Beyond Greed and Fear

by Hersh Shefrin

  1. Do financial practitioners commit errors because they rely on rules of thumb? Behavioral finance answers yes, and traditional finance answers no. Behavioral finance recognizes that practitioners use rules of thumb called heuristics to process data. One example of a rule of thumb is: “Past performance is the best predictor of future performance, so invest in a mutual fund having the best five-year record.” Now, rules of thumb are like back-of-the-envelope calculations—they are generally imperfect. Therefore, practitioners hold biased beliefs that predispose them to commit errors. For this reason, I assign the label heuristic-driven bias to the first behavioral theme. In contrast, traditional finance assumes that when processing data, practitioners use statistical tools appropriately and correctly.

  2. Does form as well as substance influence practitioners? By form, I mean the description or frame of a decision problem. Behavioral finance postulates that in addition to objective considerations, practitioners’ perceptions of risk and return are highly influenced by how decision problems are framed. For this reason, I assign the label frame dependence to the second behavioral theme. In contrast, traditional finance assumes frame independence, meaning that practitioners view all decisions through the transparent, objective lens of risk and return.

  3. Do errors and decision frames affect the prices established in the market? Behavioral finance contends that heuristic-driven bias and framing effects cause market prices to deviate from fundamental values. I assign the label inefficient markets to the third theme. In contrast, traditional finance contends that markets are efficient. Efficiency means that the price of each security coincides with fundamental value, even if some practitioners suffer from heuristic-driven bias or frame dependence.3

  Just How Pervasive Are Behavioral Phenomena?

  Behavioral phenomena play an important role in the major areas of finance: portfolio theory, asset pricing, corporate finance, and the pricing of options. These areas correspond to works recognized for Nobel prizes in economics, for the development of financial economics. To date, two such Nobel prizes have been awarded, to five recipients, for their contributions in finance.

  In 1990 Harry Markowitz, Merton Miller, and William Sharpe shared the first prize. The Nobel committee recognized Markowitz for having developed portfolio theory, Miller for laying the basis for the theory of corporate finance, and Sharpe for developing the capital asset pricing model. In 1997, the committee recognized Myron Scholes and Robert Merton for having developed option pricing theory. I have drawn on recent comments by all five Nobel laureates in order to make the connection between their work and the insights from behavioral finance.

  Why Is Behavioral Finance Important for Practitioners?

  Practitioners are prone to committing specific errors. Some are minor, and some are fatal. Behavioral finance can help practitioners recognize their own errors as well as the errors of others. Practitioners need to understand that both are important. Here is a game, called the “pick-a-number game” designed to bring out the point.

  In April 1997 the Financial Times ran a contest suggested by economist Richard Thaler.4 The paper announced that the contest winner would receive two British Airways round-trip “Club Class” tickets between London and either New York or Chicago. Readers were told to choose a whole number between 0 and 100. The winning entry would be the one closest to two-thirds of the average entry.

  The Financial Times provided the following short example to help readers understand the contest: Suppose five people enter the contest and they choose 10, 20, 30, 40 and 50. In this case, the average is 30, two-thirds of which is 20. The person who chose to enter 20 would be the winner.

  What is the point of this pick-a-number game? The point is that if you are playing to win, you need to understand how the other players are thinking. Suppose you think everyone who enters the contest will choose 20, since that is the winning choice in the example. In that case, you should choose the integer closest to two-thirds of 20, or 14.

  But you might reflect on this for a moment, and wonder whether most other entrants would also be thinking along these lines, and therefore all be planning to choose 14. In that case, your best choice would be 10. And if you kept rethinking your choice, you would eventually come down to choosing 1.5 And if everyone thinks along these lines, the winning entry will indeed be 1.

  But in a group of normal, even well-educated, people, the winning entry will not be 1. In the Financial Times contest, with two transatlantic round-trip tickets at stake, the winning choice was 13.6 If everyone chose a 1, then nobody would have made a mistake in his or her choice. But if 13 is the winning choice, then most people are making mistakes. The real point of this game is that playing sensibly requires you to have a sense of the magnitude of the other players’ errors.

  The pick-a-number game illustrates two of the three themes of behavioral finance. People commit errors in the course of making decisions; and these errors cause the prices of securities to be different from what they would have been in an error-free environment.

  Paul Gompers and Andrew Metrick (1998) document that between 1980 and 1996, there was a marked increase in institutional ownership and concentration of equities. This shift magnifies the possible market impact of mistakes made by a small group of people. As the next example illustrates, practitioners ignore the moral from the pick-a-number game at their peril.

  Consider the case of Long Term Capital Management (LTCM), a hedge fund that received considerable publicity during the second half of 1998. Three of the partners in LTCM are extremely well known—John Meriwether, who pioneered fixed-income arbitrage at Salomon Brothers, and Nobel laureates Myron Scholes and Robert Merton, mentioned earlier.7 LTCM had generated spectacular after-fee returns between 1994 and 1997.8 At year-end 1997, LTCM held more than $7 billion of capital.

  But 1998 turned out to be disastrous, as LTCM watched its $7 billion shrink to $4 billion. In September of that year, the Federal Reserve Bank of New York felt the need to organize a privately funded rescue plan in which fourteen major banks and brokerage houses contributed a total of $3.6 billion in exchange for 90 percent of LTCM’s equity. Clearly, something had gone terribly wrong.

  In fact, many things had gone wrong, but the following example is particularly illuminating. LTCM had taken large positions in two companies, Royal Dutch Petroleum and Shell Transport and Trading, that jointly owned the entity Royal Dutch/Shell. The shares of Royal Dutch Petroleum and Shell Transport trade on both the London Stock Exchange and the New York Stock Exchange. In a recent case study, Kenneth Froot and Andre Perolt (1996) point out that a corporate charter linking these two companies divides the joint cash flow of Royal Dutch/Shell between them on a 60/40 basis. Presumably, this should lock the ratio at which the shares of the two companies trade. In theory, the market value of Royal Dutch should be 1.5 times as large as the market value of Shell Transport. But as with the pick-a-number game, actual prices typically depart from what they would be in an error-free environment.9

  Interestingly, the shares of Shell Transport have traditionally traded not at parity but at an 18 percent discount relative to Royal Dutch. When the discount widened beyond 18 percent, LTCM did a “pairs” trade. They took a long position in Shell Transport and a corresponding short position in Royal Dutch, anticipating a short-term profit when the discount reverted to its traditional value. But LTCM encountered the same fate as someone who chose a 1 in the pick-a-number game. It wasn’t a winning strategy. As Business Week reported in its November 9, 1998, issue (Spiro with Laderman), the discount widened rather than narrowed.

  We are not done with Long-Term Capital Management. As we shall see in later chapters, the experiences of that particular hedge fund offer many illustrations of behavioral phenomena.

  How Behavioral Finance Developed

  Behavioral finance burgeoned when the advances made by psychologists came to the attention of economists. As noted, many of the behavioral concepts described in this volume can be found in Kahneman, Slo
vic, and Tversky’s 1982 volume. These authors’ works play a central role in the field of behavioral finance.

  Slovic’s work emphasizes misperceptions about risk. Early on, he saw the relevance of behavioral concepts for finance and discussed it in two articles. The first, pertaining to stockbrokers, appeared in the 1969 Journal of Applied Psychology. The other, pertaining to analysts and individual investors, was published in the 1972 Journal of Finance.

  Amos Tversky and Daniel Kahneman published two articles that had a profound impact on finance. Their 1974 article in Science (Tversky and Kahneman) deals with heuristic-driven errors, while their 1979 article in Econometrica (Kahneman and Tversky) deals with frame dependence.

  These last two articles strongly influenced both my work with Richard Thaler on self-control and savings behavior, and my work with Meir Statman on the “dividend puzzle.” The article addressing the dividend puzzle, so dubbed by the late Fischer Black, was published by the Journal of Financial Economics in 1984. Because he saw the limitations of the traditional approach to finance, Black enthusiastically supported the development of behavioral finance. As presidentelect of the American Finance Association, he chose to include a session on behavioral finance that I was fortunate to chair at the 1984 annual meeting.

  In July 1985, the Journal of Finance published two of the papers presented at that session. One paper, by Werner De Bondt and Richard Thaler, applied Tversky and Kahneman’s notion of representativeness to market pricing. De Bondt and Thaler argued that investors overreact to both bad news and good news. Therefore, overreaction leads past losers to become underpriced and past winners to become overpriced. The second paper, by Meir Statman and me, applied Kahneman and Tversky’s notion of framing to the realization of losses. We called this phenomenon the disposition effect, arguing that investors are predisposed to holding losers too long and selling winners too early. These two papers defined two different avenues for looking at the implications of behavioral phenomena, with one stream focusing on security prices and the other on the behavior of investors.

  In effect, the behavioral perspective brought an organized body of knowledge to bear on an approach to trading that had already been practiced for some time. De Bondt and Thaler’s work is in the tradition of Benjamin Graham and David Dodd’s notion of value investing, first described in their classic 1934 work, Security Analysis. In the late 1970s, money manager David Dreman became well known for advocating the price-to-earnings ratio (P/E) as a value measure.

  In the 1980s, scholars began to discover a host of empirical results that were not consistent with the view that market returns were determined in accordance with the capital asset pricing model (CAPM) and efficient market theory. Proponents of traditional finance regarded these findings as anomalous, and thus called them anomalies. The anomalies started with size—e.g., the small-firm effect—and kept on coming. Soon we had the January effect, the weekend effect, and the holiday effect. As they discovered new anomalies, scholars began to wonder whether traditional finance was incapable of explaining what determines security prices.

  The Reaction from Traditional Finance

  Behavioral finance and traditional finance differ sharply in respect to the three themes. So how have the proponents of traditional finance reacted? Consider first the reaction to the concept of frame dependence. In 1985, a year after the appearance of my article with Meir Statman on the dividend puzzle, the University of Chicago sponsored a conference to discuss behavioral finance.

  Nobel laureates Merton Miller and Franco Modigliani developed the traditional theory of dividends. At the Chicago conference, Miller discussed the Shefrin-Statman approach. He acknowledged that our approach might apply to his own Aunt Minnie—an interesting story perhaps, but one of many interesting stories. In fact, Miller argued, the stories were too interesting: they were distracting and diverted the attention of scholars away from the identifying the fundamental forces that drive markets. He repeated this point in the published proceedings of the conference (Miller 1986).

  One of the chapters in this book deals with the behavioral biases that led to the Orange County bankruptcy—the largest municipal bankruptcy in U.S. history—and to subsequent lawsuits that involved Merrill Lynch and many others. Merrill Lynch retained Miller’s services to assist them with their defense. In a 1997 article, Miller and coauthor David Ross argued that the bankruptcy was entirely avoidable. They may well be right. But the bankruptcy did happen—largely, I would argue, because of a series of behavioral biases. And this leads me to suggest that these biases are not too distracting, at least if our purpose is to understand major events in financial markets.

  Indeed, as I hope to make clear in this book through the use of numerous stories, behavioral phenomena are both ubiquitous and germane: ubiquitous because you will find them wherever people are making financial decisions; germane because heuristic-driven bias and framing effects are very expensive.

  In a 1987 survey of the literature on market efficiency, Robert Merton (1987b) began by reviewing a classic 1965 article by Paul Samuelson. He then moved on to discuss the challenges presented by Robert Shiller’s (1981) work on stock market volatility, the De Bondt-Thaler overreaction effect, and the Shefrin-Statman treatment of loss realization.10 At that time, Merton wrote that the evidence against market efficiency was “premature.” He pointed to technical difficulties with Shiller’s framework, weak statistical effects in the De Bondt-Thaler study, and an apparent contradiction between the prescriptions of De Bondt-Thaler and those of Shefrin-Statman.11

  Robert Merton may well have been right that in 1987 it was premature to reject market efficiency. Since 1987, however, scholars have done much work studying phenomena that involve volatility, overreaction, and loss realization, and they have resolved some of the issues Merton raised. For example, in a 1998 article Terrance Odean (1998a) confirms the Shefrin-Statman claims about realizing losers; and Odean’s study of investment performance finds no contradiction with the De Bondt-Thaler effect.12 Certainly, the experience of Long-Term Capital Management, where Merton has been extensively involved, suggests a move away from the firm conviction that markets are efficient. However, I hasten to add that rejecting market efficiency is not the same thing as having absorbed all the lessons of behavioral finance.

  Still, some tenaciously cling to the belief that markets are efficient. Eugene Fama (1998b), who pioneered work on the efficient market hypothesis, has written a more recent survey of the challenges to market efficiency presented by behavioral finance. In 1998, he published a portion of his survey in a University of Chicago Graduate School of Business magazine. The title summarizes his view: “Efficiency Survives the Attack of the Anomalies” (Fama 1998a). In this connection, I have heard Fama describe behavioral finance as nothing more than “anomalies dredging.”

  Fama’s remark about “anomalies dredging” raises two issues. The first, narrower issue, addressed in chapters 7 and 8, is whether markets are efficient. With respect to Fama’s specific concerns about market inefficiency and behavioral finance, I suggest that the weight of the evidence favors the behavioral point of view. The second, broader issue is whether there is more to behavioral finance than just market inefficiency. In other words, would heuristic-driven bias and frame dependence be irrelevant if markets were efficient? This issue will be discussed throughout the book, with the caveat that neither practitioners nor scholars can afford to ignore heuristic-driven bias and frame dependence. The mistakes are too expensive.

  Stories and Quotations

  Merton Miller and I agree that there are many interesting stories in finance. We disagree about what to do with them. Miller argues that we should ignore stories because they draw attention away from fundamental forces. I argue that we should embrace stories because they provide insight into the psychological forces that impact financial decisions and prices.

  In this book, I describe a small number of behavioral concepts and a large number of behavioral stories. The power of behavior
al finance is such that a few key concepts underlie many different stories. These stories span a lot of territory and illustrate how heuristic-driven bias and frame dependence affect the following:

  • Wall Street strategists as they predict the market

  • security analysts as they recommend stocks

  • portfolio managers as they pick stocks

  • hedge fund managers as they trade currencies

  • investment bankers as they take companies public

  • individual investors as they save for retirement

  • financial planners as they advise investors

  • corporate executives as they take over other companies

  Stories are illustrative—aids to help readers gain insight into behavioral finance. Note that I do not base general claims on stories. Rather, it is the other way around. The literature on behavioral finance contains studies documenting general phenomena; I have selected stories to illustrate the general findings.

  I quote extensively in the stories, mostly from the popular press. Quotations offer important insights into the thought processes of practitioners, and therefore into the underlying psychology. What people say provides a window into how they think, and how they think lies at the heart of behavioral finance.

  Plan of the Book

  I have organized the book around themes and applications. The rest of part I—chapters 2, 3, and 4—presents the three themes that underlie behavioral finance: heuristic-driven bias, frame dependence, and inefficient prices, respectively.