BARBERIS AND THALER
exhibit more overconfidence than laymen, particularly when they receive only limited feedback about their predictions. Finally, in a review of dozens of studies on the topic, Camerer and Hogarth (1999, p. 7) con- clude that while incentives can sometimes reduce the biases people dis- play, “no replicated study has made rationality violations disappear purely by raising incentives.”
An essential ingredient of any model trying to understand asset prices or trading behavior is an assumption about investor preferences, or about how investors evaluate risky gambles. The vast majority of models assume that investors evaluate gambles according to the expected utility frame- work, EU henceforth. The theoretical motivation for this goes back to von Neumann and Morgenstern (1944), VNM henceforth, who show that if preferences satisfy a number of plausible axioms—completeness, transitiv- ity, continuity, and independence—then they can be represented by the expectation of a utility function.
Unfortunately, experimental work in the decades after VNM has shown that people systematically violate EU theory when choosing among risky gambles. In response to this, there has been an explosion of work on so- called non-EU theories, all of them trying to do a better job of matching the experimental evidence. Some of the better known models include weighted- utility theory (Chew and MacCrimmon 1979, Chew 1983), implicit EU (Chew 1989, Dekel 1986), disappointment aversion (Gul 1991), regret the- ory (Bell 1982, Loomes and Sugden 1982), rank-dependent utility theories (Quiggin 1982; Segal 1987, 1989; Yaari 1987), and prospect theory (Kah- neman and Tversky 1979, Tversky and Kahneman 1992).
Should financial economists be interested in any of these alternatives to expected utility? It may be that EU theory is a good approximation to how people evaluate a risky gamble like the stock market, even if it does not ex- plain attitudes to the kinds of gambles studied in experimental settings. On the other hand, the difficulty the EU approach has encountered in trying to explain basic facts about the stock market suggests that it may be worth taking a closer look at the experimental evidence. Indeed, recent work in behavioral finance has argued that some of the lessons we learn from viola- tions of EU are central to understanding a number of financial phenomena.
Of all the non-EU theories, prospect theory may be the most promising for financial applications, and we discuss it in detail. The reason we focus on this theory is, quite simply, that it is the most successful at capturing the experimental results. In a way, this is not surprising. Most of the other