Misbehaving: The Making of Behavioral Economics

by Richard H. Thaler

  CRSP released its first database in 1964, and research in the field immediately took off, with University of Chicago locals leading the way. Chief among these were Miller, Fama, and a group of exceptional graduate students including Michael Jensen, Richard Roll (a distinguished scholar and longtime professor at UCLA), and Myron Scholes, the co-inventor of the Black–Scholes option-pricing model. Research proceeded quickly. By 1970 the theory and evidence supporting the EMH was sufficiently well-established that Fama was able to publish a comprehensive review of the literature that stood for many years as the efficient market bible. And just eight years after Fama had established this foundation, Jensen would publish the sentence declaring the efficient market hypothesis to be proven. Ironically, the sentence appears in the preface to a special issue of the Journal of Financial Economics that was devoted to anomalies, that is, papers reporting purported departures from the efficient market hypothesis.

  The confidence Jensen and others had in the EMH was perhaps based as much in the compelling logic of the idea as it was in the empirical data. When it came to financial markets, the invisible handwave was damn convincing, and no one was putting up much resistance. Furthermore, the 1970s was a period in which a similar revolution was taking place in macroeconomics. Models based on rational expectations were on the rise, and the popularity of Keynesian economics amongst academic economists was on the decline. Perhaps for this reason, Keynes’s writings were no longer required reading by graduate students. This is unfortunate, because had he been alive, Keynes might have made the debate more even-handed. He was a true forerunner of behavioral finance.

  Keynes is now remembered primarily for his contributions to macroeconomics and especially for his controversial argument that governments should use fiscal policy to stimulate demand during recessions or depressions. Regardless of your views about Keynesian macroeconomics, you would be foolish to dismiss his thoughts on financial markets. To me, the most insightful chapter of his most famous book, The General Theory of Employment, Interest and Money, is devoted to this subject. Keynes’s observations were based in part on his considerable experience as an investor. For many years, he successfully managed the portfolio of his college at Cambridge, where he pioneered the idea of endowments investing in equities.

  As we discussed earlier, many economists of his generation had pretty good intuitions about human behavior, but Keynes was particularly insightful on this front. He thought that emotions, or what he called “animal spirits,” played an important role in individual decision-making, including investment decisions. Interestingly, Keynes thought markets were more “efficient,” to use the modern word, in an earlier period at the beginning of the twentieth century when managers owned most of the shares in a company and knew what the company was worth. He believed that as shares became more widely dispersed, “the element of real knowledge in the valuation of investments by those who own them or contemplate purchasing them . . . seriously declined.”

  By the time he was writing the General Theory in the mid-1930s, Keynes had concluded that markets had gone a little crazy. “Day-to-day fluctuations in the profits of existing investments, which are obviously of an ephemeral and non-significant character, tend to have an altogether excessive, and even an absurd, influence on the market.” To buttress his point, he noted the fact that shares of ice companies were higher in summer months when sales are higher. This fact is surprising because in an efficient market, stock prices reflect the long-run value of a company, a value that should not reflect the fact that is it warm in the summer and cold in the winter. A predictable seasonal pattern in stock prices like this is strictly verboten by the EMH.¶

  Keynes was also skeptical that professional money managers would serve the role of the “smart money” that EMH defenders rely upon to keep markets efficient. Rather, he thought that the pros were more likely to ride a wave of irrational exuberance than to fight it. One reason is that it is risky to be a contrarian. “Worldly wisdom teaches that is it is better for reputation to fail conventionally than to succeed unconventionally.” Instead, Keynes thought that professional money managers were playing an intricate guessing game. He likened picking the best stocks to a common competition in the male-dominated London financial scene in the 1930s: picking out the prettiest faces from a set of photographs:

  Professional investment may be likened to those newspaper competitions in which the competitors have to pick out the six prettiest faces from a hundred photographs, the prize being awarded to the competitor whose choice most nearly corresponds to the average preferences of the competitors as a whole: so that each competitor has to pick, not those faces which he himself finds prettiest, but those which he thinks likeliest to catch the fancy of the other competitors, all of whom are looking at the problem from the same point of view. It is not a case of choosing those which, to the best of one’s judgment, are really the prettiest, nor even those which average opinion genuinely thinks the prettiest. We have reached the third degree where we devote our intelligences to anticipating what average opinion expects the average opinion to be. And there are some, I believe, who practice the fourth, fifth, and higher degrees.

  I believe that Keynes’s beauty contest analogy remains an apt description of how financial markets work, as well as of the key role played by behavioral factors, though it may be bit hard to get your head around. To understand the gist of his analogy, and appreciate its subtlety, try out this puzzle.

  Guess a number from 0 to 100 with the goal of making your guess as close as possible to two-thirds of the average guess of all those participating in the contest.

  To help you think about this puzzle, suppose there are three players who guessed 20, 30, and 40 respectively. The average guess would be 30, two-thirds of which is 20, so the person who guessed 20 would win.

  Make a guess before continuing. Really, you should try it: the rest of this chapter will be more fun if you have tried the game yourself.

  Is there anything you would have liked to ask before making your guess? If so, what would it be? We will return to it in a minute. Now, let’s ponder how someone might think about how to play this game.

  Consider what I will call a zero-level thinker. He says: “I don’t know. This seems like a math problem and I don’t like math problems, especially word problems. I guess I will pick a number at random.” Lots of people guessing a number between 0 and 100 at random will produce an average guess of 50.

  How about a first-level thinker? She says: “The rest of these players don’t like to think much, they will probably pick a number at random, averaging 50, so I should guess 33, two-thirds of 50.”

  A second-level thinker will say something like: “Most players will be first-level thinkers and think that other players are a bit dim, so they will guess 33. Therefore I will guess 22.”

  A third level thinker: “Most players will discern how the game works and will figure that most people will guess 33. As a result they will guess 22, so I will guess 15.”

  Of course, there is no convenient place to get off this train of thinking. Do you want to change your guess?

  Here is another question for you: What is the Nash equilibrium for this scenario? Named for John Nash, the subject of the popular book (and biopic) A Beautiful Mind, the Nash equilibrium in this game is a number that if everyone guessed it, no one would want to change their guess. And the only Nash equilibrium in this game is zero. To see why, suppose everyone guessed 3. Then the average guess would be 3 and you would want to guess two-thirds of that, or 2. But if everyone guessed 2 you would want to guess 1.33, and so forth. If and only if all participants guessed zero would no one want to change his or her guess.

  Perhaps you have now formulated the question that might have been worth asking before submitting your guess: who are the other players, and how much math and game theory do they know? If you are playing at your local bar, especially late in the evening, other people are probably not thinking too deeply, so you might make a guess around 33. Only i
f you are at a conference of game theorists would you want to guess a number close to zero.

  Now let’s see how this game is related to Keynes’s beauty contest. Formally, the setups are identical. In the guess-the-number game, you have to guess what other people are thinking that other people are thinking, just as in Keynes’s game. In fact, in economics, the “number guessing game” is commonly referred to as the “beauty contest.”

  This delightful game was first studied experimentally by the German economist Rosemarie Nagel, who teaches at Pompeu Fabra University in Barcelona. Thanks to the Financial Times newspaper, in 1997 I had the opportunity to replicate her findings in a large-scale experiment. The FT had asked me to write a short article about behavioral finance, and I wanted to use the guess-the-number game to illustrate Keynes’s beauty contest. Then I had an idea: could they run the game as a contest a few weeks before my article appeared? That way I could present fresh data from FT readers along with my article. The FT agreed, and British Airways offered up two business-class tickets from London to the U.S. as the prize. Based on what you know now, what would be your guess playing with this crowd?

  The winning guess was 13. The distribution of guesses is shown in figure 10. As you can see, many readers of the Financial Times were clever enough to figure out that zero was the Nash equilibrium for this game, but they were also clueless enough to think it would be the winning guess.# There were also quite a few people who guessed 1, allowing for the possibility that a few dullards might not fully “get it” and thus raise the average above zero.**

  FIGURE 10

  Many first and second level thinkers guessed 33 and 22. But what about the guesses of 99 or 100; what were those folks up to? It turns out that they all came from one student residence at Oxford University. Contestants were limited to one entry, but someone up to some mischief had completed postcards on behalf of all of his housemates. It fell to my research assistants and me to make the call on whether these entries were legal. We decided that since each card had a different name attached, we would leave them in, and collectively they moved the winning guess from 12 to 13. Luckily, no one from that house had guessed 13.

  We asked participants to write a short explanation of their logic, which we would use as a tie-breaker. Their explanations provided an unexpected bonus. Several were quite clever.††

  There was a poet who guessed zero: “So behaviourists observe a bod, an FT reader, ergo clever sod, he knows the competition and will fight ‘em, so reduces the number ad infinitum.”

  Here is a Tory who, having decided the world cannot be counted on to be rational, guessed 1:

  “The answer should be naught [0] . . . but Labour won.”

  A student who guessed 7 justified his choice: “because my dad knows an average amount about numbers and markets, and he bottled out at ten.” Note that like many young people, he underestimated his father. Had he given his father credit for thinking one level beyond the average contestant, he might have won!

  Finally, another poet who guessed 10: “Over 67 only interests fools; so over 45 implies innumeracy rules. 1 to 45 random averages 23. So logic indicates 15, leaving 10 to me.”

  As illustrated by all these FT guessers, at various levels of sophistication, we see that Keynes’s beauty contest analogy is still an apt description of what money managers try to do. Many investors call themselves “value managers,” meaning they try to buy stocks that are cheap. Others call themselves “growth managers,” meaning they try to buy stocks that will grow quickly. But of course no one is seeking to buy stocks that are expensive, or stocks of companies that will shrink. So what are all these managers really trying to do? They are trying to buy stocks that will go up in value—or, in other words, stocks that they think other investors will later decide should be worth more. And these other investors, in turn, are making their own bets on others’ future valuations.

  Buying a stock that the market does not fully appreciate today is fine, as long as the rest of the market comes around to your point of view sooner rather than later! Remember another of Keynes’s famous lines. “In the long run, we are all dead.” And the typical long run for a portfolio manager is no more than a few years—maybe even just a few months!

  ________________

  * When asked which he was more proud of, the hall of fame designation or his Nobel Prize, Gene said the former, pointing out that it had fewer recipients.

  † One of my many finance tutors over the years has been Nicholas Barberis, who was a colleague of mine for a while at the University of Chicago and now teaches at Yale. My discussion here draws upon our survey of behavioral finance (Barberis and Thaler, 2003).

  ‡ Experimental economists have conducted numerous experiments in which bubbles are predictably created in the laboratory (Smith, Suchanek, and Williams, 1988; Camerer, 1989; Barner, Feri, and Plott, 2005), but financial economists put little credence in such demonstrations, in part because they do not offer the opportunity for professionals to intervene and correct the mispricing.

  § The 2013 prize went to Gene Fama and Bob Shiller, whose debates you will read about in this chapter and in chapter 17, along with my fellow Chicago economist Lars Hansen, whose views lie somewhere in the large space between, or perhaps off to the side of, Fama and Shiller.

  ¶ Whether or not such a pattern in prices is verboten, a recent paper finds support for Keynes’s story about the price of ice companies. Firms with seasonal businesses have higher prices when their earnings are higher (Chang et al., 2014).

  # This is another case where the normative economic theory, here the Nash equilibrium of zero, does a terrible job as a descriptive theory, and is equally bad as a source of advice about what number to guess. There is now a burgeoning literature of attempts to provide better descriptive models.

  ** Another reason why some contestants guessed 1 was that they had noticed a sloppy bit of writing in the contest rules, which asked people to guess a number between 0 and 100. They thought that the “trick” was that the word “between” implied that guesses of 0 and 100 were disallowed. This had little bearing on the results, but I learned from the experience and switched the word “between” to “from”, as I did when posed the problem above.

  †† Others were not so clever. At least three people who guessed 33 reported having used the random number generating function in Excel to determine that, if people choose at random from 0 to 100, the average will be 50! Maybe I have too high hopes for the mathematical sophistication of Financial Times readers, but I would have thought they could figure out that the average of a number picked at random between 0 and 100 is 50 without using Excel. This confirmed my long-held suspicion that many people use spreadsheets as an alternative to thinking.

  22

  Does the Stock Market Overreact?

  The opportunity for me to do some research on financial markets was made possible by the first graduate student I had convinced to join me in the study of psychology and economics, Werner De Bondt. I met Werner in the fall of 1978, my first semester at Cornell. Werner, a Belgian exchange student, was by far the best student in the class I taught on economics and public policy in the fall and was again a standout in another course I taught in the spring. I encouraged him to continue his studies and get a PhD, which he did after serving a stint in the Belgian military. We had just one problem: Werner’s true love was finance, a topic about which I knew very little.

  Fortunately, although I had never taken a course in finance, I had picked up the basics while on the faculty at the University of Rochester Graduate School of Business. Many of the leading faculty members at the school were in finance, and the topic permeated the place. The plan was that I would supervise Werner’s thesis if we could figure out a way to inject psychology into the mix, and the finance faculty would make sure we used all the generally accepted financial economics methods so that in the unlikely event we stumbled onto something interesting, the results would be taken seriously. Some of my colleagues told me that
I was committing professorial malpractice by encouraging Werner to pursue this topic, but he was unconcerned. De Bondt was, and is, a true intellectual, interested only in finding truth. So he and I learned finance together, with him doing most of the teaching.

  For his thesis, Werner wanted to take a hypothesis from psychology and use it to make a prediction about some previously unobserved effect in the stock market. There were easier things to try. For instance, he might have offered a plausible behavioral explanation for some already observed effect in the stock market, as Benartzi and I had done when trying to explain why stocks earn much higher returns than bonds (the equity risk premium). But the problem with a new explanation for an old effect is that it’s hard to prove your explanation is correct.

  Take, for example, the fact of high trading volume in security markets. In a rational world there would not be very much trading—in fact, hardly any. Economists sometimes call this the Groucho Marx theorem. Groucho famously said that he would never want to belong to any club that would have him as a member. The economist’s version of this joke—predictably, not as funny—is that no rational agent will want to buy a stock that some other rational agent is willing to sell. Imagine two financial analysts, Tom and Jerry, are playing a round of golf. Tom mentions that he is thinking of buying 100 shares of Apple. Jerry says, that’s convenient, I was thinking of selling 100 shares. I could sell my shares to you and avoid the commission to my broker. Before they can agree on a deal, both think better of it. Tom realizes that Jerry is a smart guy, so asks himself, why is he selling? Jerry is thinking the same about Tom, so they call off the trade. Similarly, if everyone believed that every stock was correctly priced already—and always would be correctly priced—there would not be very much point in trading, at least not with the intent of beating the market.