens, 38, 104, 130 Hong Kong, 180 household, 78 housing, 45, 59, 176, 182–3, 269 Howe, Geoffrey, 67 Hudson, Michael, 183 Human Development Index, 9, 279 human nature, 28 human rights, 10, 25, 45, 49, 50, 95, 214, 233 humanistic economics, 42 hydropower, 118, 260, 263 I Illinois, United States, 179–80 Imago Mundi, 13 immigration, 82, 199, 236, 266 In Defense of Economic Growth (Beckerman), 258 Inclusive Wealth Index, 280 income, 51, 79–80, 82, 88, 176–8, 188–91, 194, 199–201 India, 2, 9, 10, 42, 124, 164, 178, 196, 206–7, 242, 290 Indonesia, 90, 105–6, 164, 168, 200 Indus Valley civilisation, 48 inequality, 1, 5, 25, 41, 63, 81, 88, 91, 148–52, 209 and consumerism, 111 and democracy, 171 and digital revolution, 191–5 and distribution, 163–205 and environmental degradation, 172 and GDP growth, 173 and greenhouse gas emissions, 58 and intellectual property, 195–8 and Kuznets Curve, 29, 166–70, 173–4 and labour ownership, 188–91 and land ownership, 178–82 and money creation, 182–8 and social welfare, 171 Success to the Successful, 148, 149, 151, 166 inflation, 36, 248, 256, 275 insect pollination services, 7 Institute of Economic Affairs, 67 institutional economics, 11 intellectual property rights, 195–8, 204 interest, 36, 177, 182, 184, 275–6 Intergovernmental Panel on Climate Change, 25 International Monetary Fund (IMF), 170, 172, 173, 183, 255, 258, 271 Internet, 83–4, 89, 105, 192, 202, 264 Ireland, 277 Iroquois Onondaga Nation, 116 Israel, 100, 103, 120 Italy, 165, 196, 254 J Jackson, Tim, 58 Jakubowski, Marcin, 196 Jalisco, Mexico, 217 Japan, 168, 180, 211, 222, 254, 256, 263, 275 Jevons, William Stanley, 16, 97–8, 131, 132, 137, 142 John Lewis Partnership, 190 Johnson, Lyndon Baines, 37 Johnson, Mark, 38 Johnson, Todd, 191 JPMorgan Chase, 149, 234 K Kahneman, Daniel, 111 Kamkwamba, William, 202, 204 Kasser, Tim, 125–6 Keen, Steve, 146, 147 Kelly, Marjorie, 190–91, 233 Kennedy, John Fitzgerald, 37, 250 Kennedy, Paul, 279 Kenya, 118, 123, 180, 185–6, 199–200, 226, 292 Keynes, John Maynard, 7–8, 22, 66, 69, 134, 184, 251, 277–8, 284, 288 Kick It Over movement, 3, 289 Kingston, London, 290 Knight, Frank, 66, 99 knowledge commons, 202–4, 229, 292 Kokstad, South Africa, 56 Kondratieff waves, 246 Korzybski, Alfred, 22 Krueger, Alan, 207–8, 210 Kuhn, Thomas, 22 Kumhof, Michael, 172 Kuwait, 255 Kuznets, Simon, 29, 36, 39–40, 166–70, 173, 174, 175, 204, 207 KwaZulu Natal, South Africa, 56 L labour ownership, 188–91 Lake Erhai, Yunnan, 56 Lakoff, George, 23, 38, 276 Lamelara, Indonesia, 105–6 land conversion, 49, 52, 299 land ownership, 178–82 land-value tax, 73, 149, 180 Landesa, 178 Landlord’s Game, The, 149 law of demand, 16 laws of motion, 13, 16–17, 34, 129, 131 Lehman Brothers, 141 Leopold, Aldo, 115 Lesotho, 118, 199 leverage points, 159 Lewis, Fay, 178 Lewis, Justin, 102 Lewis, William Arthur, 114, 167 Lietaer, Bernard, 175, 236 Limits to Growth, 40, 154, 258 Linux, 231 Liu, Eric, 158 living metrics, 240–42 living purpose, 233–4 Lomé, Togo, 231 London School of Economics (LSE), 2, 34, 65, 290 London Underground, 12 loss aversion, 112 low-income countries, 90, 164–5, 168, 173, 180, 199, 201, 209, 226, 254, 259 Lucas, Robert, 171 Lula da Silva, Luiz Inácio, 124 Luxembourg, 277 Lyle, John Tillman, 214 Lyons, Oren, 116 M M–PESA, 199–200 MacDonald, Tim, 273 Machiguenga, 105–6 MacKenzie, Donald, 101 macroeconomics, 36, 62–6, 76, 80, 134–5, 145, 147, 150, 244, 280 Magie, Elizabeth, 149, 153 Malala effect, 124 malaria, 5 Malawi, 118, 202, 204 Malaysia, 168 Mali, Taylor, 243 Malthus, Thomas, 252 Mamsera Rural Cooperative, 190 Manhattan, New York, 9, 41 Mani, Muthukumara, 206 Manitoba, 282 Mankiw, Gregory, 2, 34 Mannheim, Karl, 22 Maoris, 54 market, 81–2 and business, 88 circular flow, 64 and commons, 83, 93, 181, 200–201 efficiency of, 28, 62, 68, 87, 148, 181 and equilibrium theory, 131–5, 137, 143–7, 155, 156 free market, 33, 37, 67–70, 90, 208 and households, 63, 69, 78, 79 and maxi-max rule, 161 and pricing, 117–23, 131, 160 and rational economic man, 96, 100–101, 103, 104 and reciprocity, 105, 106 reflexivity of, 144–7 and society, 69–70 and state, 84–6, 200, 281 Marshall, Alfred, 17, 98, 133, 165, 253, 282 Marx, Karl, 88, 142, 165, 272 Massachusetts Institute of Technology (MIT), 17–20, 152–5 massive open online courses (MOOCs), 290 Matthew Effect, 151 Max-Neef, Manfred, 42 maxi-max rule, 161 maximum wage, 177 Maya civilisation, 48, 154 Mazzucato, Mariana, 85, 195, 238 McAfee, Andrew, 194, 258 McDonough, William, 217 Meadows, Donella, 40, 141, 159, 271, 292 Medusa, 244, 257, 266 Merkel, Angela, 41 Messerli, Elspeth, 187 Metaphors We Live By (Lakoff & Johnson), 38 Mexico, 121–2, 217 Michaels, Flora S., 6 micro-businesses, 9, 173, 178 microeconomics, 132–4 microgrids, 187–8 Micronesia, 153 Microsoft, 231 middle class, 6, 46, 58 middle-income countries, 90, 164, 168, 173, 180, 226, 254 migration, 82, 89–90, 166, 195, 199, 236, 266, 286 Milanovic, Branko, 171 Mill, John Stuart, 33–4, 73, 97, 250, 251, 283, 284, 288 Millo, Yuval, 101 minimum wage, 82, 88, 176 Minsky, Hyman, 87, 146 Mises, Ludwig von, 66 mission zero, 217 mobile banking, 199–200 mobile phones, 222 Model T revolution, 277–8 Moldova, 199 Mombasa, Kenya, 185–6 Mona Lisa (da Vinci), 94 money creation, 87, 164, 177, 182–8, 205 MONIAC (Monetary National Income Analogue Computer), 64–5, 75, 142, 262 Monoculture (Michaels), 6 Monopoly, 149 Mont Pelerin Society, 67, 93 Moral Consequences of Economic Growth, The (Friedman), 258 moral vacancy, 41 Morgan, Mary, 99 Morogoro, Tanzania, 121 Moyo, Dambisa, 258 Muirhead, Sam, 230, 231 MultiCapital Scorecard, 241 Murphy, David, 264 Murphy, Richard, 185 musical tastes, 110 Myriad Genetics, 196 N national basic income, 177 Native Americans, 115, 116, 282 natural capital, 7, 116, 269 Natural Economic Order, The (Gessel), 274 Nedbank, 216 negative externalities, 213 negative interest rates, 275–6 neoclassical economics, 134, 135 neoliberalism, 7, 62–3, 67–70, 81, 83, 84, 88, 93, 143, 170, 176 Nepal, 181, 199 Nestlé, 217 Netherlands, 211, 235, 224, 226, 238, 277 networks, 110–11, 117, 118, 123, 124–6, 174–6 neuroscience, 12–13 New Deal, 37 New Economics Foundation, 278, 283 New Year’s Day, 124 New York, United States, 9, 41, 55 Newlight Technologies, 224, 226, 293 Newton, Isaac, 13, 15–17, 32–3, 95, 97, 129, 131, 135–7, 142, 145, 162 Nicaragua, 196 Nigeria, 164 nitrogen, 49, 52, 212–13, 216, 218, 221, 226, 298 ‘no pain, no gain’, 163, 167, 173, 204, 209 Nobel Prize, 6–7, 43, 83, 101, 167 Norway, 281 nudging, 112, 113, 114, 123–6 O Obama, Barack, 41, 92 Oberlin, Ohio, 239, 240–41 Occupy movement, 40, 91 ocean acidification, 45, 46, 52, 155, 242, 298 Ohio, United States, 190, 239 Okun, Arthur, 37 onwards and upwards, 53 Open Building Institute, 196 Open Source Circular Economy (OSCE), 229–32 open systems, 74 open-source design, 158, 196–8, 265 open-source licensing, 204 Organisation for Economic Co-operation and Development (OECD), 38, 210, 255–6, 258 Origin of Species, The (Darwin), 14 Ormerod, Paul, 110, 111 Orr, David, 239 Ostrom, Elinor, 83, 84, 158, 160, 181–2 Ostry, Jonathan, 173 OSVehicle, 231 overseas development assistance (ODA), 198–200 ownership of wealth, 177–82 Oxfam, 9, 44 Oxford University, 1, 36 ozone layer, 9, 50, 115 P Pachamama, 54, 55 Pakistan, 124 Pareto, Vilfredo, 165–6, 175 Paris, France, 290 Park 20|20, Netherlands, 224, 226 Parker Brothers, 149 Patagonia, 56 patents, 195–6, 197, 204 patient capital, 235 Paypal, 192 Pearce, Joshua, 197, 203–4 peer-to-peer networks, 187, 192, 198, 203, 292 People’s QE, 184–5 Perseus, 244 Persia, 13 Peru, 2, 105–6 Phillips, Adam, 283 Phillips, William ‘Bill’, 64–6, 75, 142, 262 phosphorus, 49, 52, 212–13, 218, 298 Physiocrats, 73 Pickett, Kate, 171 pictures, 12–25 Piketty, Thomas, 169 Playfair, William, 16 Poincaré, Henri, 109, 127–8 Polanyi, Karl, 82, 272 political economy, 33–4, 42 political funding, 91–2, 171–2 political voice, 43, 45, 51–2, 77, 117 pollution, 29, 45, 52, 85, 143, 155, 206–17, 226, 238, 242, 254, 298 population, 5, 46, 57, 155, 199, 250, 252, 254 Portugal, 211 post-growth society, 250 poverty, 5, 9, 37, 41, 50, 88, 118, 148, 151 emotional, 283 and inequality, 164–5, 168–9, 178 and overseas development assistance (ODA), 198–200 and taxation, 277 power, 91–92 pre-analytic vision, 21–2 prescription medicines, 123 price-takers, 132 prices, 81, 118–23, 131, 160 Principles of Economics (Mankiw), 34 Principles of Economics (Marshall), 17, 98 Principles of Political Economy (Mill), 288 ProComposto, 226 Propaganda (Bernays), 107 public relations, 107, 281 public spending v. investment, 276 public–private patents, 195 Putnam, Robert, 76–7 Q quantitative easing (QE), 184–5 Quebec, 281 Quesnay, François, 16, 73 R Rabot, Ghent, 236 Rancière, Romain, 172 rating and review systems, 105 rational economic man, 94–103, 109, 111, 112, 126, 282 Reagan, Ronald, 67 reciprocity, 103–6, 117, 118, 123 reflexivity of markets, 144 reinforcing feedback loops, 138–41, 148, 250, 271 relative decoupling, 259 renewable energy biomass energy, 118, 221 and circular economy, 221, 224, 226, 235, 238–9, 274 and commons, 83, 85, 185, 187–8, 192, 203, 264 geothermal energy, 221 and green growth, 257, 260, 263, 264, 267 hydropower, 118, 260, 263 pricing, 118 solar energy, see solar energy wave energy, 221 wind energy, 75, 118, 196, 202–3, 221, 233, 239, 260, 263 rentier sector, 180, 183, 184 reregulation, 82, 87, 269 resource flows, 175 resource-intensive lifestyles, 46 Rethinking Economics, 289 Reynebeau, Guy, 237 Ricardo, David, 67, 68, 73, 89, 250 Richardson, Katherine, 53 Rifkin, Jeremy, 83, 264–5 Rise and Fall of the Great Powers, The (Kennedy), 279 risk, 112, 113–14 Robbins, Lionel, 34 Robinson, James, 86 Robinson, Joan, 142 robots, 191–5, 237, 258, 278 Rockefeller Foundation, 135 Rockford, Illinois, 179–80 Rockström, Johan, 48, 55 Roddick, Anita, 232–4 Rogoff, Kenneth, 271, 280 Roman Catholic Church, 15, 19 Rombo, Tanzania, 190 Rome, Ancient, 13, 48, 154 Romney, Mitt, 92 Roosevelt, Franklin Delano, 37 rooted membership, 190 Rostow, Walt, 248–50, 254, 257, 267–70, 284 Ruddick, Will, 185 rule of thumb, 113–14 Ruskin, John, 42, 223 Russia, 200 rust belt, 90, 239 S S curve, 251–6 Sainsbury’s, 56 Samuelson, Paul, 17–21, 24–5, 38, 62–7, 70, 74, 84, 91, 92, 93, 262, 290–91 Sandel, Michael, 41, 120–21 Sanergy, 226 sanitation, 5, 51, 59 Santa Fe, California, 213 Santinagar, West Bengal, 178 São Paolo, Brazil, 281 Sarkozy, Nicolas, 43 Saumweder, Philipp, 226 Scharmer, Otto, 115 Scholes, Myron, 100–101 Schumacher, Ernst Friedrich, 42, 142 Schumpeter, Joseph, 21 Schwartz, Shalom, 107–9 Schwarzenegger, Arnold, 163, 167, 204 ‘Science and Complexity’ (Weaver), 136 Scotland, 57 Seaman, David, 187 Seattle, Washington, 217 second machine age, 258 Second World War (1939–45), 18, 37, 70, 170 secular stagnation, 256 self-interest, 28, 68, 96–7, 99–100, 102–3 Selfish Society, The (Gerhardt), 283 Sen, Amartya, 43 Shakespeare, William, 61–3, 67, 93 shale gas, 264, 269 Shang Dynasty, 48 shareholders, 82, 88, 189, 191, 227, 234, 273, 292 sharing economy, 264 Sheraton Hotel, Boston, 3 Siegen, Germany, 290 Silicon Valley, 231 Simon, Julian, 70 Sinclair, Upton, 255 Sismondi, Jean, 42 slavery, 33, 77, 161 Slovenia, 177 Small Is Beautiful (Schumacher), 42 smart phones, 85 Smith, Adam, 33, 57, 67, 68, 73, 78–9, 81, 96–7, 103–4, 128, 133, 160, 181, 250 social capital, 76–7, 122, 125, 172 social contract, 120, 125 social foundation, 10, 11, 44, 45, 49, 51, 58, 77, 174, 200, 254, 295–6 social media, 83, 281 Social Progress Index, 280 social pyramid, 166 society, 76–7 solar energy, 59, 75, 111, 118, 187–8, 190 circular economy, 221, 222, 223, 224, 226–7, 239 commons, 203 zero-energy buildings, 217 zero-marginal-cost revolution, 84 Solow, Robert, 135, 150, 262–3 Soros, George, 144 South Africa, 56, 177, 214, 216 South Korea, 90, 168 South Sea Bubble (1720), 145 Soviet Union (1922–91), 37, 67, 161, 279 Spain, 211, 238, 256 Spirit Level, The (Wilkinson & Pickett), 171 Sraffa, Piero, 148 St Gallen, Switzerland, 186 Stages of Economic Growth, The (Rostow), 248–50, 254 stakeholder finance, 190 Standish, Russell, 147 state, 28, 33, 69–70, 78, 82, 160, 176, 180, 182–4, 188 and commons, 85, 93, 197, 237 and market, 84–6, 200, 281 partner state, 197, 237–9 and robots, 195 stationary state, 250 Steffen, Will, 46, 48 Sterman, John, 66, 143, 152–4 Steuart, James, 33 Stiglitz, Joseph, 43, 111, 196 stocks and flows, 138–41, 143, 144, 152 sub-prime mortgages, 141 Success to the Successful, 148, 149, 151, 166 Sugarscape, 150–51 Summers, Larry, 256 Sumner, Andy, 165 Sundrop Farms, 224–6 Sunstein, Cass, 112 supply and demand, 28, 132–6, 143, 253 supply chains, 10 Sweden, 6, 255, 275, 281 swishing, 264 Switzerland, 42, 66, 80, 131, 186–7, 275 T Tableau économique (Quesnay), 16 tabula rasa, 20, 25, 63, 291 takarangi, 54 Tanzania, 121, 190, 202 tar sands, 264, 269 taxation, 78, 111, 165, 170, 176, 177, 237–8, 276–9 annual wealth tax, 200 environment, 213–14, 215 global carbon tax, 201 global financial transactions tax, 201, 235 land-value tax, 73, 149, 180 non-renewable resources, 193, 237–8, 278–9 People’s QE, 185 tax relief v. tax justice, 23, 276–7 TED (Technology, Entertainment, Design), 202, 258 Tempest, The (Shakespeare), 61, 63, 93 Texas, United States, 120 Thailand, 90, 200 Thaler, Richard, 112 Thatcher, Margaret, 67, 69, 76 Theory of Moral Sentiments (Smith), 96 Thompson, Edward Palmer, 180 3D printing, 83–4, 192, 198, 231, 264 thriving-in-balance, 54–7, 62 tiered pricing, 213–14 Tigray, Ethiopia, 226 time banking, 186 Titmuss, Richard, 118–19 Toffler, Alvin, 12, 80 Togo, 231, 292 Torekes, 236–7 Torras, Mariano, 209 Torvalds, Linus, 231 trade, 62, 68–9, 70, 89–90 trade unions, 82, 176, 189 trademarks, 195, 204 Transatlantic Trade and Investment Partnership (TTIP), 92 transport, 59 trickle-down economics, 111, 170 Triodos, 235 Turkey, 200 Tversky, Amos, 111 Twain, Mark, 178–9 U Uganda, 118, 125 Ulanowicz, Robert, 175 Ultimatum Game, 105, 117 unemployment, 36, 37, 276, 277–9 United Kingdom Big Bang (1986), 87 blood donation, 118 carbon dioxide emissions, 260 free trade, 90 global material footprints, 211 money creation, 182 MONIAC (Monetary National Income Analogue Computer), 64–5, 75, 142, 262 New Economics Foundation, 278, 283 poverty, 165, 166 prescription medicines, 123 wages, 188 United Nations, 55, 198, 204, 255, 258, 279 G77 bloc, 55 Human Development Index, 9, 279 Sustainable Development Goals, 24, 45 United States American Economic Association meeting (2015), 3 blood donation, 118 carbon dioxide emissions, 260 Congress, 36 Council of Economic Advisers, 6, 37 Earning by Learning, 120 Econ 101 course, 8, 77 Exxon Valdez oil spill (1989), 9 Federal Reserve, 87, 145, 146, 271, 282 free trade, 90 Glass–Steagall Act (1933), 87 greenhouse gas emissions, 153 global material footprint, 211 gross national product (GNP), 36–40 inequality, 170, 171 land-value tax, 73, 149, 180 political funding, 91–2, 171 poverty, 165, 166 productivity and employment, 193 rust belt, 90, 239 Transatlantic Trade and Investment Partnership (TTIP), 92 wages, 188 universal basic income, 200 University of Berkeley, 116 University of Denver, 160 urbanisation, 58–9 utility, 35, 98, 133 V values, 6, 23, 34, 35, 42, 117, 118, 121, 123–6 altruism, 100, 104 anthropocentric, 115 extrinsic, 115 fluid, 28, 102, 106–9 and networks, 110–11, 117, 118, 123, 124–6 and nudging, 112, 113, 114, 123–6 and pricing, 81, 120–23 Veblen, Thorstein, 82, 109, 111, 142 Venice, 195 verbal framing, 23 Verhulst, Pierre, 252 Victor, Peter, 270 Viner, Jacob, 34 virtuous cycles, 138, 148 visual framing, 23 Vitruvian Man, 13–14 Volkswagen, 215–16 W Wacharia, John, 186 Wall Street, 149, 234, 273 Wallich, Henry, 282 Walras, Léon, 131, 132, 133–4, 137 Ward, Barbara, 53 Warr, Benjamin, 263 water, 5, 9, 45, 46, 51, 54, 59, 79, 213–14 wave energy, 221 Ways of Seeing (Berger), 12, 281 Wealth of Nations, The (Smith), 74, 78, 96, 104 wealth ownership, 177–82 Weaver, Warren, 135–6 weightless economy, 261–2 WEIRD (Western, educated, industrialised, rich, democratic), 103–5, 110, 112, 115, 117, 282 West Bengal, India, 124, 178 West, Darrell, 171–2 wetlands, 7 whale hunting, 106 Wiedmann, Tommy, 210 Wikipedia, 82, 223 Wilkinson, Richard, 171 win–win trade, 62, 68, 89 wind energy, 75, 118, 196, 202–3, 221, 233, 239, 260, 263 Wizard of Oz, The, 241 Woelab, 231, 293 Wolf, Martin, 183, 266 women’s rights, 33, 57, 107, 160, 201 and core economy, 69, 79–81 education, 57, 124, 178, 198 and land ownership, 178 see also gender equality workers’ rights, 88, 91, 269 World 3 model, 154–5 World Bank, 6, 41, 119, 164, 168, 171, 206, 255, 258 World No Tobacco Day, 124 World Trade Organization, 6, 89 worldview, 22, 54, 115 X xenophobia, 266, 277, 286 Xenophon, 4, 32, 56–7, 160 Y Yandle, Bruce, 208 Yang, Yuan, 1–3, 289–90 yin yang, 54 Yousafzai, Malala, 124 YouTube, 192 Yunnan, China, 56 Z Zambia, 10 Zanzibar, 9 Zara, 276 Zeitvorsoge, 186–7 zero environmental impact, 217–18, 238, 241 zero-hour contracts, 88 zero-humans-required production, 192 zero-interest loans, 183 zero-marginal-cost revolution, 84, 191, 264 zero-waste manufacturing, 227 Zinn, Howard, 77 PICTURE ACKNOWLEDGEMENTS Illustrations are reproduced by kind permission of: archive.org

How I Became a Quant: Insights From 25 of Wall Street's Elite
by Richard R. Lindsey and Barry Schachter
Published 30 Jun 2007

By the 1950s, Harry Markowitz was turning portfolio construction into a disciplined endeavor. The academic scene exploded in the 1960s with seminal ideas like the capital asset pricing model, and in the 1970s with arbitrage pricing theory and the Black-Scholes-Merton option pricing formula. In 1965, the University of Chicago’s Eugene Fama published “The Behavior of Stock Prices,” which laid the foundation of the efficient market hypothesis. Fama theorized that stock prices fully and instantaneously reflect all available information. In the same year, Paul Samuelson at MIT published his “Proof that Properly Anticipated Prices Fluctuate Randomly,” which showed that, in an efficient market, price changes are random and thus inherently unpredictable.

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While at Equitable, I began to participate in a variety of industry forums such as the Institute for Quantitative Research in Finance (the Q Group) and the Investment Technology Association, which is now JWPR007-Lindsey May 7, 2007 17:15 Mark Kritzman 253 called the Society for Quantitative Analysis (SQA). One year, in the early 1980s, I was responsible for the SQA conference program and lined up Fischer Black, Eugene Fama, Bob Merton, Stew Myers, Myron Scholes, Steve Ross, and Jack Treynor as speakers, among others. I also attended the CRSP conferences at the University of Chicago and the Berkeley Program in Finance. It was at these gatherings that my interest in quantitative methods gained momentum. In 1980, I accepted a position in the investment department of AT&T.

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Could computer intensive statistical techniques extract signals of future performance from observed prices? Many months (and computer cycles) later, I learned there was a dramatic difference in the accuracy of predictions using within-sample data and those tested on out-of-sample data. I was well on the way to becoming a convert to the efficient market hypothesis. Inaccurate predictions were not just the result of overt data mining. Because of the work I was doing, I was allowed to attend investment meetings between the trust company and some of its most prestigious corporate clients. One meeting in particular comes to mind. I listened with rapt attention to authoritative dictums and insightful analysis.

Chaos Kings: How Wall Street Traders Make Billions in the New Age of Crisis
by Scott Patterson
Published 5 Jun 2023

It was there that he met his future wife, Mary, who decided soon after to move back to her home in Minnesota. He followed, enrolling in the University of Minnesota’s economics department. It was dominated by professors who worshipped at the altar of the Chicago School of Economics and all that entailed—the free and open markets of Milton Friedman and George Stigler, the efficient markets of Eugene Fama. While working at the university’s computer center, he answered students’ questions about programming and supported the university’s statistical software packages. His computer skills caught the attention of two young professors in the department: Tom Sargent and Chris Sims, both of whom went on to become Nobel Prize winners.

…

A year before taking on the firm’s risk management assignment, he’d asked Goldman’s managing partner—and future New Jersey governor—Jon Corzine for a spot in the portfolio-management department. “Nah Bob,” Corzine said. “We have much more important things in line for you.” Around that time, Goldman hired a budding superstar and protégé of Eugene Fama at the University of Chicago, Cliff Asness. In 1995, Asness launched a trading outfit called Global Alpha, which quickly became a cash cow for the firm and its partners, with returns of 93 percent in 1996 and 35 percent in 1997. Litterman was amazed at Asness’s success and pleased to learn that he was using both the Black-Litterman model and the computer program Litterman had helped launch after his brief MIT teaching stint—RATS.

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It is a conundrum that has twisted the brain of many an economics student. If markets are always instantly efficient, why do traders exist? In part, the theory goes, the traders are the vehicle for making the market efficient. If a stock is too high, they sell it. If a stock is too low, they buy it. But too high or too low seem to inherently violate the efficient markets hypothesis, which also proposes that traders cannot consistently beat the market. How could they if the market was always right? Despite Yarckin’s skepticism, he graduated in three years with an economics degree and in 2000 found himself in New York City interviewing for jobs at major financial institutions.

Radical Uncertainty: Decision-Making for an Unknowable Future
by Mervyn King and John Kay
Published 5 Mar 2020

But Tucker was not talking about the US criminal justice system, nor Akerlof impugning the integrity of members of the Retail Motor Federation. And no information about the production costs of textile mills refutes Ricardo’s exposition of the principle of comparative advantage. The efficient market hypothesis is one of the most controversial models in economics – so controversial that in 2013 Eugene Fama, who developed the model, shared the Nobel Prize with Robert Shiller, who has worked to refute it. The essential insight is that publicly available information is incorporated in securities prices. The explanation of the seemingly contradictory accolades – it is hard to believe that a similar award would be made in the natural sciences – is that it is a mistake either to believe that the hypothesis is true or to assert that it is false.

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But we do know that diversification reduces the risk that the reference narrative – the reliable emergency fund, the security of retirement, the continued growth of the college endowment – might not be realised. The efficient market hypothesis, taken literally, implies that the investment success of George Soros, Warren Buffett and Jim Simons is impossible. Frank Knight, who recognised that radical uncertainty generates profit opportunities, has been vindicated by the extraordinary riches accumulated by these men. And the efficient market hypothesis is shown to be illuminating – an indispensable model – without being true. Buffett, history’s most successful investor, was well aware of this. He wrote of proponents of the efficient market hypothesis: ‘Observing correctly that the market was frequently efficient, they went on to conclude incorrectly that it was always efficient.

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The explanation of the seemingly contradictory accolades – it is hard to believe that a similar award would be made in the natural sciences – is that it is a mistake either to believe that the hypothesis is true or to assert that it is false. Most public information is incorporated in securities prices, but not always or perfectly, and that latter fact makes it possible to design successful investment strategies. Both supporters and critics of the efficient market hypothesis appear to make the mistake of believing that such a model describes ‘the world as it really is’. The efficient market hypothesis is the archetype of a model which is illuminating without being ‘true’. Like great stage plays, such as Macbeth . A small-world model is a fictional narrative, and its truth is found in its broad insights rather than its specific detail.

The Economics of Enough: How to Run the Economy as if the Future Matters
by Diane Coyle
Published 21 Feb 2011

He points out that economics is not just a research discipline that seeks to understand the world but also, to paraphrase Karl Marx, changes the world though its impact on policy and decisions. Financial economics has been particularly influential in this respect. Mackenzie and his coauthors single out the influence of Eugene Fama’s efficient markets hypothesis, which says that stock market prices capture all available information about the value of the shares and investment managers can never consistently beat the market: The efficient market hypothesis is not simply an analysis of financial markets as “external” things but has become woven into market practices. Most important, it helped inspire the establishment of index tracking funds.

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Option pricing theory explains the growth—without the theory about what the prices of these derivative contracts ought to be, there could have been no trade in them. The theory created the reality of the market. Needless to say, the financial crisis has severely undermined belief in the validity of the efficient markets hypothesis—although its creator, Eugene Fama, remains adamant that the theory is empirically correct. In a 2009 interview, he said: Prices are good estimates of the underlying value of the asset. There are real risks of volatility in stocks, and this current episode is a good example. . . . This is not a financial recession.

Creative Intelligence: Harnessing the Power to Create, Connect, and Inspire
by Bruce Nussbaum
Published 5 Mar 2013

I may have witnessed the apogee of financial capitalism in Davos, but it got its start some four decades earlier in Chicago. In May of 1970, Eugene Fama, a professor at the Booth School of Business, published an article in the Journal of Finance called “Efficient Capital Markets: A Review of Theory and Empirical Work.” In it, Fama would take Adam Smith’s theory of the “invisible hand” to new levels. Along with that of Milton Friedman, Frank Knight, George Stigler, and other economists at Chicago, Fama’s work led to the economic model we now call the efficient market hypothesis or efficient market theory. In its purely financial form, EMT attempted to describe how stocks and markets functioned.

…

NewsId=34502; “HP Still Has Top Market Share for PCs,” Forbes, October 13, 2011, accessed September 14, 2012, http://www.forbes.com/sites/marketnewsvideo/ 2011/10/13/hp-still-has-top-market-share-for-pcs/; Terrence O’Brien, “HP Reclaims Top Spot in PC Sales, Market as a Whole Climbs 21 Percent,” http://engadget.com, May 1, 2012, accessed September 14, 2012, http://www.engadget.com/2012/05/01/ hp-reclaims-top-spot-in-pc-sales-market-as-a-whole-climbs-21-pe/. 226 Even when its labs produced: http://www.polycom.com/products/polycom_halo.html, accessed September 14, 2012; Mark Speir, “Polycom Acquires HP’s Halo Video Conferencing for $89M,” RCR Wireless, June 1, 2011, accessed September 14, 2012, http://www.rcrwireless.com/austin/20110601/ components/polycom-acquires-hps-halo-video-conferencing-for-89m/. 227 sociologist Erving Goffman: Erving Goffman, Encounters: Two Studies in the Sociology of Interaction (Indianapolis, IN: Bobbs-Merrill, 1961), 78; referenced in Clifford Geertz, The Interpretation of Cultures (New York: Basic Books, 1973), 436. 227 Great Recession would soon: Michael Lind, “The Failure of Shareholder Capitalism,” http://Salon.com, March 29, 2011, accessed September 13, 2012, http://www.salon.com/2011/03/29/ failure_of_shareholder_capitalism/; “A New Idolatry,” Economist, April 22, 2010, accessed September 13, 2012, http://www.economist.com/node/15954434. 228 In May of 1970, Eugene Fama: Eugene F. Fama, “Efficient Capital Markets: A Review of Theory and Empirical Work,” Journal of Finance, vol. 25, no. 2, Papers and Proceedings of the Twenty-Eighth Annual Meeting of the American Finance Association New York, N.Y., December 28 to 30, 1969 (May 1970), 383–417. Published by Wiley-Blackwell for the American Finance Association. 228 In it, Fama would take: Joe Nocera, “Poking Holes in a Theory on Markets,” New York Times, June 6, 2006, accessed September 13, 2012, http://www.nytimes.com/2009/06/06/business/ 06nocera.html?

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Siegel, “Efficient Market Theory and the Crisis,” Wall Street Journal Online, October 27, 2009, accessed September 13, 2012, http://online.wsj.com/article/ SB10001424052748703573604574491261905165886.html. 228 Of course, what was missing: I am indebted to Ben Lee, who received his PhD from the University of Chicago, for highlighting the difference between uncertainty and risk in the economic analysis and theory formation that came out Chicago’s economics department. This distinction forms a major theme in the course we co-teach at Parsons. Ray Ball, “The Global Financial Crisis and the Efficient Market Hypothesis: What Have We Learned?” 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.

A Man for All Markets
by Edward O. Thorp
Published 15 Nov 2016

When I became interested in the stock market, I heard the same claims about investing. Academics had developed a series of arguments known as the efficient market hypothesis (EMH). Using financial market data, they showed that tomorrow’s prices looked like random fluctuations around today’s prices, therefore they were not predictable. Besides, if a price change were predictable, somebody would immediately trade on this until it was no longer so. This notion gave rise to an apocryphal story that all finance students have heard. Eugene Fama, father of EMH, was strolling across the University of Chicago campus with a graduate student. Looking down, the student exclaimed, “Look, there is a $100 bill on the ground.”

…

Yet the repeated exposés are not processed by the EMH true believer. Former UCI professor Robert Haugen, a vocal academic critic of the EMH and the author of several books arguing against the EMH, got an extreme response. During a UCLA conference, The Market Debate: A Break from Tradition, after Haugen delivered a paper on market inefficiency, he reported that Eugene Fama, father of the EMH and future co-recipient of the 2013 Nobel Prize in Economics, “…pointed to me in the audience and called me a criminal. He then said that he believed that GOD knew that the stock market was efficient. He added that the closer one came to behavioral finance, the hotter one could feel the fires of Hell on one’s feet.”

…

The likelihood of any card being dealt next at blackjack also is not random if you count the cards. What appears random for one state of knowledge may not be if we are given more information. Future prices are not predictable and no one can beat the market, but only when market prices “truly” fluctuate randomly. Supporters of the efficient market hypothesis, really a collection of related hypotheses, generally believe that securities markets in advanced developed countries respond quickly and almost completely to new information. True believers originally held that most investors were rational and well informed over the decades. However, they have reluctantly yielded to the overwhelming evidence to the contrary, but they still say the collective impact of investors generally keeps current market prices close to the best possible estimate of the value, averaged over all future scenarios.

Straight Talk on Trade: Ideas for a Sane World Economy
by Dani Rodrik
Published 8 Oct 2017

When the 2013 Nobel Prize in economics (technically the Sveriges Riksbank Prize in Economic Sciences in Memory of Alfred Nobel) was awarded to Eugene Fama and Robert Shiller, along with Lars Peter Hansen, many were puzzled by the selection. Fama and Shiller are both distinguished and highly regarded scholars, so it was not their qualifications that raised eyebrows. What seemed odd was that the committee had picked them together. The two economists seem to hold diametrically opposed views on how financial markets work. Fama, the University of Chicago economist, is the father of the “efficient market hypothesis,” the theory that asset prices reflect all publicly available information, with the implication that it is impossible to consistently beat the market.

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Unfortunately, empirical evidence in economics is rarely reliable enough to settle decisively a controversy characterized by deeply divided opinion—certainly not in real time. This is particularly true in macroeconomics, where the time-series data are open to diverse interpretations. Those with strong priors in favor of financial market efficiency, such as Eugene Fama, for example, can continue to absolve financial markets from culpability for the crisis, laying the blame elsewhere. Keynesians and “classical” economists can continue to disagree on their interpretation of high unemployment. But even in microeconomics, where it is sometimes possible to generate precise empirical estimates using randomized controlled trials, those estimates apply only locally to a particular setting.

Sabotage: The Financial System's Nasty Business
by Anastasia Nesvetailova and Ronen Palan
Published 28 Jan 2020

They have to be: the system in which they operate is fast-changing, competitive and very, very tough. But working hard or being smart is not good enough in today’s financial markets. Finance is a fiercely dynamic and competitive industry, with capital markets being among the closest to what academics call the ‘efficient market hypothesis (EMH)’. Proposed by, among others, two Nobel laureates, Paul Samuelson and Eugene Fama, EMH is often misunderstood. It tends to be simplified to imply that ‘markets know best’. The theory appears to suggest that markets allocate resources so efficiently and quickly that no outside intervention by governments or regulators is ever needed.

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Because if trading units operate in competitive markets, then they will be forced to innovate, make efficiency gains and ultimately optimize societal resource allocation. States and governments are encouraged, therefore, to curb their natural tendency to intervene in the markets, including the financial markets. There are many problems with the theory, and they have been discussed ad nauseam in wider literature. The efficient market hypothesis is only one variant of a core assumption of standard economics. It suggests that in the long run profits in perfectly competitive markets are close to zero. As new firms enter the industry, they increase the supply of the product available in the market, forcing prices down to the point of near-zero profits.

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The cases described above provide only very few illustrations of a general trend. Some observers will inevitably want to attribute the behaviour to isolated rogue elements within specific banks, operating on their own initiative. But we are much more pessimistic. As Paul Samuelson argued many years back, the efficient market hypothesis suggests that neither banks nor other financial institutions can make money just because of their superior ability to interpret financial trends. The alternative and better-guaranteed source of income, to come back to the legendary quips emerging from Lehman’s meeting, is to take advantage of the ‘dumbest person in the room’.

The Einstein of Money: The Life and Timeless Financial Wisdom of Benjamin Graham
by Joe Carlen
Published 14 Apr 2012

As Buffett said, “There are no undervalued stocks, these theorists argue, because there are smart security analysts who utilize all available information to ensure unfailingly appropriate prices.”57 Of course, the fact that a particular investment approach would outperform the market by a significant margin certainly calls the universality of EMT into question and strengthens the validity of Graham's core premise that there are superior long-term rewards for identifying and purchasing securities that are underpriced relative to their intrinsic value. As a market commentator wrote in 2010 regarding a more current perspective on “The Superinvestors of Graham and Doddsville,” “Overall Warren Buffett beats Eugene Fama and the Efficient Market Hypothesis crowd by 5–2.”58 Or, in the language of the scientific method, the data is clearly in favor of the “Graham and Dodd” hypothesis (of superior returns through capitalizing upon high price-value discrepancies), not the EMT. Indeed, the performance of the gold miner equipped with a powerful sensor system is consistently better than the miner who's just taking random stabs in the ground.

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As noted value investor and writer Jason Zweig highlighted in his commentary that augments the 2003 edition of The Intelligent Investor, “When asked what keeps most individual investors from succeeding, Graham had a concise answer: ‘The primary cause of failure is that they pay too much attention to what the stock market is doing currently.’”9 This answer strikes at the heart of the widely popular efficient market theory (EMT). EMT posits that market pricing, representing the collective results of many well-informed market participants, can be relied on to be correct or “efficient.” The most authoritative test supporting this hypothesis was conducted by University of Chicago economist Eugene Fama in the 1960s (although even Fama conceded that market efficiency was a continuum and did not hold with absolute strength and consistency10). As noted investment-finance academic and author Lawrence Cunningham wrote, due to this alleged market efficiency, Fama “concluded that no trading rule or strategy could be derived that outperformed the market consistently.”11 Indeed, if EMT (in its purest form) is correct, then there are no inefficiencies for any investment strategy, including value investing, to exploit.

Makers and Takers: The Rise of Finance and the Fall of American Business
by Rana Foroohar
Published 16 May 2016

As Friedman famously said back in 1970, “the social responsibility of business is to increase its profits.”33 This went hand in hand with another idea, which was that the share price of a firm always perfectly reflected all known information, and thus stock prices were the best overall measure of corporate value. This idea, known as the “efficient-market hypothesis,” eventually won its creator, another Friedman disciple and Chicago academic, Eugene Fama, the Nobel Prize. Ironically, Fama won it jointly in 2013 with Robert Shiller, a Yale economist whose work basically said the opposite—that markets, and asset values, were influenced by a variety of things (emotions, biases, bad habits, and pure chance) that had little to do with efficiency, and that they didn’t always work well, or predictably.34 The joint prize to the two men, one representing the past and the other the future, expresses as well as anything the existential crisis that has beset the economics profession.

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Its ascension eventually led another pair of Chicago-educated academics, Michael Jensen and William Meckling, to develop a management framework that would further reshape both business education and the corporate landscape: agency theory, or the notion that managers should be treated like owners, and paid in stock, to boost corporate performance. It’s a framework that is still front and center in MBA curriculums. Jensen and Meckling were, not surprisingly, disciples of Friedman and Eugene Fama. And ironically, given the damage it would do to any number of firms, their idea was a response to a growing worry, sparked in the 1970s, that American business actually wasn’t really all that healthy at its core. Despite the confidence of the “organization man” and the large, global enterprises that he ran, a series of events—from oil shocks to higher inflation to swift advances into manufacturing being made by emerging economies like China and India—made people fear that the United States was losing ground.

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THE FUTURE OF BUSINESS EDUCATION The sense of value, defined only as economic value without higher moral or social purpose, is what most enraged MIT Sloan School professor Andrew Lo when he began investigating the business model of the pharmaceutical industry. Fortunately, as a business school professor himself, he was in a position to do something about it. While most economists still uphold the efficient-market hypothesis, which posits that all available information is reflected in a stock’s price and that investors are rational, Lo believes that markets are less like rule-based physics and more like messy biological systems. In fact, he’s come up with an entirely new way of teaching finance—it’s called the adaptive-markets hypothesis.

Corporate Finance: Theory and Practice
by Pierre Vernimmen , Pascal Quiry , Maurizio Dallocchio , Yann le Fur and Antonio Salvi
Published 16 Oct 2017

At every moment, a financial instrument trades at a price determined by its return and its risk. Eugene Fama (1970) has developed the following three tests to determine whether a market is efficient: ability to predict prices; market response to specific events; impact of insider information on the market. In a weak-form efficient market, it is impossible to predict future returns. Existing prices already reflect all the information that can be gleaned from studying past prices and trading volumes. The efficient market hypothesis says that technical analysis has no practical value, nor do martingales (martingales in the ordinary, not the mathematical, sense).

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In the case of financial distress, banks are likely to organise the restructuring privately. This is often the case in Germany or in France, where bilateral relationships between banks and corporates are stronger than in the Anglo-Saxon world. Section 47.3 Bankruptcy and financial theory 1. The efficient markets hypothesis In the efficient markets hypothesis, bankruptcy is nothing more than a reallocation of assets and liabilities to more efficient companies. It should not have an impact on investor wealth, because investors all hold perfectly diversified portfolios. Bankruptcy, therefore, is simply a reallocation of the portfolio.

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There is consistent observation that stock prices perform better when the sun shines than when it rains. There again, although statistically significant, these anomalies are not material enough to generate arbitrage opportunities. There are some grounds to think that the efficient market theory is not valid. Nevertheless, Eugene Fama, one of the founders of this theory, defends it strongly. He calls into question the methodologies used to find anomalies (in particular for the overreaction of markets). Behavioural finance rejects the founding assumption of market efficiency: what if investors were not rational? It tries to build on other fields of social science to derive new conclusions.

The Wisdom of Finance: Discovering Humanity in the World of Risk and Return
by Mihir Desai
Published 22 May 2017

For a discussion of the rise of the alternative asset industry and its effect on Wall Street, see Desai, Mihir A. “The Incentive Bubble.” Harvard Business Review 90, no. 3 (March 2012): 123–29. For an excellent but rigorous overview of the state of play in asset pricing generally, see Campbell, John Y. “Empirical Asset Pricing: Eugene Fama, Lars Peter Hansen, and Robert Shiller.” Scandinavian Journal of Economics 116, no. 3 (2014): 593–634; and Cochrane, John H. Asset Pricing. Princeton, NJ: Princeton University Press, 2001. A slightly more accessible version of these ideas is provided in Cochrane, John H., and Christopher L. Culp.

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Second, there is the inability to identify cleanly which risks have been undertaken, creating ambiguity over what expected returns should have been. Finally, there is now plenty of evidence that indicates that few money managers consistently beat the market, after consideration of their fees. This last piece is what is known as the efficient markets hypothesis—it is very hard, if not impossible, to consistently beat the market. That hypothesis is much derided today because of the convulsions of the markets and because many professional investors have an interest in making people believe that it is untrue. And naïve formulations of efficient markets—all available information is in prices already—are surely untrue.

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“Efficient Capital Markets: A Review of Theory and Empirical Work.”Journal of Finance 25, no. 2 (May 1970): 383–417. In particular, Fama is generous with his referencing of earlier work, including that of Paul Samuelson, Bill Sharpe, Benoit Mandelbrot, Paul Cootner, Jack Treynor, and others. This lecture is an excellent source on the ideas of efficient markets: Fama, Eugene. “A Brief History of the Efficient Market Hypothesis.” Lecture, Masters of Finance. February 12, 2014. https://www.youtube.com/watch?v=NUkkRdEknjI. An alternative stream of important research on this topic was triggered by Grossman, Sanford J., and Joseph E. Stiglitz. “On the Impossibility of Informationally Efficient Markets.” American Economic Review 70, no. 3 (June 1980): 393–408.

Wall Street: How It Works And for Whom
by Doug Henwood
Published 30 Aug 1998

More generally, if the application of rational expectations theory to the virtually "ideal" conditions provided by the stock market fails, then what confidence can economists have in its application to other areas of economics...? (Marsh and Merton 1986, quoted in Fortune 1991). The answer to the confidence question, as we'll see, is not much. the view from 1970 Perhaps the easiest way to consider the vast literature on market efficiency is to focus on two reviews of the state of the art written by Eugene Fama of the University of Chicago, the first in 1970, when the theory was in high WALL STREET flower, and the second in 1991, when it had taken serious hits. Fama opened his canonical 1970 review of the efficient market theory'^ as follows: The primary" role of the capital market is allocation of ownership of the economy's capital stock.

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But obviously neither the product nor stock markets work as advertised. That means that capital is admitting that corporations must be subject to some kind of outside oversight. If that's the case, then the question becomes oversight by whom, in what form, and in whose interest. Few economists pay much attention to corporations, or how they're owned and run. As Eugene Fama (1991) noted, "many of the corporate-control studies appear in finance journals, but the work goes to the heart of issues in industrial organization, law and economics, and labor economics." He might have added politics and culture, since these too shape and are shaped by big business. Corporate governance is too important a matter to be left to finance theorists.

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Whether this is an accurate picture of the average human is open to question, but there's no question that capitalism as a system and economics as a discipline both reward people who conform to the model.^ After this overture, let's examine three of the most prominent theories that financial economists developed over the years — Tobin's q, the Modigliani-Miller theorem, and the efficient market hypothesis. The first is a theory of how finance influences the real world; the second, a vision of how finance is largely irrelevant to the real world; and the third, a deeply influential story about how markets are wondrous instruments of adjustment and allocation. Like all models, they tried to simplify the world in order to explain it.

Finding Alphas: A Quantitative Approach to Building Trading Strategies
by Igor Tulchinsky
Published 30 Sep 2019

Shaw & Co. 8 design 25–30 automated searches 111–120 backtesting 33–41 case study 31–41 core concepts 3–6 data inputs 4, 25–26, 43–47 evaluation 28–29 expressions 4 flow chart 41 future performance 29–30 horizons 4–50 intraday alphas 219–221 machine learning 121–126 noise reduction 26 optimization 29–30 prediction frequency 27 quality 5 risk-on/risk off alphas 246–247 robustness 89–93 smoothing 54–55, 59–60 triple-axis plan 83–88 universe 26 value 27–30 digital filters 127–128 digitization 7–9 dimensionality 129–132 disclosures 192 distressed assets 202–203 diversification automated searches 118–119 exchange-traded funds 233 portfolios 83–88, 108 DL see deep learning dot (inner) product 63–64 Dow, Charles 7 DPIN see dynamic measure of the probability of informed trading drawdowns 106–107 dual timestamping 78 dynamic measure of the probability of informed trading (DPIN) 214–215 dynamic parameterization 132 early-exercise premium 174 earnings calls 181, 187–188 earnings estimates 184–185 earnings surprises 185–186 efficiency, automated searches 111–113 Index295 efficient markets hypothesis (EMH) 11, 135 ego 19 elegance of models 75 EMH see efficient markets hypothesis emotions 19 ensemble methods 124–125 ensemble performance 117–118 estimation of risk 102–106 historical 103–106 position-based 102–103 shrinkage 131 ETFs see exchange-traded funds Euclidean space 64–66 evaluation 13–14, 28–29 backtesting 13–14, 33–41, 69–76 bias 77–82 bootstrapping 107 correlation 28–29 cutting losses 20–21 data selection 74–75 drawdowns 107 information ratio 28 margin 28 overfitting 72–75 risk 101–110 robustness 89–93 turnover 49–60 see also validation event-driven strategies 195–205 business cycle 196 capital structure arbitrage 204–205 distressed assets 202–203 index-rebalancing arbitrage 203–204 mergers 196–199 spin-offs, split-offs & carve-outs 200–202 exchange-traded funds (ETFs) 223–240 average daily trading volume 239 challenges 239–240 merits 232–233 momentum alphas 235–237 opportunities 235–238 research 231–240 risks 233–235 seasonality 237–238 see also index alphas exit costs 19, 21 expectedness of news 164 exponential moving averages 54 expressions, simple 4 extreme alpha values 104 extrinsic risk 101, 106, 108–109 factor risk heterogeneity 234 factors financial statements 147 to alphas 148 failure modes 84 fair disclosures 192 fair value of futures 223 Fama–French three-factor model 96 familiarity bias 81 feature extraction 130–131 filters 127–128 finance blogs 181–182 finance portals 180–181, 192 financial statement analysis 141–154 balance sheets 143 basics 142 cash flow statements 144– 145, 150–152 corporate governance 146 factors 147–148 fundamental analysis 149–154 growth 145–146 income statements 144 negative factors 146–147 special considerations 147 finite impulse response (FIR) filters 127–128 296Index FIR filters see finite impulse response filters Fisher Transform 91 five-day reversion alpha 55–59 Float Boost 125 forecasting behavioral economics 11–12 computer adoption 7–9 frequencies 27 horizons 49–50 statistical arbitrage 10–11 UnRule 17–21 see also predictions formation of the industry 8–9 formulation bias 80 forward-looking bias 72 forwards 241–249 checklist 243–244 Commitments of Traders report 244–245 instrument groupings 242–243 seasonality 245–246 underlying assets 241–242 frequencies 27 full text analysis 164 fundamental analysis 149–154 future performance 29–30 futures 241–249 checklist 243–244 Commitments of Traders report 244–245 fair value 223 instrument groupings 242–243 seasonality 245–246 underlying assets 241–242 fuzzy logic 126 General Electric 200 generalized correlation 64–66 groupings, futures and forwards 242–243 group momentum 157–158 growth analysis 145–146 habits, successful 265–271 hard neutralization 108 headlines 164 hedge fund betas see risk factors hedge funds, initial 8–9 hedging 108–109 herding 81–82, 190–191 high-pass filters 128 historical risk measures 103–106 horizons 49–50 horizontal mergers 197 Huber loss function 129 humps 54 hypotheses 4 ideas 85–86 identity matrices 65 IIR filters see infinite impulse response filters illiquidity premium 208–211 implementation core concepts 12–13 triple-axis plan 86–88 inaccuracy of models 10–11 income statements 144 index alphas 223–240 index changes 225–228 new entrants 227–228 principles 223–225 value distortion 228–230 see also exchange-traded funds index-rebalancing arbitrage 203–204 industry formation 8–9 industry-specific factors 188–190 infinite impulse response (IIR) filters 127–128 information ratio (IR) 28, 35–36, 74–75 initial hedge funds 8–9 inner product see dot product inputs, for design 25–26 integer effect 138 intermediate variables 115 Index297 intraday data 207–216 expected returns 211–215 illiquidity premium 208–211 market microstructures 208 probability of informed trading 213–215 intraday trading 217–222 alpha design 219–221 liquidity 218–219 vs. daily trading 218–219 intrinsic risk 102–103, 105–106, 109 invariance 89 inverse exchange-traded funds 234 IR see information ratio iterative searches 115 Jensen’s alpha 3 L1 norm 128–129 L2 norm 128–129 latency 46–47, 128, 155–156 lead-lag effects 158 length of testing 75 Level 1/2 tick data 46 leverage 14–15 leveraged exchange-traded funds 234 limiting methods 92–93 liquidity effect 96 intraday data 208–211 intraday trading 218–219 and spreads 51 literature, as a data source 44 look-ahead bias 78–79 lookback days, WebSim 257–258 looking back see backtesting Lo’s hypothesis 97 losses cutting 17–21, 109 drawdowns 106–107 loss functions 128–129 low-pass filters 128 M&A see mergers and acquisitions MAC clause see material adverse change clause MACD see moving average convergence-divergence machine learning 121–126 deep learning 125–126 ensemble methods 124–125 fuzzy logic 126 look-ahead bias 79 neural networks 124 statistical models 123 supervised/unsupervised 122 support vector machines (SVM) 122, 123–124 macroeconomic correlations 153 manual searches, pre-automation 119 margin 28 market commentary sites 181–182 market effects index changes 225–228 see also price changes market microstructure 207–216 expected returns 211–215 illiquidity premium 208–211 probability of informed trading 213–215 types of 208 material adverse change (MAC) clause 198–199 max drawdown 35 max stock weight, WebSim 257 mean-reversion rule 70 mean-squared error minimization 11 media 159–167 academic research 160 categorization 163 expectedness 164 finance information 181–182, 192 momentum 165 novelty 161–162 298Index sentiment 160–161 social 165–166 mergers and acquisitions (M&A) 196–199 models backtesting 69–76 elegance 75 inaccuracy of 10–11 see also algorithms; design; evaluation; machine learning; optimization momentum alphas 155–158, 165, 235–237 momentum effect 96 momentum-reversion 136–137 morning sunshine 46 moving average convergencedivergence (MACD) 136 multiple hypothesistesting 13, 20–21 narrow framing 81 natural gas reserves 246 negative factors, financial statements 146–147 neocognitron models 126 neural networks (NNs) 124 neutralization 108 WebSim 257 newly indexed companies 227–228 news 159–167 academic research 160 categories 163 expectedness 164 finance information 181–182, 192 momentum 165 novelty 161–162 relevance 162 sentiment 160–161 volatility 164–165 NNs see neural networks noise automated searches 113 differentiation 72–75 reduction 26 nonlinear transformations 64–66 normal distribution, approximation to 91 novelty of news 161–162 open interest 177–178 opportunities 14–15 optimization 29–30 automated searches 112, 115–116 loss functions 128–129 of parameter 131–132 options 169–178 concepts 169 open interest 177–178 popularity 170 trading volume 174–177 volatility skew 171–173 volatility spread 174 option to stock volume ratio (O/S) 174–177 order-driven markets 208 ordering methods 90–92 O/S see option to stock volume ratio outliers 13, 54, 92–93 out-of-sample testing 13, 74 overfitting 72–75 data mining 79–80 reduction 74–75, 269–270 overnight-0 alphas 219–221 overnight-1 alphas 219 parameter minimization 75 parameter optimization 131–132 PCA see principal component analysis Pearson correlation coefficients 62–64, 90 peer pressure 156 percent profitable days 35 performance parameters 85–86 Index299 PH see probability of heuristicdriven trading PIN see probability of informed trading PnL see profit and loss pools see portfolios Popper, Karl 17 popularity of options 170 portfolios correlation 61–62, 66 diversification 83–88, 108 position-based risk measures 102–103 positive bias 190 predictions 4 frequency 27 horizons 49–50 see also forecasting price changes analyst reports 190 behavioral economics 11–12 efficient markets hypothesis 11 expressions 4 index changes 225–228 news effects 159–167 relative 12–13, 26 price targets 184 price-volume strategies 135–139 pride 19 principal component analysis (PCA) 130–131 probability of heuristic-driven trading (PH) 214 probability of informed trading (PIN) 213–215 profit and loss (PnL) correlation 61–62 drawdowns 106–107 see also losses profit per dollar traded 35 programming languages 12 psychological factors see behavioral economics put-call parity relation 174 Python 12 quality 5 quantiles approximation 91 quintile distributions 104–105 quote-driven markets 208 random forest algorithm 124–125 random walks 11 ranking 90 RBM see restricted Boltzmann machine real estate investment trusts (REITs) 227 recommendations by analysts 182–183 recurrent neural networks (RNNs) 125 reduction of dimensionality 130–131 of noise 26 of overfitting 74–75, 269–270 of risk 108–109 Reg FD see Regulation Fair Disclosure region, WebSim 256 regions 85–86 regression models 10–11 regression problems 121 regularization 129 Regulation Fair Disclosure (Reg FD) 192 REITs see real estate investment trusts relationship models 26 relative prices 12–13, 26 relevance, of news 162 Renaissance Technologies 8 research 7–15 analyst reports 179–193 automated searches 111–120 backtesting 13–14 300Index behavioral economics 11–12 computer adoption 7–9 evaluation 13–14 exchange-traded funds 231–240 implementation 12–13 intraday data 207–216 machine learning 121–126 opportunities 14–15 perspectives 7–15 statistical arbitrage 10–11 triple-axis plan 83–88 restricted Boltzmann machine (RBM) 125 Reuleaux triangle 70 reversion alphas, five-day 55–59 risk 101–110 arbitrage 196–199 control 108–109 drawdowns 106–107 estimation 102–106 extrinsic 101, 106, 108–109 intrinsic 102–103, 105–106, 109 risk factors 26, 95–100 risk-on/risk off alphas 246–247 risk-reward matrix 267–268 RNNs see recurrent neural networks robustness 89–93, 103–106 rules 17–18 evaluation 20–21 see also algorithms; UnRule Russell 2000 IWM fund 225–226 SAD see seasonal affective disorder scale of automated searches 111–113 search engines, analyst reports 180–181 search spaces, automated searches 114–116 seasonality exchange-traded funds 237–238 futures and forwards 245–246 momentum strategies 157 and sunshine 46 selection bias 77–79, 117–118 sell-side analysts 179–180 see also analyst reports sensitivity tests 119 sentiment analysis 160–161, 188 shareholder’s equity 151 Sharpe ratios 71, 73, 74–75, 221, 260 annualized 97 Shaw, David 8 shrinkage estimators 131 signals analysts report 190, 191–192 cutting losses 20–21 data sources 25–26 definition 73 earnings calls 187–188 expressions 4 noise reduction 26, 72–75 options trading volume 174–177 smoothing 54–55, 59–60 volatility skew 171–173 volatility spread 174 sign correlation 65 significance tests 119 Simons, James 8 simple moving averages 55 simulation backtesting 71–72 WebSim settings 256–258 see also backtesting size factor 96 smoothing 54–55, 59–60 social media 165–166 sources of data 25–26, 43–44, 74–75 automated searches 113–114 see also data sparse principal component analysis (sPCA) 131 Spearman’s rank correlation 90 Index301 special considerations, financial statements 147 spin-offs 200–202 split-offs 200–202 spreads and liquidity 51 and volatility 51–52 stat arb see statistical arbitrage statistical arbitrage (stat arb) 10–11, 69–70 statistical models, machine learning 123 step-by-step construction 5, 41 storage costs 247–248 storytelling 80 subjectivity 17 sunshine 46 supervised machine learning 122 support vector machines (SVM) 122, 123–124 systemic bias 77–80 TAP see triple-axis plan tax efficiency, exchange-traded funds 233 teams 270–271 temporal-based correlation 63–64, 65 theory-fitting 80 thought processes of analysts 186–187 tick data 46 timestamping and bias 78–79 tracking errors 233–234 trades cost of 50–52 crossing effect 52–53 latency 46–47 trend following 18 trimming 92 triple-axis plan (TAP) 83–88 concepts 83–86 implementation 86–88 tuning of turnover 59–60 see also smoothing turnover 49–60 backtesting 35 control 53–55, 59–60 costs 50–52 crossing 52–53 examples 55–59 horizons 49–50 smoothing 54–55, 59–60 WebSim 260 uncertainty 17–18 underlying principles 72–73 changes in 109 understanding data 46 unexpected news 164 universes 26, 85–86, 239–240, 256 UnRule 17–18, 20–21 unsupervised machine learning 122 validation, data 45–46 valuation methodologies 189 value of alphas 27–30 value distortion, indices 228–230 value factors 96 value investing 96, 141 variance and bias 129–130 vendors as a data source 44 vertical mergers 197 volatility and news 164–165 and spreads 51–52 volatility skew 171–173 volatility spread 174 volume of options trading 174–177 price-volume strategies 135–139 volume-synchronized probability of informed trading (VPIN) 215 302Index VPIN see volume-synchronized probability of informed trading weather effects 46 WebSim 253–261 analysis 258–260 backtesting 33–41 data types 255 example 260–261 settings 256–258 weekly goals 266–267 weighted moving averages 55 Winsorization 92–93 Yahoo finance 180 Z-scoring 92 

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For example, the work of financial economists on the capital asset pricing model (the CAPM, which aims to decompose a stock’s return into its market component and an idiosyncratic component) and its derivatives has spawned an enormous, multidecade-long search to prove and/or disprove its validity, and to enhance its explanatory power with additional factors. The initial research on the CAPM was published in the 1960s (e.g. William Sharpe’s 1964 article, “Capital Asset Prices: A Theory of Market Equilibrium under Conditions of Risk”), and the debate continued into the 1990s (e.g. Eugene Fama and Kenneth French, “The Cross-Section of Expected Stock Returns”). A 2018 scan of The Journal of Finance found at least one entry on the subject of factor pricing (“Interpreting Factor Models,” by Serhiy Kozak, Stefan Nagel, and Shrihari Santosh). But models from academia, even when they provide a foundation for applied research, are often incomplete or based on assumptions that are inconsistent with the real markets in which traders operate.

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In fact, the academic literature in financial economics has tackled this problem exhaustively, qualifying the markets and the nature of information and how it affects prices, and deriving conclusions based on various assumptions about the markets, about market participants and their level of rationality, and how the participants interact and process information. The term “efficient market hypothesis” (EMH) is sometimes used to describe the theory that says market prices reflect all available information. The EMH gained prominence in the 1960s, and empirical studies of prices and of asset manager performance since then have lent credence to the idea that the market is efficient enough to make it impossible to determine whether top asset managers’ performance is due to anything but luck.

Models. Behaving. Badly.: Why Confusing Illusion With Reality Can Lead to Disaster, on Wall Street and in Life
by Emanuel Derman
Published 13 Oct 2011

Others rely on technical analysis, a combination of rational and magical thinking that involves spotting the repetition of patterns in the trajectory of stock prices. None of these models works well consistently. Jujitsu Finance It’s a fact, then, that no one is very good at predicting stock prices. Faced with this failure, a school of academics associated with Eugene Fama at the University of Chicago in the 1960s developed what has become known as the Efficient Market Hypothesis, which I prefer to call the Efficient Market Model (EMM), since it’s a model of a hypothetical world rather than a correct hypothesis about the one we inhabit. I was a persevering student of physics when the EMM became popular, though I knew nothing of it.

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De Morgan, Augustus debt markets debt securities deduction Deleuze, Gilles deliciousness: analogy with risk democracy derivative emotions derivatives, financial Derman, Chaim (father) Derman, Emanuel: childhood and youth of education of in England eyesight of four questions of graduate education of moth in refrigerator example and professional background of quantum dream of Derman, Joshua (son) Derman, Sonia (mother) Derman, Sonya (daughter) Descartes, René desires: definition of disappointment and freedom and money and Spinoza’s emotions theory and will and desperation: love and devotion; Spinoza’s emotions theory and diagrams, Feynman diffusion Dirac Equation: analogies and bare and dressed electrons and Dirac wave function and as explanation of reality idea of electrons and impact on physics of intuition and knowledge and matter and metaphors and nature of models and nature of theories and positrons and quantum electrodynamics and Standard Model and as successful theory Dirac, Paul Dirac sea distance: measurement of divergences: electromagnetic theory and diversification domino computer dressed electrons drift Du Fay, Charles “Ducks Ditty” (song) Dyson, Freeman Earth: as magnet earthquakes: probability of economic models See also financial models; specific model Eddington, A. S. Efficient Market Hypothesis. See Efficient Market Model Efficient Market Model (EMM): accuracy of as assumption about human behavior assumptions of Black-Scholes Model and CAPM as extension of as cause of financial crisis conceptual mismatches in development of function of futility of using financial models and hypothesis of ideology and ignoring of complexity by invalidation of results of Law of One Price and as metaphor popularity of price and QED and risk and return in Sharpe Ratio and Spinoza’s emotions theory and stock market crash and as theory or model uncertainty and value and volatility and efficient markets: definition of Einstein, Albert: as bird as Derman role model diffusion model and and Dirac’s work and intuition as making the unconscious conscious on Maxwell and models as gedankenexperiments quanta and relativity theory of electric generator, first electricity See also electromagnetic theory electrochemistry: discovery of electrodynamics: Maxwell’s laws of electromagnetic theory: absolutes and accuracy of Ampère’s contributions to analogies and confirmation of curls and divergences and EMM and Faraday’s contributions to field and function of history of intuition and light and Maxwell’s contributions to and Maxwell’s views about Ampère as metaphor phenomena and as predictor qualities of quantitative laws and Standard model and as success trajectory of discoveries of as triumph of mental over physical waves and electromagnetism.

Smart Money: How High-Stakes Financial Innovation Is Reshaping Our WorldÑFor the Better
by Andrew Palmer
Published 13 Apr 2015

And to drum up interest, he and others have formulated a provocative question: “Can financial engineering cure cancer?”2 Lo is not an ivory-tower zealot. Well before the financial crisis, he was struck by the failure of the “efficient-market hypothesis” to grapple with the basics of human behavior. The essence of the efficient-markets hypothesis, which was formulated in 1970 by a University of Chicago economist named Eugene Fama, who shared the 2013 Nobel Prize for Economics, is that markets are rational. The hypothesis posits that market prices incorporate all the publicly available information on a given security and that people respond rationally to this information.

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The desire to make simplifying assumptions is understandable in finance—“Can you imagine how hard physics would be if electrons had feelings?” is the question Richard Feynman, a physicist, once asked—but this one takes the cake. Humans are not always rational, and markets are swayed by sentiment as much as logic. Instead of the efficient-market hypothesis, Lo champions something called the “adaptive-market hypothesis,” which takes the world as it is rather than as it should be. The AMH accepts that some market behavior is hardwired. Our brains have been programmed by evolution to respond to emotions such as fear and greed. Financial markets are the perfect playground for these emotions, a theater that is dedicated to volatility and risk, to losing and winning.

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See Credit-default swap Cecchetti, Stephen, 79 Church-tower principle, 207 Cigarettes, as means of payment, 5 Clark, Geoffrey Wilson, 144 Clearinghouse, 39 ClearStreet, 210 Clinical drug trials, indemnification of, xii–xiii Coates, John, 116 Code, simplification of, 63 Cohen, Ronald, 91–95, 97, 106, 108, 112 Coins, history of, 4 Collateral, xiv, 7, 38, 65, 76, 150, 177, 185, 204–206, 215 Collateralized-debt obligations (CDOs), 43, 234–235 Collective Health, 104 College graduates, earning power of, 170–171 Commenda, 7–8, 19 Commercial paper, 185 Commodity Futures Trading Commission, 54 CommonBond, 182, 184, 197 Confusion de Confusiónes (de la Vega), 24 Congressional Budget Office, 99, 169 Consumer Financial Protection Bureau overdraft fees and prepaid cards, concern about, 203–204 report on reverse mortgages, 141 survey on payday borrowing, 200 CoRI, 132 Corporate debt, in United States, 120 Corporate finance, 237–238 Correlation risk, 165 Cortisol and testosterone, effect of on risk appetite and aversion, 116 Counterparty risk, 22 Credit, industrialization of, 206 Credit Card Accountability, Responsibility, and Disclosure (Credit CARD) Act of 2009, 203 Credit cards, 203 Credit-default swap (CDS), 37, 64–65, 75, 124, 169, 238 Credit ratings, 24, 120–121, 233–236 Credit-reporting firms, 24 Credit risk, 200, 201, 237, 238 Credit scores, 47–49, 201, 216–217 Creditworthiness, xiv, 10, 12, 47, 121, 197, 202, 204, 216 Crowdcube, 152–155, 158–159, 162 Damelin, Errol, 208 Dark Ages, banking in, 11 Dark pools, 60 DCs (defined-contribution schemes), 129, 131 DE Shaw, 163 Debit cards, 204 Debt, 6, 7, 70, 149, 164 Decumulation, 138–139 Defined-benefit schemes, 129, 131 Defined-contribution (DC) schemes, 129, 131 Dependent variable, 201 Deposit insurance, 13, 43–44 Derivatives, 3, 9–10, 29–32, 38, 40 Desai, Samir, 189 Development-impact bonds, 103 Diabetes, cost of in United States, 102 Dimensional Fund Advisors, 129 Direct lending, 184 Discounting, 19 Disposition effect, 25 Diversification, 8, 12, 20, 117–119, 196, 236 Doorways to Dreams (D2D), 213–214 Dot-com boom, 148 Dow Jones Industrial Average, 40 Dow Jones Transportation Average, 40 Drug development, investment in, vii-viii, 114–115 Drug-development megafund adaptive market hypothesis and, 115–117 Alzheimer’s disease, 122 credit rating, importance of, 120–121 diversification and, 117, 119–120, 122 drug research, improvement of economics of, 114–115 financial engineering, need for, 119 guarantors for, 121 orphan diseases and, 118–119, 122 reactions to, 118 securitization and, 117–119, 122 Dumb money, comparison of to smart money, 155–158 Dun and Bradstreet, 24 Durbin Amendment (2010), 204 Dutch East India Company (VOC), 14–15, 38 E-Mini contracts, 54–55 Eaglewood Capital, 183–184 Ebola outbreak (2014), mortality rate of, 230 Ebrahimi, Rod, 210–211 Ecology, finance and, 113 Economist 2013 conference, xv on railways, 25 on worth of residential property, 70 Educational equity adverse selection in, 174, 175, 182 CareerConcept, 166 differences in funding rates, 176 enforceability, 177 in Germany, 166 Gu, Paul, 172, 175–176 income-share legislation, US Senate and, 172 information asymmetry, 174 Lumni, 165, 168, 175 Oregon, interest in income-share agreements, 172, 176 Pave, 166–168, 173, 175, 182 peer-to-peer insurance, 182 problems with, 167–168, 173–174 providers and recipients, contact between, 160, 175 risk-based pricing model, 176 student loans, 169–171 Upstart, 166–168, 173, 175, 182 Yale University and, 165 Efficient-market hypothesis, 115 Endogeneity, 239 Epidemiology, finance and, 113 Eqecat, 222 Equity, 7–8, 149–150, 186–187 Equity-crowdfunding in Britain, 154 Crowdcube, 152–155, 158–159, 162 Friendsurance, 182–183 Equity-crowdfunding in Britain (continued) herding, 159–160 social insurance, 182–183 Equity-derivatives contracts, 29 Equity-sharing, 7–8 Equity-to-assets ratio, 186 Eren, Selcuk, 73 Eroom’s law, 114 Essex County Council, 95 Eurobond market, 32 European Bank for Reconstruction and Development, 169 Exceedance-probability curve, 231–232, 232 figure 3 Exxon, 169 Facebook, 174 Fair, Bill, 47 False substitutes, 44 Fama, Eugene, 115 Fannie Mae, 48, 78, 85, 168 Farmer, Doyne, 60, 63 Farynor, Thomas, 16 FCIC (Financial Crisis Inquiry Commission), 50 Federal Deposit Insurance Corporation (FDIC), 186, 200 Federal Reserve Bank of New York, 170, 204, 205 Feynman, Richard, 115 Fibonacci (Leonardo of Pisa), 19 FICO score, 47–49 Films to rent, study of hyperbolic discounting, 133–134 Finance bailouts, 35–36 banks, purpose of, 11–14 collective-action problem in, 62 computerization of, 31–32 democratization of, 26–28 economic growth and, 33–34 fresh ideas, need for, xviii, 38–39, 80, 85–86 globalization and, 30, 225 heuristics, use of in, 45–50 illiteracy, financial, 134–135 importance of, 10 information, importance of, 10–11 inherent failings in, 241 misconceptions about, xiii–xvi panic, consequences of, 44 regulatory activity, results of, 33 risk assessment, 24, 45, 77–78 risk management, 55, 117–118, 123 as solution to real-world problems, 114 standardization, 39–41, 45, 47, 51 unconfirmed trades, backlog of, 64–65 use of catastrophe risk modeling in, 233–239 See also High-frequency trading (HFT); Internet Finance, history of bank, derivation of word, 12 Book of Calculation (Fibonacci), 19 call options, 10 Code of Hammurabi, 8 coins, 4 commodity forms of exchange, 4–5 credit and debt, 5–7 in Dark Ages, 11 democratization, 26–28 deposits, 6 derivatives, 29–32, 38 Dutch East India Company (VOC), 14–15, 38 early financial contracts, 5 early forms of finance, 3 equity contracts, 7–8 fire insurance, 16–17 first futures market, 29, 39–40 forward contracts, 38 in Greece, 11 industrialization and, 3, 27–28 inflation-protected bonds, 26 insurance, 8–10, 16–17, 20–22 interest, origin of, 5 in Italy, 9, 14 life annuities, 20–22 maritime trade and, 7–8, 14, 17, 23 payment, forms of, 4–5 put options, 9–10 railways, effect of on, 23–25 in Roman Empire, 7, 8, 11, 36 securities markets, 14 stock exchanges, 14, 24–25 Finance, innovation in absence of, xvi–xvii credit and debt, 5–7 derivatives, 9–10, 29–32 diffusion, pattern of, 45 drivers of, 22–26 equity, 7–8 importance of, 66, 242–243 insurance, 8–9, 16–17, 20–22 lessons from, 32–34 mathematical insights, 18–20 payment, forms of, 4–5 risks of, 145 stock exchanges, 14–16 Finance and the Good Society (Shiller), 242 Financial Crisis Inquiry Commission (FCIC), 50 Financial crisis of 2007–2008 causes of, xv, 34, 69 effects of, xx–xi future of finance, effect on, 243 mortgage debt, role of in, 69–70 new regulations since, 185, 187 Financial Times, quote from Chuck Prince in, 62 Fire insurance, early, 16–17 Fitch Ratings, 24 Flash Boys (Lewis), 57 Flash crash, 54–56, 63 Florida, hurricane damage in, 223, 225 Florida, new residents per day in, 225 Foenus nauticum, 8 Forward contracts, 38 Forward transactions, 15 France collapse of Mississippi scheme in, 36 eighteenth century life annuities in, 20–21 government spending in, 99 Freddie Mac, 48, 85 Fresno, California, social-impact bond pilot program in, 103–104 Friedman, Milton, 165 Friendsurance, 182–183 Fundamental sellers, 54–55 Funding Circle, 181–182, 189, 197 Futures, 29, 39–40 Galton Board, 17, 18 figure 1 Gaussian copula, 235 Geithner, Timothy, 64–65 Genentech, xii General Motors, bailout of, xi Geneva, Switzerland, annuity pools in, 21–22 Gennaioli, Nicola, 42, 44 Ginnie Mae, 168 Girouard, Dave, 166 Glaeser, Edward, 74 Globalization, finance and, 30, 225 Goldman Sachs, 61, 98, 156, 235 Google Trends, 218 Gorlin, Marc, 218 Government spending, rise in, 99–100 Governments, support for new financial products by, 168–169 Grameen Bank, 203 Greece, forerunners of banks in, 11 Greenspan, Alan, 236 Greenspan consensus, 236 Grillo, Baliano, 9 Gu, Paul, 162–164, 166, 172, 175–176 Guardian Maritime, 151 Haldane, Andy, 188 Halley, Edmund, 19–20 Hamilton, Alexander, 35–36 Hammurabi, Code of, 5, 8 Health conditions, SIB early detection programs for, 102–104 Health-impact bonds, 103–104 Hedge funds, 123, 158, 183 Hedging, 30–31, 54, 124, 129, 131, 156, 206, 227 Heiland, Frank, 73 Herding, 24, 159–160 Herengracht Canal properties, Amsterdam, real price level for, 74 Heuristics, 45–50 HFRX, 157–158 High-frequency trading (HFT) benefits of, 58 code, simplification of, 63 flash crash, 54–56 latency, attempts to lower, 53 pre-HFT era, 59–61 problems with, 56–58, 62–63 Hinrikus, Taavet, 190–191 HIV infection rates, SIB program for reduction of, 103 Holland, tulipmania in, 33, 36 Home equity, 139–140 Home-ownership rates, in United States, 85, 170 Homeless people, SIB program for, 96–97 Housing boom of mid-2000s, 148–149 Human capital contracts, 165, 167, 173–174, 176, 177 defined, 6 as illiquid asset, 177 Hurricane Andrew, effect of on insurers, 223–224, 225 Hurricane Hugo, 223 Hyperbolic discounting, 133–134, 211 IBM, 169 If You Don’t Let Us Dream, We Won’t Let You Sleep (drama), 111 IMF (International Monetary Fund), 125–126 Impact investing, 92 Implied volatility, 116 Impure altruism, 109–110 Income-share agreements, 167, 172–178 Independent variables, 201 Index funds, 40 India, CDS deals in, 37 India, social-impact bonds (SIBs) in, 103 Industrialization, effect of on finance, 3, 27–28 Inflation-protected Treasury bills, 131 Information asymmetry, 174 Innovator’s dilemma, 189 Instiglio, 103 Insurance, 8–10, 16–17, 142, 223–225 Insurance-linked securities, 222 Interbank markets, x Interest, origin of, 5 Interest-rate swaps, 29 International Maritime Bureau Piracy Reporting Centre, 151 International Monetary Fund (IMF), 125–126 International Swaps and Derivatives Association (ISDA), 40 Internet, role of in finance creditworthiness, determination of, 172–173, 202, 218 direct connection of suppliers and consumers, xviii, 32 equity crowdfunding, 152–155 income-share agreements, 172–173 ROSCAs, 210 small business loans, 216 speed and ease of borrowing, 189 student loans, 166–167 Intertemporal exchange, 6 Intuit, 218 Investment grade securities, 121 Ireland, banking crisis in, xiv–xv, 69 Isaac, Earl, 47 ISDA (International Swaps and Derivatives Association), 40 ISDA master agreement, 40 Israel, SIBs in, 97 Italy discrimination against female borrowers in, 208 financial liberalization and, 34 first securities markets in, 14 maritime trade partnerships in, 7–8 J.

A Little History of Economics
by Niall Kishtainy
Published 15 Jan 2017

On another it takes thirty-two minutes because an accident slowed the traffic down. When you’re a little off, it’s because of random factors that affect the speed of the traffic. On average your prediction of a thirty-minute journey time is a good one. One of the first to apply Muth’s idea was the economist Eugene Fama (b. 1939). He wondered what rational expectations implied for how financial markets worked. The financial system’s banks and stock exchanges channel money from savers to borrowers. A saver wants to put £300 into a bank account and withdraw it after six months. A corporation wants to borrow those savings, but needs a loan of £10 million to dig a mine which it will repay in five years.

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It would be impossible for you or me to consistently beat the market by trying to guess next week’s movement in a share price. Unfortunately for us, the price of Nifty Wrap’s shares will already have jumped up to take account of the new aerosol wrapping paper. Fama’s theory is called the ‘efficient markets hypothesis’. It says that the prices in financial markets reflect all available information. When all information is factored into share prices then investors have exploited all profit opportunities. This doesn’t mean that prices don’t change – far from it. What it means is that you won’t be able to predict them.

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It revived ideas that Keynes had fought against, those of the classical school which had said that the economy would always quickly adjust to eliminate unemployment and that there was no point in the government trying to boost it further. The new classical economics is controversial. Were the millions of unemployed workers during the Great Depression in the 1930s or the recessions since out of work voluntarily? Do markets really adjust so quickly? Many doubt it. The efficient markets hypothesis, too, has been questioned. Are people really able to quickly gather and understand vast amounts of economic information, so that there are no unexploited profit opportunities in financial markets? Here, some refer to the story of the student and the economics professor, a believer in rational expectations theory, who are walking together to class.

Barometer of Fear: An Insider's Account of Rogue Trading and the Greatest Banking Scandal in History
by Alexis Stenfors
Published 14 May 2017

If traders do not behave rationally, other traders immediately spot this and exploit the opportunity provided by a mispricing in the market. Furthermore, the irrational traders lose more and more money, so they either stop trading or are sacked. The market is left with the rational, emotionless traders who ensure that the FX market remains hyper-efficient. This is the logic of the so-called efficient market hypothesis, developed by professor and Nobel laureate Eugene Fama. For decades, it has been part of the core curriculum at business schools and in economics faculties around the world. It is one of the theories in finance that truly has had a major impact – from students learning the basics of how financial markets work to policy makers and regulators assessing how markets can be made more efficient.

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I remember being perplexed by his explanation. Although I understood how important religious and cultural rituals were (even to traders), I had never come across someone admitting to something so irrelevant being of relevance to their trading strategy. Professors in behavioural finance have long argued that the efficient market hypothesis makes unrealistic assumptions about human behaviour. In short, they argue that there is no room to account for psychology in the most influential theory on how traders should behave. In the real world, people are not always rational. Moreover, people tend to be irrational over and over again, and in similar ways.

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Academics and experts in behavioural finance emphasise that investors and traders should be aware of their own – and others’ – psychological biases and take them into account when trading. This makes perfect sense. The financial markets consist of human beings (or, increasingly, computer algorithms programmed by human beings), and human beings do not always behave rationally. However, even though this contradicts the efficient market hypothesis, proponents of the two different schools have one thing in common. Both tend to assume that traders act as market takers (approaching a market, which somehow already exists) rather than as market makers (creating that market). In other words, traders are seen as patients who either are rational or can learn to become more rational by visiting a therapist.

Investing Amid Low Expected Returns: Making the Most When Markets Offer the Least
by Antti Ilmanen
Published 24 Feb 2022

There are many candidate theories from each camp for any premium (the key ones were referenced earlier), and data does not easily allow us to determine which theories matter more. Academic debates have been going on for decades. As a testimony to the importance of these debates, Eugene Fama, the father of the efficient market hypothesis, and Robert Shiller, arguably its most ardent critic, shared the 2013 Nobel Prize in Economics.1 Some observers consider only risk-based explanations sustainable, claiming that arbitrage forces and investor learning will quickly eliminate any behavioral anomalies. The counterargument is that limits of arbitrage and slow learning can sustain behavioral anomalies for long periods after the opportunity has been identified.

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As with the previous equations, FLAM's beauty is in the broad strategic insights it gives, not in being precisely right (as it too involves simplifying assumptions). The history of FLAM is worth sharing. The main portfolio algebra relations had been mapped in the 1960s and 1970s by the pioneers in academic finance (such as Eugene Fama and Richard Roll). Yet they were not widely used among investment practitioners until Richard Grinold made many key insights lucid and applicable for active investment managers. Grinold (1989) introduced the concept of FLAM in an eponymous article, together with “information ratio” (IR, the risk-adjusted active return).10 Grinold and Kahn's (1999) great book Active Portfolio Management developed both concepts further.

More Than You Know: Finding Financial Wisdom in Unconventional Places (Updated and Expanded)
by Michael J. Mauboussin
Published 1 Jan 2006

EXHIBIT 21.1 Clockspeeds in Sample Industries IndustryProduct ClockspeedProcess Clockspeed Fast-Clockspeed Industries Personal computers < 6 months 2-4 years Toys and games < 1 year 5-15 years Semiconductors 1-2 years 3-10 years Cosmetics 2-3 years 10-20 years Medium-Clockspeed Industries Automobiles 4-6 years 10-15 years Fast food 3-8 years 5-25 years Machine tools 6-10 years 10-15 years Pharmaceuticals 7-15 years 5-10 years Slow-Clockspeed Industries Commercial aircraft 10-20 years 20-30 years Tobacco 1-2 years 20-30 years Petrochemicals 10-20 years 20-40 years Paper 10-20 years 20-40 years Source: Fine, Clockspeed, 239. Reproduced with permission. That average clockspeeds are shortening does not mean that all sectors are changing equally rapidly. One of the factors underlying the average change is a shift in the composition of public companies. Eugene Fama and Kenneth French show that the number of companies in the Compustat database rose 70 percent between the mid-1970s and the mid-1990s. Most of the new companies, launched via initial public offerings, were smaller and faster growing than the existing companies.4 Since more fast-clockspeed companies have been added to the market mix over the past twenty-five years or so, the average clockspeed has shrunk.

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Behavioral-finance enthusiasts often fail to distinguish between the individual and the collective. Mug’s Game? Behavioral-finance experts understand the role of diversity in price formation. As Andrei Shleifer writes in his excellent book Inefficient Markets: An Introduction to Behavioral Finance:The efficient market hypothesis does not live or die by investor rationality. In many scenarios where some investors are not fully rational, markets are still predicted to be efficient. In one commonly discussed case, the irrational investors in the market trade randomly. When there are a large number of such investors, and when their trading strategies are uncorrelated, their trades are likely to cancel each other out.

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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. Investing—Profession or Business? 1 Burton G. Malkiel, “The Efficient Market Hypothesis and Its Critics,” Journal of Economic Perspectives 17, no. 1 (Winter 2003): 78. This is not a new finding. See also Burton G. Malkiel, “Returns from Investing in Equity Mutual Funds, 1971-1991,” Journal of Finance 50, no. 2 (June 1995): 549-72; Michael C. Jensen, “The Performance of Mutual Funds in the Period 1945-1964,” Journal of Finance 23 (1968): 389-416. 2 Special thanks to Gary Mishuris for creating the initial list and prompting this line of inquiry. 3 Jack Bogle, using John Maynard Keynes’s terminology, contrasts speculation (“forecasting the psychology of the market”) with enterprise (“forecasting the prospective yield of an asset”).

Damsel in Distressed: My Life in the Golden Age of Hedge Funds
by Dominique Mielle
Published 6 Sep 2021

Hedge funds that were already big ships were on their way to becoming supertankers. But this growth explosion had grave consequences for liquidity and flexibility. The two original sources of hedge fund competitive “edges” mostly went out the window. The Efficient Market Hypothesis, a cornerstone of modern finance usually associated with a paper by Eugene Fama and Paul Samuelson in 1970, proposes that asset prices fully reflect available information and that, as a result, consistently beating the market is impossible. An important assumption here is that liquidity is perfect, that there always are willing buyers and sellers.

Broke: How to Survive the Middle Class Crisis
by David Boyle
Published 15 Jan 2014

These were the days when the economic doctrine known as the Efficient Market Hypothesis was taking hold. Promulgated by the Chicago economist Eugene Fama and his colleagues in 1970, it suggested that market prices were always right. They took all the available information and computed the correct price. The Hypothesis lay behind the extraordinary growth in financial trading since then, and it remains the justification for the vast rewards of the traders. They are paid so well, or so they say, because they are efficiently producing accurate prices. But there was a peculiar contradiction about the Efficient Market Hypothesis: it meant that there could not be any price anomalies for traders to exploit for a bargain.

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What he found was that the price of stocks tend to overshoot. They carry on going up beyond what ought to be the top of the market, just as momentum tends to take them down further than they should go at the bottom. Here was a potential key to unlock the puzzle, and it was the central flaw to the Efficient Market Hypothesis on which everything else was based. It also provides a small part of the explanation for everything else that has gone wrong with the City of London, set out so graphically by the governor of the Bank of England, Mervyn King, in 2011. Governors of the Bank of England are not usually in the habit of giving interviews.

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It ridiculed their moral sense and their sense of responsibility. Unleashing the City — the knock-on effects of the event known as Big Bang — may have systematically destroyed the very values of the middle class it was supposed to support, leaving their future in doubt. The idea that the Efficient Market Hypothesis was wrong was not exactly new when Paul Woolley began to worry away at it. The billionaire financier George Soros pointed out that markets don’t actually have full information. There was also the idea, known as the Grossman-Stiglitz Paradox: that if all the relevant information was reflected in market prices, then no single agent would have enough incentive to get the information which prices are based on.

Eat People: And Other Unapologetic Rules for Game-Changing Entrepreneurs
by Andy Kessler
Published 1 Feb 2011

When it’s at its most efficient, with buyers and sellers neatly matched up at the right price, it’s a pretty good predictor. When it’s not, chaos is sure to follow. In effect, the stock market is doing price discovery as well as a game of hot potato, getting stocks into the correct hands with the right risk profile. Eugene Fama, a University of Chicago business school professor, proposed an efficient-market hypothesis back in 1969. Fama suggested that a market in which prices always “fully reflect” available information is called “efficient.” Fama believed that a market that is liquid enough (lots of buyers and sellers meeting in the market and sharing price information) and that can be arbitraged easily (someone can quickly take advantage of price differentials by buying or selling) will be efficient enough so that any information and investor expectations will be quickly reflected in securities prices.

Value Investing: From Graham to Buffett and Beyond
by Bruce C. N. Greenwald , Judd Kahn , Paul D. Sonkin and Michael van Biema
Published 26 Jan 2004

Benjamin Graham: The Memoirs of the Dean of Wall Street (New York: McGraw-Hill, 1996) edited and with an introduction by Seymour Chatman. Janet C. Lowe, Benjamin Graham on Value Investing: Lessons from the Dean of Wall Street (Chicago: Dearborn Financial, 1994). Chapter One Two major papers by Eugene Fama and Kenneth French: Eugene F Fama and Kenneth R. French, "The Cross-Section of Expected Stock Returns," Journal of Finance, XLVII:2, June 1992, 427-465, and Fama and French, "Size and Book-to-Market Factors in Earnings and Returns," Journal of Finance, March 1995, 131-155. Other studies confirming and expanding the Fama-French findings are summarized and described in a pamphlet produced by Tweedy, Browne Company, L.P., 52 Vanderbilt Avenue, New York, NY 10017: "What Has Worked in Investing: Studies of Investment Approaches and Characteristics Associated with Exceptional Returns."

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Once investors know that cheap stocks outperform expensive stocks, they should bid up the price of the cheap stocks and eliminate the superior performance. That the differential has persisted is what makes it an anomaly. There have been two distinct responses to the evidence that cheap stocks provide superior performance. One seeks to explain it, the other to explain it away. We will start with the latter. Essentially a defense of the efficient market hypothesis, the argument is that the superior performance occurs only because the value portfolios bear more risk than do expensive portfolios or the market as a whole. Because the theory holds that additional risk should indeed produce extra returns, the anomaly dissolves once risk is taken into account; superior performance is explained away.

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Because, as the theory holds, it is possible to diversify away the risks of holding only one or a few securities, investors will not be rewarded for those risks that they assume in running narrow portfolios. The only risk that does earn a com mensurate reward is the risk of volatility, or the risk that the diversified portfolio will move up and down at a greater rate than some even more broadly diversified benchmark, like the Standard & Poor's 500 index or the Wilshire 5000. The efficient market hypothesis-the idea that the market always incorporates the best estimate of the true value of a security-is embedded in this conception of risk and diversification; otherwise it might be possible for a clever investor to pick relatively few securities and be rewarded for these selections. Value investors reject both parts of the theory.

Adam Smith: Father of Economics
by Jesse Norman
Published 30 Jun 2018

It follows that the intelligent investor, in the title of Graham’s famous book, must have some independent and more fundamental way to assess long-term value, as well as the patience to wait till Mr Market is foolish enough to offer them an opportunity, and the financial wherewithal to grab it. THE EFFICIENT MARKET HYPOTHESIS But there is another view of markets, which is often contrasted with the Graham–Buffett view. This is the so-called Efficient Market Hypothesis. It does not date from the dawn of political economy; rather, it was first developed by Eugene Fama, an economist at the University of Chicago, in the late 1960s. It comes in different varieties: strong, semi-strong and weak. But at their heart these varieties all have two key ideas: what the behavioural economist Richard Thaler has aptly called ‘The Price is Right’ and ‘No Free Lunch’.

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According to the Efficient Market Hypothesis, financial asset prices are always right. It follows from this that there can be no such thing as an asset price bubble or market overshoot: since asset prices always reflect fundamental value, rapidly inflating asset prices can only reflect rising expectations of future returns. Because there can be no market bubbles, moreover, there can be no role for central banks to prick or deflate them; indeed some economists—including Milton Friedman—have suggested that central banks should be abolished altogether. But the Efficient Market Hypothesis goes further.

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There are no free lunches, no riskless profits to be gained, and no investor, however expert or naive, can do better over time than the market. The Efficient Market Hypothesis has been hugely influential in the development of modern finance theory; its early impact was such that in 1978 the economist Michael Jensen roundly stated, on the basis of considerable research, that ‘there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.’ In effect, it allows analysts to construct recognizable mathematical distributions of the probability of future price movements.

Dead Companies Walking
by Scott Fearon
Published 10 Nov 2014

Worst of all, though, those qualities also cause far too many money managers to confuse success with the size of their assets. They think bigger is always better—and they screw their clients out of higher returns because of it. Back when I was in business school in the early 1980s, the big idea in economics was something called the efficient markets hypothesis. It was formed by University of Chicago professor Eugene Fama. To simplify it as much as possible, Fama said that all stocks are efficiently priced at all times. In other words, the collective wisdom of the marketplace correctly sets the value of all publicly traded companies. In general, I agree. I think the stocks of most companies are efficiently priced.

Other People's Money: Masters of the Universe or Servants of the People?
by John Kay
Published 2 Sep 2015

The models that have been developed in financial economics are wide-ranging, and often technically ingenious. They include the Markowitz model of portfolio allocation (to which Greenspan referred) and the Black–Scholes model (the derivative pricing model to which he alluded). The key components of academic financial theory, however, are the ‘efficient market hypothesis’ (EMH), for which Eugene Fama won the Nobel Prize in 2013, and the Capital Asset Pricing Model (CAPM), for which William Sharpe won the Nobel Prize in 1990. Sharpe shared that prize with Markowitz, and Myron Scholes received a Nobel Prize in 1997, just before the famous blow-up of Long-Term Capital Management, in which Scholes was a partner; Black had died in 1995.

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But trading in financial markets, and innovation in business, are directed to the search for profit opportunities that have not been taken. The efficient market hypothesis at once captures an important aspect of reality – the absence of easy profits – and neglects an equally fundamental one: that the search for profits that are not easy is the dynamic of a capitalist system. Henry Ford, Walt Disney and Steve Jobs were not attempting to exploit arbitrage opportunities but trying to change the world (as were many less successful entrepreneurs). The wise investor will think twice before rejecting the efficient market hypothesis. Yet the volume of trading we observe in securities markets today would be wholly inexplicable if the hypothesis that all information relevant to security valuation is already in the price were true.

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The ‘no arbitrage’ condition was what Summers had in mind when he derided financial economists as people who ask whether two quart bottles of ketchup sell for twice the price of quart bottles without taking an interest in how the price of ketchup is itself determined. The legendary investor Warren Buffett presented the best summary critique of the efficient market hypothesis: ‘Observing correctly that the market was frequently efficient, they [academics, investment professionals and corporate managers] went on to conclude incorrectly that it was always efficient. The difference between these propositions is night and day.’27 Or, in Buffett’s case, a $50 billion fortune.

The Missing Billionaires: A Guide to Better Financial Decisions
by Victor Haghani and James White
Published 27 Aug 2023

See also Treasury Inflation‐Protected Securities (TIPS) annuities vs., 170 consol, 299 corporate, 212–213, 228 and interest rates, 293–294 municipal, 213 nominal, 204–205 Booth, David, 217–218 Borrowing, funding spending through, 270 Bubbles, 254 Buffett, Warren, 125, 131, 182, 209, 254, 307, 322 “Buy‐borrow‐die” approach, 270 Buy vs. rent decision, 214 CAEY (cyclically adjusted earnings yield), 345n1 Call options, 197n, 262 Campbell, John, 50n, 52, 150, 151, 295, 350n8 CAPE (cyclically adjusted price‐to‐earnings ratio), 50, 344n1 Capital asset pricing model (CAPM), 217, 232, 344n2 Capital gains taxes, 9, 45, 161, 182, 192, 213, 229, 266–272, 267t, 269e, 323 Capital in the 21st Century (Piketty), 324 Certainty‐equivalent return (CER), 82–83, 108n, 198, 340 Certainty‐equivalent wealth, 100, 124, 146, 197, 262, 267, 268, 306 Choi, James, 7, 100 Choice theory, 74–75 CMH (cost matters hypothesis), 203, 215 Cochrane, John, 52n Cognitive biases, 8, 77 Coin‐flipping experiment, 6, 11, 13, 15–25 description, 16–17 optimal strategy in, 17–19, 18t results of, 19–22, 21e, 29t stock‐market investing vs., 23–24 Collectibles, 231 Commodities, 231, 262–263 Competitiveness, of markets, 335 Compound return, average annual vs., 205–206 Consolidated annuities (consol bonds), 299 Constant absolute betting, 18–19 Constant fractional betting, 18–21, 24, 28 Constant proportional betting, 24 Constant Proportion Portfolio Insurance (CPPI), 184 Constant relative risk‐aversion (CRRA) utility, 75–79, 76e, 87, 89, 90, 107, 108n, 109, 109e, 113, 114, 340 adjustments to, 186 with digital assets, 305e with endowments, 155, 156 in investment opportunity exercise, 177–178 and mix of risky assets, 232 with options, 248, 249 with retirement spending, 134t Constant Standard of Living (CSL) annuities, 237–239 Consumer Price Index (CPI), 235–237, 239–242 Corporate bonds, 212–213, 228 “Costanza” trade, 258, 309–317 Cost basis, 269 Cost matters hypothesis (CMH), 203, 215 Covered‐call writing strategies, 256 CPI, see Consumer Price Index CPPI (Constant Proportion Portfolio Insurance), 184 CRRA utility, see Constant relative risk‐aversion utility Cryptocurrencies, 231, 304, 305e CSL (Constant Standard of Living) annuities, 237–240, 243 Currency fluctuations, 209 Cyclically adjusted earnings yield (CAEY), 344n1 Cyclically adjusted price‐to‐earnings ratio (CAPE), 50–51, 344n1 Decision‐making: biases in, 332 criticisms of expected‐utility‐based, 103–116 rational and consistent, as goal, 104 under uncertainty, 11 Deferred‐income annuities, 171 Defined‐contribution savings plans, 131 Derivatives, 116 Desire, and risk‐taking, 68–69 Dewey, Richard, 6, 16, 22, 60, 61, 343n1 Digital assets, 231, 304–305, 305e, 307 Diminishing marginal utility of consumption, 69 Disability insurance, 198n Discounted Lifetime Utility, 131n Discount rate, 208 Dividend‐based spending rule, 161 Doubling down betting, 18, 21 Drag, lift vs., 31–33 Dybvig, Philip, 355n1 Dynamic allocation strategy, 54, 54e, 55e, 59, 61e, 63–64, 337 Dynamic programming, 136 Earnings yield, see Cyclically adjusted price‐to‐earnings ratio (CAPE) Efficient markets, definition of, 303 Efficient markets hypothesis (EMH), 203, 215 Ellsberg, Daniel, 279n Ellsberg puzzle, 279, 280e, 281–282 Elm Wealth, 10, 11, 17, 123 EMH (efficient markets hypothesis), 215 End‐of‐life bequests, 169–170 “Endowment” economy, 292 Endowments, 149–163 complex situations affecting, 160–161 definition of, 150 dividend‐based rule with, 161 earnings‐yield policy with, 161–162 and family wealth, 161 future contributions to, 159–160 optimal spending policy with, 157–158 smoothed spending policies with, 162 spending policy options with, 151–154, 151t, 152e, 153t, 154e and time preference, 155–156 Epistemic uncertainty, 276 Epstein‐Zin preferences, 348n5 Equity‐linked annuities, 170 Equity Risk Premium (ERP) puzzle, 291–296 ESG investing, 224 ETFs, 212, 216–217, 221, 258, 309–313, 312e Exotic options, 263 Expected compound return, 154, 154e Expected excess return, 160 Expected Lifetime Utility, 8, 130–133, 134t, 135, 142, 144, 145, 201 with annuities, 169–171 calculation of, 133, 155 with endowments, 156–157, 160 importance of maximizing, 336 with options, 260 and sequence of returns, 141 steps in using, 138 Expected rate of return, 208 Expected Utility, 7–9, 122–126, 320–321, 325.

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Factor Investingg Factor investing has spawned hundreds of academic articles and trillions of dollars in assets under management, much of it invested through long‐only “Smart Beta” strategies. At its core is a high‐stakes unresolved tension spanning the industry and academia: is the stock market essentially efficient in terms of risk and reward, or are there major inefficiencies from which large groups of investors can systematically profit? The story begins with Nobel Laureate Eugene Fama and his 1965 PhD thesis, in which he proposed that the stock market is efficient and therefore very hard to beat.6 Decades later, Fama and his colleague Kenneth French noticed that stocks of companies that were either relatively small or cheaply valued had higher returns than predicted by the most popular stock market model of the day, the capital asset pricing model (CAPM).

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Estimating the return distributions for these investments will rely on the challenging task of forecasting changes in market microstructures, investor behavior, and the amount of risk‐capital that will be attracted to these opportunities, each of which can change rapidly and unpredictably. To help cut through all this complexity, we find ourselves always coming back to these three related hypotheses: The efficient markets hypothesis: The markets, especially large and liquid ones, are fairly efficient. The cost matters hypothesis: Costs matter. The average investor hypothesis: The market portfolio is the only investment that everybody can own at the same time. We'll see that these guiding principles are very effective in narrowing down the plausible return distributions we can expect from the different types of investments we'll discuss.

Buying Time: The Delayed Crisis of Democratic Capitalism
by Wolfgang Streeck
Published 1 Jan 2013

Lin, ‘Income Dynamics, Economic Rents and the Financialization of the US Economy’, American Sociological Review, vol. 76/4, 2011, pp. 538–59. 71 Fig. 1.8 shows four countries where the compensation effect was especially marked. It is worth noting that Sweden too (along with other Scandinavian countries) belongs in this group. 72 Among the main names here are Eugene Fama (father of the ‘efficient market hypothesis’), Merton H. Miller (co-founder of the Modigliani-Miller theorem), Harry Markowitz, Robert Merton, Myron Scholes and Fischer Black. Most have taught at the University of Chicago and appear on the list of winners of the so-called Nobel Prize in economics, awarded by the Swedish central bank (Riksbank). 73 This became clear in summer 2012, during the discussions on an EU ‘rescue package’ for Spanish banks.

No One Would Listen: A True Financial Thriller
by Harry Markopolos
Published 1 Mar 2010

Like me, maybe even more than me, he could glance at numbers and draw meaningful conclusions from them. At Bentley College, he played a lot of poker, ran a small bookie operation, and came to believe firmly in the efficient markets hypothesis. Believing that concept was where Neil and I differed most. The efficient markets hypothesis, which was first suggested by French mathematician Louis Bachelier in 1900 and was applied to the modern financial markets by Professor Eugene Fama at the University of Chicago in 1965, claims that if all information is simultaneously and freely available to everyone in the market, no one can have an edge. In this hypothesis having an edge means that for all intents and purposes you have accurate information that your competitors don’t have.

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These were the tools we depended on throughout our investigation. When Neil returned to college in the fall of 1992 to earn credit for his work as an intern, he had to write a paper. This will tell you what you need to know about Neil: The paper he wrote criticized the basic investment strategy we used at Rampart because it violated the efficient markets hypothesis. Three years later, after working in various jobs at several different types of investment companies, Neil returned to Rampart. Initially he was hired to upgrade our accounting system, with the unspoken hope that eventually it might become something more. For several months Neil ran two accounting systems—our legacy system and the new system—in parallel, and reconciled everything to the penny.

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The goal was to level the playing field, to ensure that anyone who wanted to buy or sell securities had access to the same information as everyone else, that they had all the information they needed to make intelligent decisions. As the SEC explains on its web site, its current mission is to “protect investors, [and] maintain fair, orderly, and efficient markets.” The efficient markets hypothesis, which Neil even now continues to believe in, theorizes—very basically—that as long as all market information is simultaneously and freely available to everyone, no one can have an edge. And that is completely dependent on the ability of the SEC to do its job. Through the years, though, the SEC had gained a completely undeserved reputation as the agency that effectively policed the financial markets, allowing people to believe that their interests were being protected.

Efficiently Inefficient: How Smart Money Invests and Market Prices Are Determined
by Lasse Heje Pedersen
Published 12 Apr 2015

EFFICIENTLY INEFFICIENT MARKETS To search for trading strategies that consistently make money over time, we need to understand the markets where securities are traded. The fundamental question concerning financial markets is whether they are efficient, a question that remains hotly debated. For instance, the Nobel Prize in economics in 2013 was awarded jointly to Eugene Fama, the father and defender of efficient markets, Robert Shiller, the father of behavioral economics, and Lars Hansen, who developed tests of market efficiency.2 As seen in Overview Table I, an efficient market, as defined by Fama, is one where market prices reflect all relevant information. In other words, the market price always equals the fundamental value and, as soon as news comes out, prices immediately react to fully reflect the new information.

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Ainslie III of Maverick Capital 108 Chapter 8 Dedicated Short Bias 115 Interview with James Chanos of Kynikos Associates 127 Chapter 9 Quantitative Equity Investing 133 Interview with Cliff Asness of AQR Capital Management 158 Part III Asset Allocation and Macro Strategies 165 Chapter 10 Introduction to Asset Allocation: The Returns to the Major Asset Classes 167 Chapter 11 Global Macro Investing 184 Interview with George Soros of Soros Fund Management 204 Chapter 12 Managed Futures: Trend-Following Investing 208 Interview with David Harding of Winton Capital Management 225 Part IV Arbitrage Strategies 231 Chapter 13 Introduction to Arbitrage Pricing and Trading 233 Chapter 14 Fixed-Income Arbitrage 241 Interview with Nobel Laureate Myron Scholes 262 Chapter 15 Convertible Bond Arbitrage 269 Interview with Ken Griffin of Citadel 286 Chapter 16 Event-Driven Investments 291 Interview with John A. Paulson of Paulson & Co. 313 References 323 Index 331 The Main Themes in Three Simple Tables OVERVIEW TABLE I. EFFICIENTLY INEFFICIENT MARKETS Market Efficiency Investment Implications Efficient Market Hypothesis: Passive investing: The idea that all prices reflect all relevant information at all times. If prices reflect all information, efforts to beat the market are in vain. Investors paying fees for active management can expect to underperform by the amount of the fee. However, if no one tried to beat the market, who would make the market efficient?

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Soros has developed a theory of boom/bust cycles and reflexivity, as he describes in the following excerpt from a recent lecture.5 Let me state the two cardinal principles of my conceptual framework as it applies to the financial markets. First, market prices always distort the underlying fundamentals. The degree of distortion may range from the negligible to the significant. This is in direct contradiction to the efficient market hypothesis, which maintains that market prices accurately reflect all the available information. Second, instead of playing a purely passive role in reflecting an underlying reality, financial markets also have an active role: they can affect the so-called fundamentals they are supposed to reflect.

Crisis Economics: A Crash Course in the Future of Finance
by Nouriel Roubini and Stephen Mihm
Published 10 May 2010

Whoever came up with the joke was on to something: markets look remarkably inefficient; savvy investors manage to pick up plenty of genuine hundred-dollar bills. Many economists, moreover, have poked holes in the Efficient Market Hypothesis, not with anecdotal evidence but with rigorous statistical analysis. The most trenchant critic is Yale economist Robert Shiller. In the early 1980s, Shiller conducted research demonstrating that stock prices exhibit far more volatility than the Efficient Market Hypothesis can possibly explain. By the end of that decade, he and other critics had amassed a remarkable body of evidence showing that asset prices rarely rest in a state of equilibrium but rather fluctuate wildly.

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In theory, the Great Depression should have put an end to this sort of nonsense, but postwar academic departments of economics and finance breathed new life into the old fallacy. Much of the credit—if that’s the word—goes to the economics department at the University of Chicago. A professor named Eugene Fama and others sympathetic to laissez-faire economic policies began to construct elaborate mathematical models aimed at proving that markets are utterly rational and efficient. Again, they believed that the price of any given asset at any time is always completely correct. In other words, an asset cannot be overvalued or undervalued; the current price is the right price, nothing more and nothing less.

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The scores of economists who embraced this thesis in the postwar years gave it nuance, acknowledging that markets may be more or less efficient depending on certain variables. But its overall thrust—that markets are efficient and incorporate all known information into prices—remained a truism in business schools and economics departments. By the 1970s the Efficient Market Hypothesis had become conventional wisdom, preached from academic pulpits at the University of Chicago and elsewhere. However, not everyone bought into it. A popular joke among economists neatly captures its logical absurdities. An economist and his friend are walking down the street when they come across a hundred-dollar bill lying on the ground.

The Clash of the Cultures
by John C. Bogle
Published 30 Jun 2012

Simple Arithmetic: An Unarguable Conclusion Few commentators have recognized that two distinct intellectual ideas formed the foundation for passive investment strategies. Academics and sophisticated students of the markets—“quants,” as they are known today—rely upon the EMH—the Efficient Market Hypothesis, first articulated by University of Chicago Professor Eugene Fama in the mid-1960s. This theory suggests that by reflecting the informed opinion of the mass of investors, stocks are continuously valued at prices that accurately reflect the totality of investor knowledge, and are thus fairly valued. But, as I’ve often noted, we didn’t rely on the EMH as the basis for our conviction.

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See also Retirement system design problems with growth in passively managed index funds in simplifying speculative investment options in Delaware Democracy, corporate Derivatives Dimensional Fund Advisors Directors Diversification Dodd-Frank Wall Street Reform and Consumer Protection Act (2010) “Do ETFs Badly Serve Investors?” (Tower and Xie) Domestic equity mutual funds Double-agency society Earnings, managed Econometric techniques “Economic Role of the Investment Company, The” (Bogle) Economics (Samuelson) Economist, The Efficient Market Hypothesis (EMH) Ellis, Charles D. Emerging markets stock funds Employee Retirement Income Security Act (ERISA) Employer, stock of Equity diversification Equity index funds Equity mutual funds. See also Actively managed equity funds assets costs domestic emerging markets expense ratio, average failure of large-cap number of returns small capitalization volatility, increase in Equity ownership, institutional ERISA (Employee Retirement Income Security Act) Essinger, Jesse Estrada, Javier Exchange traded funds (ETFs): assets Economist on future of growth in history of holding periods institutional versus individual investors in managers, leading number of problems with profile focus and selection risk profile of returns as speculation trading volumes traditional index funds versus turnover Vanguard Wall Street Journal listing of Exchange traded notes (ETNs) Executive compensation: average worker’s pay compared to cost of capital and highest increase in ratchet effect reform, progress on reform suggestions as “smoking gun,” tax surcharge on Exile on Wall Street (Mayo) Expectations, investment Expectations market Expenses.

Austerity: The History of a Dangerous Idea
by Mark Blyth
Published 24 Apr 2013

So when it happened, it was bound to open up room for ideas that said such events were inevitable if you let markets regulate themselves, which is the Keynesian point. It was hard to publicly defend the logic of self-correcting markets when they were so obviously not self-correcting. Indeed, such traditional standard bearers for the neoclassical cause as Eugene Fama, Edward Prescott, and Robert Barro who had previously enjoyed public prominence found themselves confined to the opinion pages of the Wall Street Journal. No one was buying “the price is always right/state bad and market good” story when prices had been shown to be wrong by a few orders of magnitude and the state was bailing out the market.

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Agents’ expectations of the future, in new classical language, will be rational, not random, and the price given by the market under such conditions will be the “right” price that corresponds to the true value of the asset in question. Markets are efficient in the aggregate if their individual components are efficient, which they are, by definition. This world was indeed, to echo Dr. Pangloss, the best of all possible worlds. As John Eatwell noted a long time ago, these ideas, formalized as the efficient markets hypothesis (EMH) and the rational expectations hypothesis (RATEX), are just as important politically as they are theoretically, for taken together they hold that free and integrated markets are not merely a good way to organize financial markets, they are the only way. Any other way is pathology.

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Tales of Two Small European Countries,” (Giavazzi), 169, 170, 171, 176, 209–210 Canada fiscal adjustment in, 173 Capitalism, Socialism and Democracy, (Schumpeter), 128, 129 Cassel, Gustav, 191 central banks, independence of, 156–158 certificates of deposit (CDs), 234 Chin, Menzie, 11 China, 55 Chowdhury, Anis, 176 Churchill, Winston, 123 and the gold standard, 189 1929 budget speech, 124 Citigroup, 48 Clinton, Bill, 12 Clinton, Hillary, 218 Cochrane, John, 2, 239 Colander, David, 99 collateralized debt obligations, 28, 234 Congressional Research Group, 242 Considine, John, 208 Coolidge, Calvin, 120 Credit Agricole, 87 credit default swaps, 26, 29, 30 Daimler/Mercedes Benz, 132 Darwin’s Dangerous Idea (Dennett), 159 De Grauwe, Paul, 86 debt inflation, 150 default as a way out of financial crises, 183 mortgage, 41, 42, 44, 50 risk, 24 sovereign, 113, 210, 241 See also credit default swaps (CDSs) deflation, 240, 241 demand-side economics, 127 See also supply-side economics Denmark, 207, 209 as a welfare state, 214 austerity in, 17, 169–170, 170–171, 179 expansion, 205, 206, 209 fiscal adjustment in, 173 Dennett, Daniel Darwin’s Dangerous Idea, 159 derivatives, 27–30 credit default swaps, 27–30 special investment vehicles, 29 See also mortgages; real estate Deutsche Bank, 83 devaluation and hyperinflation, 194 as a way out of financial crises, 75, 173, 208, 213 of currency, 76, 77, 147, 169, 171, 188, 191, 197 Diamond, Peter, 243 disintermediation, 23, 49, 232 Dittman, Wilhelm, 195 Dow Jones Industrial Average, 1, 2–3 Duffy, James, 208 Eatwell, John, 42 Economic and Financial Affairs Council of the European Council of Ministers (ECOFIN), 173, 175, 176 economics Adam Smith, 109 Austrian school of, 31, 144 demand-side, 127 Frieburg school of, 135 Germany’s Historical school of, 143 Keynesian, ix, 39, 54 liberal, 99 London School of, 31, 144 macro, 40 neoclassical, 41 neoliberal, 41, 92 public choice, 166 supply-side, 111 zombie, 10, 234 Economics of the Recovery Program, The, (Schumpeter), 128 Economist, The, 69, 166, 216 efficient markets hypothesis, 42 Eichengreen, Barry, 183, 231 Einaudi, Luigi, 165, 167 Eisenhower, Dwight, 243 Englund, Peter, 211 Estonia austerity in, 18, 103, 179, 216–226, 217 fig. 6.1 Eucken, Walter, 135–136 centrally administered economy, 135–136 transaction economy, 135–136 Euro, 74–75, 77 success or failure of, 78–81, 87–93 European banks austerity and, 87 fall of, 84–87 “too big to bail”, 6, 16 European Bond Market, 1 European Central Bank, 54, 55, 84 and austerity, 60, 122 and bailouts, 71–73 and loans to Ireland, 235 and the success of the REBLL states, 216 emergency liquidity assistance program, 4 limitations of, 87–93 long-term refinancing operation, 4, 86 Monthly Bulletin, June 2010, 176 See also Trichet, Jean Claude European Commission, 122 and austerity, 221 and loans to Ireland, 235 and the success of the REBLL states, 216 European Economic Community, 62–64 European Exchange Rate Mechanism, 77 European Union and austerity, 221 and bailouts, 71–73, 208, 221 influence on Europe, 74–75 Eurozone and current economic conditions, 213 current account imbalances, 78 fig. 3.1 ten-year government bond yields, 80 fig. 3.2 exchange-traded funds (ETFs), 234 Fama, Eugene, 55 Fannie Mae, 121 Farrell, Henry, 55 Federal Deposit Insurance Corporation (FDIC), 24 Feldstein, Martin, 55, 78 Ferguson, Niall, 72 Figaro, Le, 201 financial repression, 241 Financial Stability Board, 49 Financial Times, 60 Fisher, Irving, 150 Fitch Ratings, 238 Flandin, Pierre-Étienne, 202 fractional reserve banking, 110 France, 4 and Germany’s nonpayment of Versailles treaty debt, 57 and John Law, 114 and the gold standard, 185, 204 assets of large banks in, 6 austerity in, 17, 126, 178–180 and the global economy in the 1920s and 1930s, 184–189 bond rates in, 6 depression in, 201–202 Eurozone Current Account Imbalances, 78 fig. 3.1 Eurozone Ten-Year Government Bond Yields, 80 fig. 3.2 war debts to the United States, 185 See also Blum, Leon; Flandin, Pierre-Étienne; Laval, Pierre; Poincaré, Raymond Freddie Mac, 121 free option, 29 Freiberg school of economics, 135, 136, 138–139 Frieden, Jeffry, 11 Friedman, Milton, 103, 155, 156, 165, 173 G20 2010 meeting in Toronto, 59–62 Gates, Bill, 7, 8, 13 Gaussian distribution, 33, 34 General Theory (Keynes), 126, 127, 145 Gerber, David, 136 Germany, 2, 16 and repayment war damage in France, 200–201 and the gold standard, 185 and the Treaty of Versailles, 185 as an economic leader, 75–78 austerity in, 17, 25, 57, 59, 101–103, 132–134 and the global economy in the 1920s and 1930s, 178–180, 184–189, 186, 193–197 Bismarkian patriarchal welfare state, 137 Bundesbank, 54, 156, 172, 173 capital drain after World War I, 186 Center Party, 194 Christian Democrats, 137, 139 competition, 137–138 economic ideology of, 56–58, 59–60 entrance into world economy, 134–135 Eurozone Current Account Imbalances, 78 fig. 3.1 Eurozone Ten-Year Government Bond Yields, 80 fig. 3.2 fiscal prudence of, 2, 17, 54 founder’s crisis, 134 German Council of Economic Advisors Report, 169 gold standard and, 196 Historical school of economics, 143 hyperinflation in the 1920s, 56–57, 185, 194, 200, 204 industry in, 132–134 See also BASF, Daimler/Mercedes Benz, Krups, Siemens, ThyssenKrupp ordoliberalism in, 101, 131, 133 origins of, 135–137 order-based policy, 136 National Socialists, 194–195 Nazi period in, 136, 196 Social Democratic Party, 140, 194, 195, 204 social market economy, 139 Stability and Growth Pact, 92, 141 stimulus in, 55–56 See also Freiburg school of economics stop in capital flow from United States in 1929, 190, 194 unemployment in, 196 WTB plan, 195, 196 Giavazzi, Francesco, 179, 205, 206 “Can Severe Fiscal Contractions be Expansionary?

A Pelican Introduction Economics: A User's Guide
by Ha-Joon Chang
Published 26 May 2014

This was the kind of practice Gordon Gekko (you’ve met him in Chapter 3) was attacking in Wall Street, when he pointed out the company that he was trying to take over had no less than thirty-three vice presidents, doing God knows what. Many pro-market economists, especially Michael Jensen and Eugene Fama, the 2013 Nobel Economics Prize winner, have suggested that this principal-agent problem can be reduced, if not eliminated, by aligning the interests of the managers more closely to those of the shareholders. They suggested two main approaches. One is making corporate takeover easier (so more Gordon Gekkos, please), so that managers who do not satisfy the shareholders can be easily replaced.

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Information economics explains why asymmetric information – the situation in which one party to a market exchange knows something that the other does not – makes markets malfunction or even cease to exist.7 However, since the 1980s, many Neoclassical economists have also developed theories that go so far as to deny the possibility of market failures, such as the ‘rational expectation’ theory in macroeconomics or the ‘efficient market hypothesis’ in financial economics, basically arguing that people know what they are doing and therefore the government should leave them alone – or, in technical terms, economic agents are rational and therefore market outcomes efficient. At the same time, the government failure argument was advanced, to argue that market failure in itself cannot justify government intervention because governments may fail even more than markets do (more on this in Chapter 11).

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The individualist economic model assumes the kind of rationality that no one possesses – Herbert Simon called it ‘Olympian rationality’ or ‘hyper-rationality’. The standard defence is that it does not matter whether a theory’s underlying assumptions are realistic or not, so long as the model predicts events accurately. This kind of defence rings hollow these days, when an economic theory assuming hyper-rationality, known as the Efficient Market Hypothesis (EMH), played a key role in the making of the 2008 global financial crisis by making policy-makers believe that financial markets needed no regulation. The problem is, simply put, that human beings are not very rational – or that they possess only bounded rationality.* The list of non-rational behaviour is endless.

Red-Blooded Risk: The Secret History of Wall Street
by Aaron Brown and Eric Kim
Published 10 Oct 2011

See Bayesians/Bayesian concepts; Frequency vs. degree of belief Demon of Our Own Design, A, (Bookstaber) Derivatives/derivative money: capital creation and clearinghouses definition derivative money energy sector and exposure from derivatives liquidity and as the new money numeraire and spread trade and as store of value Derivatives Models on Models (Haug) Derman, Emanuel Desrosières, Alain Dexter, Andrew Diogenes Disintermediation Dissertation (Brown) Dorner, Dietrich Drobny, Steven Druckenmiller, Stanley Duffie, Darrell Earle, Timothy Economic Function of Futures Markets, The (Williams) Economics of Risk and Time, The (Gollier) Econophysics Education of a Speculator, The (Niederhoffer) Efficient markets hypothesis (EMH) Efficient markets theory: empirical evidence equilibrium price and father of efficient markets generally market inefficiencies and misrepresentations and myth about Efron, Brad Eichengreen, Barry Einhorn, David Eisenhower, Dwight Emergence of Probability, The (Hacking) EMH. See Efficient markets hypothesis (EMH) Energy industry Engle, Rob Equilibrium eRaider.com Errors/error rates ETFs. See Exchange-traded funds (ETFs) Evans, Dylan Evolution EWMA.

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There is an infinite number of rules that would have worked in the past, because there is an infinite number of potential rules. You can always find lots that seem to work great—it’s called data mining. Finding ideas that will work in the future requires theory. Efficiency versus Equilibrium A crucial point in interpreting tests of efficient markets theory was described by Eugene Fama, known as the father of efficient markets: “Every test of market efficiency is a joint test of market efficiency and market equilibrium.” In simpler words, you can’t test whether the market is doing what it is supposed to do without first specifying what it is supposed to do. That’s true for testing markets, but not for exploiting markets.

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A manager in the 1950s might have agreed that MPT was a decent simplified model of portfolio construction, and Markowitz did market it as a product with some limited success. No one thought they were IGT investors, and until Ed Thorp, no one tried to market an IGT product. The next advance in real-world finance was the efficient markets hypothesis (EMH). This held that all securities were priced fairly—that you shouldn’t be able to build two portfolios out of public securities such that one consistently outperforms the other after adjusting for risk. In the IGT world, there’s no clear meaning to fair price. The parallel hypothesis in IGT is that capital is allocated to securities properly.

Making It Happen: Fred Goodwin, RBS and the Men Who Blew Up the British Economy
by Iain Martin
Published 11 Sep 2013

Boyd and Amanda Heitz, University of Minnesota, February 2012. 5 ‘The implicit subsidy of banks’, Joseph Noss and Rhiannon Sowerbutts, Financial Stability paper, 15 May 2012. Bank of England. 6 ‘“Too big to fail” is too dumb an idea to keep’, John Kay, Financial Times, 27 October 2009. 7 The credit for the development of the efficient market hypothesis is often given to Professor Eugene Fama, of the University of Chicago Booth School of Business. Index (the initials FG in subentries refer to Fred Goodwin) ABN Amro, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10 and low RBS liquidity, ref 1 Adam & Co., ref 1, ref 2 Agnew, Jonathan, ref 1 AIG, ref 1 Alemany, Ellen, ref 1 Allan, Iain, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 and CDOs, ref 1, ref 2, ref 3, ref 4 Antonveneta, ref 1 Argus, Don, ref 1 Argyll, 2nd Duke of, ref 1 Armitstead, Louise, ref 1 Arsenal FC, ref 1 Arthur Andersen, ref 1, ref 2 asset-backed securities (ABSs), ref 1, ref 2 AstraZeneca, ref 1, ref 2 Aviva, ref 1 Ayr Bank, ref 1, ref 2 BAA, ref 1 Bailey, Andrew, ref 1, ref 2, ref 3 Bailie Gifford, ref 1 Balfour Beatty, ref 1 Balls, Ed, ref 1, ref 2, ref 3 Bank of America, ref 1 Merrill Lynch sold to, ref 1 Bank Bosses are Criminals, ref 1 Bank of China, ref 1, ref 2 Bank of Credit and Commerce International (BCCI), ref 1, ref 2, ref 3 Bank of England: and banking supervision, see banks: regulation of; Financial Services Authority and County NatWest, ref 1 culpability of, ref 1 Darling reassurance to RBS concerning, ref 1 founding of, ref 1, ref 2 Gieve role in, ref 1 house prices ignored by, ref 1 independence of, ref 1, ref 2, ref 3, ref 4, ref 5 King becomes governor of, ref 1, ref 2 Monetary Policy Committee of, ref 1, ref 2, ref 3 and RBS collapse, ref 1, ref 2 and RBS privatisation, ref 1 and Scottish banks’ own notes, ref 1 and tripartite regulation, ref 1, ref 2, ref 3, ref 4, ref 5; see also Financial Services Authority Bank of Scotland, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6 founding of, ref 1, ref 2 as joint stock-bank, ref 1 modern British banking pioneered by, ref 1 national networks developed by, ref 1 and NatWest, ref 1, ref 2, ref 3, ref 4, ref 5 RBS early rivalry with, ref 1 ‘sues for peace’, ref 1 Whigs distrust, ref 1 see also Halifax; HBOS bankers: accountants versus, ref 1 ‘“canny” Scottish’, ref 1 Labour honours and ennobles, ref 1 large remuneration of, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12, ref 13 prosecution avoided by, ref 1 banks: auditing of, ref 1; see also banks: regulation/supervision of bailouts of, ref 1, ref 2, ref 3, ref 4, ref 5 passim, ref 1 and Basel regulation, ref 1 and Big Bang, ref 1, ref 2, ref 3, ref 4 Brown wish for competition among, ref 1 Darling promises support for, ref 1 Darling meeting with CEOs of, ref 1 deregulation of, ref 1 foreign investment, presence of, in UK, ref 1 globalised nature of, ref 1 growing profits of, ref 1 innovative activities embraced by, ref 1; see also individual banks and interest rates, ref 1, ref 2, ref 3, ref 4, ref 5 lighter scrutiny of, ref 1; see also Financial Services Authority more credit offered by, ref 1 proposed ring fence for, ref 1, ref 2 regulation/supervision of, ref 1, ref 2, ref 3; see also banks: auditing of; Basel; Financial Services Authority reluctance of, to deal with RBS, ref 1 remodelling of, ref 1 revelations about conduct of, ref 1 ‘too big to fail’, ref 1 tripartite regulation of, ref 1, ref 2, ref 3, ref 4, ref 5; see also Basel; Financial Services Authority UK, balance sheets of, ref 1, ref 2, ref 3, ref 4 UK, clearing, balance sheets of (since 1960), ref 1 UK, growth of, ref 1 UK, steady fall in number of, ref 1 and Value at Risk (VaR), ref 1, ref 2 see also City of London Banque de France, ref 1 Barclays, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9 and ABN Amro, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8 FG hates, ref 1 fines paid by, ref 1 growing profits of, ref 1 Barclays Capital, ref 1, ref 2 Barings, ref 1, ref 2 Basel, ref 1 Bear Stearns, ref 1 Better Regulation Action Plan, ref 1 see also banks: regulation of Better Regulation Task Force, ref 1 Big Bang, ref 1, ref 2, ref 3, ref 4, ref 5 Birmingham and Midshires, ref 1 Black, Joseph, ref 1 Blair, Cherie, ref 1 Blair, Tony, ref 1, ref 2, ref 3 and 1997 election, ref 1 and bank regulation, ref 1 bankers fêted by, ref 1 Brown wants to oust, ref 1 FG Chequers meal with, ref 1 and Gaddafi, ref 1 leadership won by, ref 1 Blank, Victor, ref 1 Bloomberg, ref 1 Blue Arrow affair, ref 1 Blunkett, David, ref 1 BNP Paribas, ref 1, ref 2 boom and bust, ‘end’ of, ref 1, ref 2, ref 3, ref 4, ref 5 Botín, Emilio, ref 1, ref 2, ref 3, ref 4 BP, ref 1 Bradford & Bingley, ref 1, ref 2 Braveheart, ref 1, ref 2, ref 3 Briault, Clive, ref 1, ref 2 Brown, Andrew, ref 1 Brown, Gordon, ref 1, ref 2 passim and 1997 election, ref 1 ‘appalled’ by RBS crisis, ref 1 and bank bailouts, ref 1, ref 2, ref 3 and bank regulation, ref 1, ref 2, ref 3 bankers fêted by, ref 1 becomes Chancellor, ref 1 and BoE independence, ref 1, ref 2, ref 3 boom–bust conference speech of, ref 1 and boom and bust, ‘end’ of, ref 1, ref 2, ref 3, ref 4, ref 5 Chancellorship aspirations of, ref 1 Darling joint press conference with, ref 1 economic growth under, ref 1 father influence on, ref 1 FG compared to, ref 1 and Greenspan, see Greenspan, Alan house prices rise under, ref 1 and interest-rate control, ref 1, ref 2 King relationships with, ref 1 last Mansion House speech of, ref 1 leadership bid lost by, ref 1 and Lloyds–HBOS, ref 1 RBS bailout announced by, ref 1, ref 2 and RBS collapse, ref 1, ref 2 Smith influence on, ref 1 and socialism, ref 1 at university, ref 1 and US politics, ref 1, ref 2 Brown, John, ref 1 Brown, John Ebenezer, ref 1, ref 2 Buccleuch, Duke of, ref 1 Buchan, Colin, ref 1, ref 2, ref 3, ref 4, ref 5 Buffet, Warren, ref 1 Burlington Resources, ref 1 Burns, Robert, ref 1 Burns, Terry, ref 1 Burnside, Howard, ref 1 Burt, Peter, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6 Bush, George H.W., ref 1, ref 2 Bush, George W., ref 1, ref 2, ref 3 Bush, Laura, ref 1 Butler, Lord, ref 1 Cable, Vince, ref 1 Caledonia, naming of, ref 1 Cameron, Donald, ref 1 Cameron, Johnny, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 passim, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9 passim, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 and ABN Amro, ref 1, ref 2, ref 3, ref 4 FG stands by, ref 1 FSA investigates, ref 1, ref 2 at Gogarburn opening, ref 1 and hedging exposure, ref 1 and worsening liquidity situation, ref 1 Camerons of Locheal, ref 1, ref 2, ref 3, ref 4 Campbell, Archibald, see Ilay, Earl of Campbell, John, ref 1, ref 2, ref 3 Canary Wharf, ref 1 Caplan, Rick, ref 1, ref 2, ref 3, ref 4, ref 5 Carpenter, Ben, ref 1, ref 2, ref 3 Charles, Prince of Wales, ref 1, ref 2, ref 3 Charter One, ref 1, ref 2 Chase, ref 1 Chirac, Jacques, ref 1 Chisholm, Andy, ref 1 Churchill, ref 1, ref 2 Churchill, Winston, ref 1 Cicutto, Frank, ref 1, ref 2, ref 3 Citibank, ref 1 Citigroup, ref 1, ref 2, ref 3 Citizens Bank, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12 and Mellon, ref 1 new CEO for, ref 1 City of Glasgow Bank, ref 1 City of London, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12, ref 13, ref 14, ref 15 modernisation of, ref 1 see also banks Clarke, Charles, ref 1 Clarke, Ken, ref 1 Clinton, Bill, ref 1, ref 2, ref 3 Clydesdale Bank, ref 1, ref 2, ref 3, ref 4, ref 5 away days of, ref 1 celebrations at, as FG leaves, ref 1 FG becomes CEO of, ref 1 Cochrane, Alan, ref 1 Cole-Hamilton, Richard, ref 1 Coleman, David, ref 1, ref 2 collateralised debt obligations (CDOs), ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11 index of, ref 1 varieties of, ref 1 see also sub-prime mortgages Commonwealth Bancorp, ref 1 Community Bancorp, ref 1 Compagnie Bancaire, ref 1 Company of Scotland, ref 1 founding of, ref 1 ‘Competition in UK Banking’, ref 1 Connolly, John, ref 1, ref 2, ref 3, ref 4, ref 5 ConocoPhillips, ref 1 Conservatives, see Tories consumer debt, ref 1 Conti, Tom, ref 1 Cooper, Yvette, ref 1, ref 2 Corbett, R.Y., ref 1 Cornwall, Duchess of, ref 1 Countrywide Financial, ref 1 County NatWest, ref 1, ref 2 Coutts, ref 1, ref 2, ref 3, ref 4, ref 5 Cox, Archie, ref 1 credit crunch, see financial crisis credit default swaps (CDSs), ref 1 Crosby, James, ref 1, ref 2, ref 3, ref 4, ref 5 knighthood lost by, ref 1 Crowe, Brian, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12 and CDOs, ref 1 and hedging exposure, ref 1 moved to ABN Amro, ref 1 ordination of, ref 1, ref 2 withdrawn from ABN Amro, ref 1 and worsening liquidity situation, ref 1 Crowe, Russell, ref 1 Cruickshank, Don, ref 1 Crutchley, John-Paul, ref 1 Cryan, John, ref 1, ref 2 Cummings, Peter, FSA fines, ref 1 Cummins, John, ref 1 Currie, Jim, ref 1 Daily Telegraph, ref 1, ref 2 Daniels, Eric, ref 1 Darien Scheme, ref 1, ref 2, ref 3, ref 4 Caledonia emerges from, ref 1 Darling, Alistair, ref 1, ref 2 and bank bailouts, ref 1, ref 2, ref 3 banks’ CEOs meet with, ref 1 and Brown–George spat, ref 1 Brown joint press conference with, ref 1 at ECOFIN meeting, ref 1 and FG knighthood, ref 1 and FG pension, ref 1, ref 2, ref 3 FSA and BoE meet with, ref 1 at Gogarburn opening, ref 1 Goodwin meets (2007), ref 1 King follows plan of, ref 1 King relationships with, ref 1 memoirs of, ref 1 MPs briefed on financial crisis by, ref 1 RBS bailout announced by, ref 1, ref 2 and RBS collapse, ref 1 Treasury meeting called by, ref 1 UK banks supported by, ref 1 Darroch, Kim, ref 1 Davidson, Joanna, ref 1, ref 2 Davies, Howard, ref 1, ref 2 Davos, ref 1 de la Renta, Oscar, ref 1 deficit, sharp rise in, ref 1 Deloitte & Touche, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 Deutsche Bank, ref 1, ref 2 Dewar, Donald, ref 1 Diamond, Bob, ref 1, ref 2, ref 3 forced out of post, ref 1 Dickinson, Alan, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12, ref 13 Dime Bancorp, ref 1 Direct Line, ref 1, ref 2, ref 3 District Bank, ref 1 Dixon Motors, ref 1 Dixon, Paul, ref 1 Dixon, Simon, ref 1 dotcom bubble, ref 1 Dow Jones, ref 1 Drake-Brockman, Symon, ref 1 Dresdner Kleinwort Wasserstein, ref 1, ref 2 ‘Drivers for Growth’ conference, ref 1 Drummond Bank, ref 1, ref 2, ref 3 Dundas, Lawrence, ref 1 Dundee Banking Company, ref 1 Dutch Central Bank, ref 1 Duthie, Robin, ref 1 East India Company, ref 1 Economic and Financial Affairs Council (ECOFIN), ref 1, ref 2 Economist, ref 1, ref 2 Eden, James, ref 1, ref 2 Elizabeth II, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 emerging economies, ref 1 Emirates Stadium, ref 1 Enron, ref 1, ref 2 Equitable Life, ref 1 Equivalent Company, ref 1 Ernst & Young, ref 1 euro, see single currency Exchange Rate Mechanism (ERM), ref 1, ref 2 ‘failure of the Royal Bank of Scotland, The’ (FSA), ref 1, ref 2 Fastow, Andy, ref 1 Federal Reserve, ref 1, ref 2, ref 3 Ferguson, Adam, ref 1 Ferguson, Alex, ref 1 Ferguson, William, ref 1 Ferrovial, ref 1 Fidelity, ref 1 Fildes, Christopher, ref 1 Financial Conduct Authority., ref 1 financial crisis: beginning of, ref 1 Darling updates Commons on, ref 1 government spending at start of, ref 1 insurers crack under weight of, ref 1 recessions follow, ref 1 spreads to UK high street, ref 1 studies and reports of, ref 1 Financial Services Authority (FSA), ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9, ref 10, ref 11, ref 12 ‘Arrow’ reports of, ref 1 and auditors, ref 1 and RBS collapse, ref 1 RBS on watch-list of, ref 1 self-investigation by, ref 1 successors to, ref 1 and tripartite regulation, ref 1, ref 2, ref 3, ref 4, ref 5; see also Bank of England Financial Times, ref 1, ref 2 First Active, ref 1 Fish, Larry, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9 chairs RBS Americas, ref 1 criticised, ref 1 pension of, ref 1 Fisher, Mark, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7 at Gogarburn opening, ref 1 moved to ABN Amro, ref 1 Fitch Ratings, ref 1, ref 2 Fleming, Ian, ref 1 Fletcher, Andrew, ref 1 Forbes, ref 1 foreign exchange, ref 1, ref 2 Formula 1, ref 1, ref 2 Fortis, ref 1, ref 2, ref 3 Fountain Workshop, ref 1 Franklyn Resources, ref 1 Freshfields, ref 1 Friedrich, Bill, ref 1, ref 2 Fuld, Dick, ref 1 Gaddafi, Muammar, ref 1 Gartmore, ref 1 GE, ref 1 George II, ref 1 George, Eddie, ref 1, ref 2, ref 3, ref 4 Gibson, Mel, ref 1, ref 2 Gieve, John, ref 1 Giles, Chris, ref 1 Gladiator, ref 1 Glass–Steagall Act, ref 1 global financial crisis, see financial crisis Global Transaction Services, ref 1, ref 2 Glyn, Mills & Co., ref 1, ref 2 Goldman Sachs, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6, ref 7, ref 8, ref 9 Goodwin, Andrew (brother), ref 1 Goodwin, Dale (sister), ref 1 Goodwin, Fred: affair of, ref 1, ref 2, ref 3, ref 4 after RBS, ref 1 and away days, ref 1, ref 2 bailout terms heard by, ref 1 Barclays hated by, ref 1 becomes Clydesdale CEO, ref 1 becomes RBS CEO, ref 1 birth of, ref 1 Brown compared to, ref 1 Brown likes, ref 1 Bush dinner guest, ref 1 and car dealership, ref 1 CDO presentation by, ref 1 at CEOs–Darling meeting, ref 1 at CEOs meeting, ref 1 Chequers invitation to, ref 1 ‘classic bully’, ref 1 cleanliness campaigns of, ref 1 at Clydesdale, see Clydesdale Bank colleagues testify to abilities of, ref 1 cult status of, ref 1 at Darling 2008 meeting, ref 1 Darling visited by (2007), ref 1 document criticises management of, ref 1 early life of, ref 1, ref 2 extraordinary general meeting appearance of, ref 1 face-to-face firing disliked by, ref 1, ref 2, ref 3 first job of, ref 1 fixation on detail by, ref 1, ref 2, ref 3, ref 4, ref 5, ref 6 and Forbes, ref 1 ‘Fred the Shred’ nickname of, ref 1, ref 2, ref 3, ref 4 and FSA, ref 1, ref 2 at Gogarburn opening, ref 1 Harvard study on, ref 1, ref 2 ‘has shut out the world’, ref 1 Hester view of, ref 1 ‘I want to be bigger than J.

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Just think of the trouble that might have been averted in Britain if he had focused on such themes at the start of his tenure in 2003. Yet that was simply not the mood of the time. The intellectual climate was such that there was an over-reliance on the application of new economic theories, mathematical modelling and the growing ‘tyranny of data’. The ‘efficient market hypothesis’, developed in the 1970s, dominated thinking on financial markets for most of the next four decades.7 It held that markets are self-correcting and that if investors all have the same information they will make entirely rational decisions. What a nice idea, if you presume that everyone has access to and takes time to read the same material.

Trend Following: How Great Traders Make Millions in Up or Down Markets
by Michael W. Covel
Published 19 Mar 2007

Fama, two scholars at the University of Chicago, launched what became known as the Efficient Market Hypothesis: “The premise of the hypothesis is that stock prices are always right; therefore, no one can divine the market’s future direction, which in turn, must be ‘random.’ For prices to be right, of course, the people who set them must be both rational and well informed.”27 In other words, Miller and Fama believed that perfectly rational people would never pay more or less than any financial instrument was actually worth. A fervent supporter of the Efficient Markets Hypothesis, Myron Scholes was certain that markets could not make mistakes.

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With each forecast of trend following doom and gloom, usually in the form of book review, column, or interview, I would “set the record straight.” I’d usually start by addressing the assumption that generates much of the confusion in the first place—the efficient market hypothesis. The hypothesis essentially says that you can’t find an edge to beat the market, and simply sticking with a benchmark or index is the best path to take for profit (believe that still after 2008?). Proponents of the efficient market hypothesis argue that because markets are efficient and prices fully reflect all information, traders who consistently outperform the market do so out of luck, not skill. Of course, in the real world, markets are both efficient and inefficient, some more than others.

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In hindsight, the old-guard Chicago professors were clearly aware of the problem as Nobel Laureate Professor Merton Miller pondered: “Models that they were using, not just Black-Scholes models, but other kinds of models, were based on normal behavior in the markets and when the behavior got wild, no models were able to put up with it.”35 If only the principals at LTCM had remembered Albert Einstein’s quote that elegance was for tailors, part of his observation Chapter 4 • Big Events, Crashes, and Panics 155 about how beautiful formulas could pose problems in the real world. LTCM had the beautiful formulas; they were just not for the real world. Eugene Fama, Scholes’ thesis advisor, had long held deep reservations about his student’s options pricing model: “If the population of price changes is strictly normal [distribution], on the average for any stock…an observation more than five standard deviations from the mean should be observed about once every 7,000 years.

The Volatility Smile
by Emanuel Derman,Michael B.Miller
Published 6 Sep 2016

Whether you believe their performance was due to luck or to skill, to significantly outperform the market you do not need to be very good at stock price prediction. Being right just 55% to 60% of the time, consistently, over many trades, is remarkable and can lead to great profit. In the 1960s, faced with this failure at price prediction, a group of academics associated with Eugene Fama at the University of Chicago developed what has become known as the efficient market hypothesis. Over the years, many formulations of the theory have evolved, some more mathematical and rigorous, and some less so. Economists have defined strong, weak, and other kinds of “efficiency.” No matter how we define it, though, at its core the EMH acknowledges the following more or less true fact of life: It is difficult or well-nigh impossible to successfully and consistently predict what is going to happen to a stock’s price tomorrow based on all the information you have today.

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MODELING THE RISK OF UNDERLIERS As described earlier, replication begins with the science, the descriptive model of underlier behavior. Modern portfolio theory rests on the efficient 18 THE VOLATILITY SMILE market hypothesis (EMH), a framework that has come under renewed and very severe attack since the onset of the great financial crisis of 2007–2008. Let’s try to understand what it proposes. The Efficient Market Hypothesis Empirically, no one is very good at stock price prediction, whether using magical thinking or deep fundamental analysis. To be sure, there have been a few investors who have significantly outperformed the market in the past. Whether you believe their performance was due to luck or to skill, to significantly outperform the market you do not need to be very good at stock price prediction.

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Converting the experience of failed attempts at systematic stock price prediction into a hypothesis was a fiendishly clever jiu-jitsu response on the part of economists. It was an attempt to turn weakness into strength: “I can’t figure out how things work, so I’ll make the inability to do that a principle.” Uncertainty, Risk, and Return It might seem as though the efficient market hypothesis claims that the stock’s price and value are identical, and that nothing more can be said. That’s not the case. Let’s proceed to understand how the assumption of efficient markets can lead to a model for valuing securities. The elephant in the room of finance, as in the realm of all things human, is the unknown future.

Beyond Diversification: What Every Investor Needs to Know About Asset Allocation
by Sebastien Page
Published 4 Nov 2020

Similarly, at some point, the finance student should be shown the effect of replacing [the model’s assumptions about borrowing at the risk-free rate and shorting] with more realistic constraints. Other academics have expressed broader misgivings about the model, from both the theoretical and the empirical perspectives. In a 2004 paper titled “The Capital Asset Pricing Model: Theory and Evidence,” published in the Journal of Economic Perspectives, Eugene Fama and Kenneth French attack the CAPM much more directly than Markowitz: In the end, we argue that whether the model’s problems reflect weaknesses in the theory or in its empirical implementation, the failure of the CAPM in empirical tests implies that most applications of the model are invalid. Ouch.

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In the end, better return and risk forecasts and a thoughtful portfolio construction process will allow these theories to perform better in practice. Quantitative methods, as well as the availability and analysis of data and information, have produced sophisticated models that have improved market efficiency. Proponents of the efficient market hypothesis must explain them in simple words, and they must interpret results in the context of their theoretical foundations. Sébastien did a great job on this book. But I’m a tough grader. I give him a solid “A–.” Jean-Paul Page Retired Professor of Finance Université de Sherbrooke, Québec, Canada Acknowledgments I DECIDED TO WRITE THIS BOOK WHILE OUT ON A LONG trail run.

The Road to Ruin: The Global Elites' Secret Plan for the Next Financial Crisis
by James Rickards
Published 15 Nov 2016

In truth, it hasn’t. Neo-Keynesian economics has held sway for just seventy years since its inception by MIT’s Paul Samuelson in 1947. Monetarism has been intellectually dominant for about sixty years since it emerged from the University of Chicago under Milton Friedman in the 1960s. Eugene Fama’s efficient markets hypothesis percolated in academic studies in the 1960s, yet only started to exert market influence in the 1970s with the options pricing model of Fischer Black, Myron Scholes, and Robert Merton. The Black-Scholes model enabled derivatives and leverage. David Ricardo’s theory of comparative advantage is two hundred years old, yet was first implemented in a widespread rules-based way after 1947 in the General Agreement on Tariffs and Trade.

Woke, Inc: Inside Corporate America's Social Justice Scam
by Vivek Ramaswamy
Published 16 Aug 2021

They’re high-paid bureaucrats charged with balancing the interests of founders, investors, and employees. These managers often make handsome salaries, but they own much less of the company than founders and investors do. In general, they’re not billionaires. And they’re not playing the capitalist game just for money. They’re playing for power. Academics like Michael Jensen and Eugene Fama have commented at length about incentive misalignments between hired corporate managers and their shareholders. They wrote a famous paper in 1998 titled “Separation of Ownership and Control,” which made the basic observation that managers own very little of firms yet wield day-to-day control of them.4 And that in turn creates so-called “agency costs,” an economic term referring to the value an entity loses when it outsources some of its decision-making to an entity with different interests.

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Because Wall Street tends to focus on the profit line at the bottom of an income statement in a given year, turning a blind eye to how a company can deploy its balance sheet into investment that generates even more profits in the future, even if that comes at the expense of profitability in the near term. Of course, that doesn’t make any sense. It’s one of many reasons why the efficient market hypothesis is a load of garbage. But the good news is that it’s what allowed people like Warren Buffett to get rich and people like me to build successful companies. I was able to pay a small upfront payment—often just a few million dollars—for drugs that could be worth tens or hundreds of times more.

The Tyranny of Nostalgia: Half a Century of British Economic Decline
by Russell Jones
Published 15 Jan 2023

Policy should therefore be aimed at increasing the incentives for individuals to minimize their leisure time, by cutting income taxes and reducing unemployment and other social security benefits. In the same vein as the REH and RBC theory was the efficient markets hypothesis (EMH), which was popularized by another Chicago economist, Eugene Fama. Fama’s central assertion was that financial markets work perfectly. An individual stock price will accurately embody the knowledge and understanding of financial analysts, investors and the firm’s management about its earnings potential. In the case of commodities, spot prices will reflect everything known about resource stocks.

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A consensus had developed about the appropriate macroeconomic framework of thought, and about how macroeconomic policy should be conducted. The arcane Panglossian certainties of new classical theory, which embodied elements of monetarism, the rational expectations hypothesis (REH), real business cycle (RBC) theory and the efficient markets hypothesis (EMH) had been synthesised with new Keynesianism, or the attempt to incorporate certain Keynesian features into micro-founded models, by emphasizing how market ‘frictions’ could cause deviations from the optimal level of output. The stickiness of wages and prices within an REH framework was explained by considerations such as imperfect information and imperfect competition.

Debunking Economics - Revised, Expanded and Integrated Edition: The Naked Emperor Dethroned?
by Steve Keen
Published 21 Sep 2011

Addendum: Fama overboard Eugene Fama and his collaborator Kenneth French played a key role in promoting the efficient markets hypothesis, right from Fama’s first major paper while still a PhD student, in which he stated that: ‘For the purposes of most investors the efficient markets model seems a good first (and second) approximation to reality. In short, the evidence in support of the efficient markets model is extensive, and (somewhat uniquely in economics) contradictory evidence is sparse’ (Fama 1970: 416). Since then, Fama has become almost synonymous with the efficient markets hypothesis – he, rather than Sharpe, is the author referred to as the originator of the hypothesis in most textbooks on finance.

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While some fudging has been allowed to make membership possible in the first place, when an economic crisis eventually strikes, Europe’s governments may be compelled to impose austerity upon economies which will be in desperate need of a stimulus (ibid.: 212–13). The Efficient Markets Hypothesis encouraging debt-financed speculation [According to the Efficient Markets Hypothesis] The trading profile of the stock market should therefore be like that of an almost extinct volcano. Instead, even back in the 1960s when this [Sharpe] paper was written, the stock market behaved like a very active volcano. It has become even more so since, and in 1987 it did a reasonable, though short-lived, impression of Krakatau.

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Partly for this reason, his thesis was received poorly by the economics profession, and his insights were swamped by the rapid adoption of Hicks’s IS-LM analysis after the publication of Keynes’s General Theory.9 After the Great Depression, economists continued to cite his pre-Crash work on finance, while his debt-deflation theory was largely ignored.10 As a result, the antipathy he saw between the formal concept of equilibrium and the actual performance of asset markets was also ignored. Equilibrium once again became the defining feature of the economic analysis of finance. This process reached its zenith with the development of what is known as the ‘efficient markets hypothesis.’ The efficient markets hypothesis Non-economists often surmise that the term ‘efficient’ refers to the speed at which operations take place on the stock market, and/or the cost per transaction. Since the former has risen and the latter fallen dramatically with computers, the proposition that the stock market is efficient appears sensible.

The Default Line: The Inside Story of People, Banks and Entire Nations on the Edge
by Faisal Islam
Published 28 Aug 2013

‘Milton Friedman was right about some things, wrong about others, but maybe we should all apologise for not grasping the fragile nature of the banking system.’ Would Friedman be turning in his grave? Lucas pointed out that he would have backed a more tightly regulated banking system with ‘100 per cent reserves’. He defended the ‘efficient markets hypothesis’, the intellectual basis of pre-crisis financialisation, as ‘a law of nature’, but conceded his colleague Eugene Fama might have been wrong in naming it ‘efficient’. So there was a sliver of self-doubt. Three years on, and Elkhart was back on its feet. Un-employment had fallen from 20 to 8 per cent. Jewellers who in 2009 had been tempting residents to pawn their gold teeth were now back to selling engagement rings.

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Amazingly, in November 2006, on behalf of the mortgage-seekers of Britain, the Northern Rock roadshow reached Africa. Scarce African liquidity, which could have funded local infrastructure, was instead diverted into Northern Rock to fund instant negative-equity mortgages at the very top of the UK housing bubble. For half a century the ‘efficient markets hypothesis’ conquered all in financial thinking. Of the many refutations of the hypothesis since the crisis, this African investment in Northern Rock stands out as one of the most egregious examples. Northern Rock did not itself slice up all the risk into CDOs. The Rock’s methods were relatively simple.

Portfolio Design: A Modern Approach to Asset Allocation
by R. Marston
Published 29 Mar 2011

For the past two decades, many investment advisors have divided their U.S. stock allocations along the value-growth dimension. Since portfolios are also typically divided by size, many of these same advisors divide portfolios into four quadrants called style boxes: large-cap value and growth and small-cap value and growth. Two influential papers by Eugene Fama and Kenneth French present evidence that book-to-market and size explain a large portion of the cross-section variation of stocks, so it makes sense to divide portfolios along these two dimensions.1 We will examine the chief characteristics of value and growth indexes, beginning with a description of large-cap value and growth stocks.

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, Financial Analyst Journal (March-April). Banz, Rolf W., 1981, “The Relation between Return and Market Value of Common Stocks, ”Journal of Financial Economics (March), pp. 3–18. Basu, Sanjoy, 1977, “Investment Performance of Common Stocks in Relation to Their Price-Earnings Ratios: A Test of the Efficient Market Hypothesis,” Journal of Finance (June), pp. 663–682. Bernstein Wealth Management Research, 2006, Hedge Funds: Too Much of a Good Thing?, Bernstein Global Wealth Management (June). Black, Fischer, and Robert Litterman, 1992, “Global Portfolio Optimization,” Financial Analysts Journal (September-October), pp. 28–43.

Extreme Money: Masters of the Universe and the Cult of Risk
by Satyajit Das
Published 14 Oct 2011

Random movements in prices, devoid of any trend or cycle, were a depressing prospect for economists. Maurice Kendall, a British statistician, described it as the work of “the Demon of Chance,” randomly drawing a number from a distribution of possible price changes, which, when added to today’s price, determined the next price. While working for a stock market newsletter, Eugene Fama noticed patterns in stock prices that would appear and disappear rapidly. In his doctoral dissertation, he laid out the argument that stock prices were random, reflecting all available information relevant to its value. Prices followed a random walk and market participants could not systematically profit from market inefficiencies.

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The physicist Paul Dirac observed that: “In physics, we try to tell people in such a way that they understand something that nobody knew before. In the case of poetry, it’s the exact opposite.”6 Economics, as practiced at Chicago, with its mix of dogma, political fundamentalism, and mathematics, was neither poetry nor physics. Theories—rational expectations, real business cycle theory, portfolio theory, efficient market hypothesis, capital structure theory, capital asset pricing models, option pricing, agency theory—rolled off the academic production line. Many economists received recognition in the form of the Nobel prize in Economics (technically the “Severige Riksbank [Swedish Central Bank] Prize in Economic Sciences in Memory of Alfred Nobel” founded in 1968).

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Michael Jensen, a graduate student at Chicago, used a measure developed by Sharpe called the information ratio to compare actual returns earned by investment managers adjusting for the risk taken. Jensen found that few funds outperformed the broad market. On average, investors buying all the stocks in the market would earn higher returns with lower risk. Fund managers with high returns simply took higher risk rather than possessing supernatural skill. Demon of Chance The efficient market hypothesis (EMH) stated that the stock prices followed a random walk, a formal mathematical statement of a trajectory consisting of successive random steps. Pioneers Jules Regnault (in the nineteenth century) and Louis Bachelier (early twentieth century) had discovered that short-term price changes were random—a coin toss could predict up or down moves.

Expected Returns: An Investor's Guide to Harvesting Market Rewards
by Antti Ilmanen
Published 4 Apr 2011

As investors (principals) try to learn about a manager’s (agent’s) skill from his past performance and effectively chase returns, the resulting fund flows push prices away from fair values, inducing short-term momentum and long-term reversal patterns. 5.3 DETOUR: A BRIEF SURVEY OF THE EFFICIENT MARKETS HYPOTHESIS Before turning to behavioral finance, it is appropriate to briefly survey the efficient markets hypothesis (EMH). The classic statement from Fama (1970) is that markets are informationally efficient if “prices reflect all available information”. The EMH is also closely tied to the assumption of investor rationality. The main practical implication of the EMH is investors’ inability to consistently beat the market.

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Index AAA/AA/A-rated bonds absolute valuation academic investors active investing active risk puzzle (Litterman) active strategies adaptive markets hypothesis (Lo) advisors, CTAs agriculture alpha—beta barbell alpha—beta separation alphas CAPM currency carry hedge funds long horizon investors portable alpha alternative assets assets list commodities hedge funds liquidity momentum strategies PE funds premia real estate risk factors alternative betas AM see arithmetic mean ambiguity aversion Amihud, Yakov announcement days arbitrage behavioral finance CRP front-end trading equity value strategies term structure models Argentina arithmetic mean (AM) art investing asset classes 1990—2009 alternative assets “bad times” performance currency carry derivatives foreign exchange forward-looking indicators growth sensitivities historical returns inflation long history momentum strategies performance 1990—2009 profitable strategies risk factors style diversification traditional trend following understanding returns value strategies volatility selling world wealth assets 1968—2007 asset richening AUM Berk—Green management model cyclical variation empirical “horse races” ERPC feedback loops forward-looking measures growth illiquidity liquidity long-horizon investors market relations multiple asset classes prices/pricing privately held real assets risky assets seasonal regularities survey-based returns tactical forecasting tail risks time-varying illiquidity premia volatility see also asset classes assets under management (AUM) asymmetric information asymmetric returns asymmetric risk at-the-money (ATM) options seasonal regularities tail risks volatility selling attention bias AUM see assets under management BAB see betting against beta backfill bias backwardation “bad times” carry strategies catastrophes crashes crises inflation rare disasters bank credibility Bank of England Barcap Index BBB-rated bonds behavioral finance applications arbitrage biases cross-sectional trading heuristics historical aspects macro-inefficiencies micro-inefficiencies momentum over/underreaction preferences prospect theory psychology rational learning reversal effects speculative bubbles value stocks BEI see break-even inflation benchmarks, view-based expected returns Berk—Green asset management model Bernstein, Peter betas alpha—beta barbell BAB currency carry equity hedge funds long-horizon investors risk time-varying betting against beta (BAB) biases attention behavioral finance confirmation conservatism currency carry downgrading extrapolation forward rate hedge funds heuristic simplifications high equity premium hindsight historical returns learning limits memory momentum overconfidence overfitting overoptimism reporting representativeness reversal tendencies self-attribution self-deception survey data terminology volatility selling binary timing model Black—Litterman optimizers Black—Scholes (BS) option-pricing formula Black—Scholes—Merton (BSM) world blind men and elephant poem (Saxe) bond risk premium (BRP) approximate identities bond yield business cycles covariance risk cyclical factors decomposed-year Treasury yield drivers ex ante measures historical returns inflation interpreting BRP IRP macro-finance models nominal bonds realized/excess return safe haven premium supply—demand survey-based returns tactical forecasting targets terminology theories YC bonds AAA/AA/A-rated balanced portfolios BBB-rated credit spreads ERPB government historical records HY bonds IG bonds inflation-linked long-term nominal non-government relative valuation stock—bond correlation top-rated yields see also bond risk premium; corporate bonds booms break-even inflation (BEI) Bretton Woods system BRIC countries BRP see bond risk premium BSM see Black—Scholes—Merton bubbles absolute valuation memory bias money illusion real estate Shiller’s four elements speculative Buffet, Warren building block approach business cycles asset returns economic regime analysis ex ante indicators realized returns buybacks B-S see Black—Scholes option-pricing formula C-P BRP see Cochrane—Piazzesi BRP forward rate curve calls seasonal regularities tail risks volatility selling Campbell, John Campbell—Cochrane habit formation model Capital Asset Pricing Model (CAPM) alphas carry strategies Consumption CAPM covariance with “bad times” disagreement models ERP Intertemporal CAPM liquidity-adjusted market frictions market price equation multiple risk factors risk factors risk-adjusted returns risk-based models skewness stock—bond correlation supply—demand volatility Capital Ideas (Bernstein) capitalism capitalization (cap) rate CAPM see Capital Asset Pricing Model carry strategies 1990—2009 active investing asset classes business cycles credit carry currency ERP financing rates foreign exchange forward-looking indicators forward-looking measures generic proxy role historical returns long-horizon investors non-zero yield spreads real asset investing roll Sharpe ratios 2008 slide tactical forecasting cash, ERPC cash flow catastrophes see also “bad times” CAY see consumption/wealth ratio CCW see covered call writing CDOs see collateralized debt obligations CDSs see credit default swaps central banks Chen three-factor stock returns model China Citi (Il—)Liquidity indices Cochrane—Piazzesi BRP (C-P BRP) forward rate curve see also Campbell—Cochrane collateral return collateralized debt obligations (CDOs) comfortable approaches commodities characteristics equity value strategies excess returns expected returns expected risk premia futures historical returns inflation momentum return decomposition returns 1984—2009 supply—demand seasonals term structure trading advisors value indicators commodity momentum performance rational stories simple strategies trend following tweaks when it works well why it works see also momentum strategies commodity trading advisors (CTAs) composite ranking cross-asset selection models compound returns conditioners confirmation bias conservatism constant expected returns constant relative risk aversion (CRRA) Consumption CAPM consumption/wealth ratio (CAY) contemporaneous correlation contrarian strategies blunders feedback loops forward indication approach see also reversal convenience yield corporate bonds credit spreads CRP forward-looking indicators front-end trading IG bonds liquidity sample-specific valuation tactical forecasting correlation asset returns correlation premium correlation risk default correlations equities implied risk factors tail risks costs control currency carry enhancing returns taxes trading costs country-specific vulnerability indices covariance with “bad times” covariance risk risk factors covered call writing (CCW) crashes markets see also “bad times” credit default swaps (CDSs) credit-pricing models credit risk credit risk premium (CRP) analytical models attractive opportunities business cycles credit default swaps credit spreads decomposing credit spread default correlations emerging markets debt front-end trading historical excess returns IG bonds low ex post premia mortgage-backed securities non-government debt portfolio risk reduced-form credit-pricing models reward—risk single-name risk swap—Treasury spreads tactical forecasting terminology theory credit spreads AAA/AA/A-rated bonds BBB-rated bonds business cycles CRP cyclical effects decomposition empirical “horse races” forward-looking indicators high-yield bonds rolling yield top-rated bonds volatility yield-level dependence credit and tactical forecasting creditworthiness crises 2007—2008 crisis currency carry liquidity money markets see also “bad times” cross-asset selection forecasting models cross-sectional market relations cross-sectional trading CRP see credit risk premium CRRA see constant relative risk aversion CTAs see commodity trading advisors currency base of returns carry empirical “horse races” equity value strategies inflation see also foreign exchange currency carry baseline variants combining carry conditioners costs diversification emerging markets ex ante opportunity financial crashes foreign exchange historical returns hyperinflation indicators interpreting evidence maturities pairwise carry trading portfolio construction ranking models regime indicators seasonals selection biases strategy improvements “timing” the strategy trading horizons unwind episodes why strategies work cyclical effects credit spreads growth seasonal regularities see also business cycles D/P see dividend yield data mining see also overfitting; selection bias data sources of time series data series construction day-of-the-week effect DDM see dividend discount model debt supercycle default correlations, CDOs default rates, HY bonds deflation delta hedging demand see supply—demand demographics derivatives Dimson, Elroy direct hedge funds disagreement models discount rates discounted cash flows discretionary managers disinflation disposition effect distress diversification currency carry drawdown control long-horizon investors return risk factors style diversification return (DR) dividend discount model (DDM) equities ERP forward-looking indicators growth rate debates dividend growth dividend yield (D/P) DJCS HF index dollars base of returns cost averaging currency carry foreign exchange downgrading bias downside beta DR see diversification return drawdown control duration risk duration timing dynamic strategies equity value strategies portfolio construction risk factors E/P see earnings/price ratio earnings E/P ratio EPS equity returns forecasts growth rates yield see also earnings/price ratio earnings-per-share (EPS) earnings/price (E/P) ratio absolute valuation drivers forward-looking indicators measures choices relative valuation value measures economic growth see also growth efficiency behavioral finance macro-inefficiencies market inefficiency micro-inefficiencies efficient markets hypothesis (EMH) elephant and blind men poem (Saxe) EMBI indices emerging markets carry strategies currency carry debt equity returns future trends growth EMH see efficient markets hypothesis empirical multi-factor finance models endogenous return and risk feedback loops market timing research endowments energy sector commodity momentum trend following volatility selling enhancing returns costs horizon investors risk management skill EPS see earnings per share equilibrium accounting equilibrium model equities 1990—2009 business cycles carry strategies correlation premium empirical “horse races” forward-looking indicators inflation long history momentum sample-specific valuation tactical forecasting ten-year rolling averages value strategies see also stock . . .

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I confess: I have been obsessed with expected returns. The passion for the topic arose in as different places as the Bank of Finland in Helsinki and the UofC campus in Hyde Park. I earned my finance doctorate at the University of Chicago Business School (now the Booth School of Business) in the early 1990s, with Professors Eugene Fama and Kenneth French as my dissertation chairmen. In many minds this background puts me squarely in the efficient markets’ camp. However, we Chicago finance students were not taught a dogma. Instead, we were given a lifelong desire to learn more about financial markets with the emphasis on an empirical approach: let ideas compete freely and let data be the judge.

The Shifts and the Shocks: What We've Learned--And Have Still to Learn--From the Financial Crisis
by Martin Wolf
Published 24 Nov 2015

Moreover, the passage of time and the experience of a long period of financial stability had robbed the Western world of the terror of financial instability born in the 1930s. At the same time, economics provided theories justifying the proposition that free markets would allocate resources optimally. We saw the rise, for example, of the efficient market hypothesis associated with Chicago University’s Nobel laureate Eugene Fama and of belief in shareholder value maximization associated with Harvard University’s Michael Jensen. Beyond these intellectual arguments in favour of financial liberalization there were also practical arguments against regulation. Over time, it was found increasingly difficult to make the regulations that existed stick, as financial actors increasingly found ways around them.

Triumph of the Optimists: 101 Years of Global Investment Returns
by Elroy Dimson , Paul Marsh and Mike Staunton
Published 3 Feb 2002

Since the 1960s, many articles such as Breen (1968) and Basu (1977) had recorded superior returns from buying stocks with low price to earnings ratios. Other measures of value were likely to generate similar results. In those days, deviations from market efficiency were often explained away as a consequence of poor research methods. What was different in the 1990s was that Eugene Fama, the pre-eminent believer in the capital asset pricing model and market efficiency, was the author of much of the research. As Haugen (1999) put it: “The reason the Fama-French study made headlines was that…the Pope said God was dead.” Figure 10-6: International evidence on the value-growth effect based on book-to-market 0.6 Value-growth return premium (% per month) .52 .37 0.4 0.3 .52 .49 0.5 .29 .29 .27 .27 .26 0.2 .18 .17 Swi UK .14 .10 0.1 0.0 -0.1 -0.2 -.24 -0.3 Aus Bel Can Fra Ger Ita Jap Neth Swe Source: Authors’ calculations using IIA Indexes over research periods used in various studies US HK Sing Chapter 10 Stock returns: value versus growth 147 Despite the contribution of Fama and others to the evidence, and the competing explanations for why one might expect to observe a premium, the robustness of the value-growth premium remains a matter of dispute (see Shleifer, 2000, and Hawawini and Keim, 2000).

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Journal of Financial Economics 9: 3–18 Barclays Capital, 1999, Equity-Gilt Study. London: Barclays Capital Barsky, J., and B. De Long, 1993, Why does the stock market fluctuate? Quarterly Journal of Economics 108: 291–311 Basu, S., 1977, The investment performance of common stocks in relation to their priceearnings ratios a test of the efficient markets hypothesis. Journal of Finance 32: 663–682 Bernstein, P.L., 1997, What rate of return can you reasonably expect…or what can the long run tell us about the short run? Financial Analysts Journal 53(2): 20–28 316 References 317 Bianchi, B., 1979, Appendice statistica: il rendimento del consolidato dal 1862 al 1946, in Vicarelli, F.

The Intelligent Investor (Collins Business Essentials)
by Benjamin Graham and Jason Zweig
Published 1 Jan 1949

Daddy Knows Best became such gospel that, by 1999, only 3.7% of the companies that first sold their stock to the public that year paid a dividend—down from an average of 72.1% of all IPOs in the 1960s.9 Just look at how the percentage of companies paying dividends (shown in the dark area) has withered away: FIGURE 19-1 Who Pays Dividends? Source: Eugene Fama and Kenneth French, “Disappearing Dividends,” Journal of Financial Economics, April 2001. But Daddy Knows Best was nothing but bunk. While some companies put their cash to good use, many more fell into two other categories: those that simply wasted it, and those that piled it up far faster than they could possibly spend it.

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Du Pont, Glore, Forgan & Co., dual-purpose funds due diligence Dundee, Angelo Durand, David e*Trade “earning power,” earnings: and advice; average; and bargains; on capital funds; “consensus” about; debt and profits on capital (1950–69); and dividends; and expectations for investors; hiding true; and history and forecasting of stock market; inflation and; and margin of safety; and market fluctuations; owner; and per-share earnings; and performance (1871–1970); and portfolio policy for aggressive investors; and portfolio policy for defensive investors; real; and repurchase plans; and security analysis; and speculation; and stock selection for aggressive investors; and stock selection for defensive investors. See also “earning power”; per-share earnings; price/earnings ratio; specific company or type of security earnings-covered test Eastman Kodak Co. EDGAR database Edison Electric Light Co. Edward VII (king of Great Britain), “efficient markets hypothesis” (EMH) Electric Autolite Co. Electronic Data Systems electronics industry Elias, David Ellis, Charles ELTRA Corp. EMC Corp. emerging-market nations Emerson, Ralph Waldo Emerson Electric Co. Emery Air Freight Emhart Corp. employee-purchase plans employees: stock options for.

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* Only a few major rail stocks now remain, including Burlington Northern, CSX, Norfolk Southern, and Union Pacific. The advice in this section is at least as relevant to airline stocks today—with their massive current losses and a half-century of almost incessantly poor results—as it was to railroads in Graham’s day. * Graham is summarizing the “efficient markets hypothesis,” or EMH, an academic theory claiming that the price of each stock incorporates all publicly available information about the company. With millions of investors scouring the market every day, it is unlikely that severe mispricings can persist for long. An old joke has two finance professors walking along the sidewalk; when one spots a $20 bill and bends over to pick it up, the other grabs his arm and says, “Don’t bother.

Buffett
by Roger Lowenstein
Published 24 Jul 2013

In place of the cold, “unromantic” investor of Brealey and Myers, Shiller’s respondents reported sweaty palms, rapid pulse rates, and hypertension. On average, they had checked prices thirty-five times. The survey presented a microcosm of crowd psychology in action, with 40 percent of the institutional investors experiencing “a contagion of fear from other investors.”42 In another blow, Eugene Fama demonstrated that the beta of a stock had no relation to its actual return.43 Nobel prizes had been awarded for treatises on beta; now, it developed, beta was useless. But analysts and academics continued to use it. Definitions were rejiggled here and there, but the structure was left intact. Indeed, as the Economist reported, the theory itself lived on, despite the “awkward” facts.

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Buffett was asked to speak on behalf of Graham-and-Dodders, the University of Rochester’s Michael C. Jensen for the theorists. A devout believer, Jensen had written in 1978: I believe there is no other proposition in economics which has more solid empirical evidence supporting it than the Efficient Market Hypothesis.30 Indeed, he had warned dissenters that the theory was “accepted as a fact of life, and a scholar who purports to model behavior in a manner which violates it faces a difficult task of justification.”31 Since Jensen’s encyclical, the theory, and particularly the concept of beta, had come under attack.

The Snowball: Warren Buffett and the Business of Life
by Alice Schroeder
Published 1 Sep 2008

These academics had started by positing the reasonable but not necessarily obvious truth that if a whole lot of people were trying to be better than average, they would become the average. Paul Samuelson, an MIT economist, revived and circulated the 1900 work of Louis Bachelier, who observed that the market is made up of speculators who cohere into a whole that operates according to a “random walk.”38 A professor from the University of Chicago, Eugene Fama, took Bachelier’s work and tested it empirically in the modern-day market, which he described as “efficient.” The scrabbling efforts of legions of investors to beat the market made those very efforts futile, he said. Yet an army of professionals had sprung up who charged everything from modest fees to the soon-to-be-legendary hedge-fund cut of “two-and-twenty”(two percent of assets and twenty percent of returns) for the privilege of managing an investor’s money and trying to predict the future behavior of stocks.

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He said the best way to make money in the market was to simply buy an index of the market itself without paying the high fees that the toll-takers charged. Over the long term, the market tended to outperform bonds, so investors would receive the payback from the entire economy’s growth. So far, so good. The professors who had discovered this efficient-market hypothesis (EMH) kept hacking away at their computers over the years, however, to turn these ideas into an even tighter version, one that had the purity and rigor of physics and mathematics, one to which there could be no exceptions. They concluded that nobody could beat the average, that the market was so efficient that the price of a stock at any time must reflect every piece of public information about a company.

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It was what he did with the information the Wall Street Journal gave him, however, that made him a superior investor. If a monkey got the Wall Street Journal in its driveway every night just before midnight, the monkey still could not match Buffett’s investing record by throwing darts. Buffett made sport of the controversy by playing with a Wall Street Journal dartboard in his office. The efficient-market hypothesis invalidated him, however. Furthermore, it invalidated Ben Graham. That would not do. He and Munger saw these academics as holders of witch doctorates.42 Their theory peddled bafflemath, teaching a whole generation of students something disprovable. They offended Buffett’s reverence for rational thinking and for the profession of teaching.