Chapter 18 A SURVEY OF BEHAVIORAL FINANCE* NICHOLAS BARBERIS University of Chicago RICHARD THALER University of Chicago Contents Abstract 1054 Keywords 1054 1.Introduction 1055 2.Limits to arbitrage 1056 2.1.Market efficiency 1056 2.2.Theory 1058 2.3.Evidence 1061 2.3.1.Twin shares 1061 2.3.2.Index inclusions 1063 2.3.3.Internet carve-outs 1064 3.Psychology 1065 3.1.Beliefs 1065 3.2.Preferences 1069 3.2.1.Prospect theory 1069 3.2.2.Ambiguity aversion 1074 4.Application:The aggregate stock market 1075 4.1.The equity premium puzzle 1078 4.1.1.Prospect theory 1079 4.1.2.Ambiguity aversion 1082 4.2.The volatility puzzle 1083 4.2.1.Beliefs 1084 4.2.2.Preferences 1086 5.Application:The cross-section of average returns 1087 5.1.Belief-based models 1092 We are very grateful to Markus Brunnermeier,George Constantinides,Kent Daniel,Milt Harris,Ming Huang.Owen Lamont,Jay Ritter,Andrei Shleifer,Jeremy Stein and Tuomo Vuolteenaho for extensive comments. Handbook of the Economics of Finance,Edited by G.M.Constantinides,M.Harris and R.Stulz 2003 Elsevier Science B.V.All rights reserved
Chapter 18 A SURVEY OF BEHAVIORAL FINANCE° NICHOLAS BARBERIS University of Chicago RICHARD THALER University of Chicago Contents Abstract 1054 Keywords 1054 1. Introduction 1055 2. Limits to arbitrage 1056 2.1. Market efficiency 1056 2.2. Theory 1058 2.3. Evidence 1061 2.3.1. Twin shares 1061 2.3.2. Index inclusions 1063 2.3.3. Internet carve-outs 1064 3. Psychology 1065 3.1. Beliefs 1065 3.2. Preferences 1069 3.2.1. Prospect theory 1069 3.2.2. Ambiguity aversion 1074 4. Application: The aggregate stock market 1075 4.1. The equity premium puzzle 1078 4.1.1. Prospect theory 1079 4.1.2. Ambiguity aversion 1082 4.2. The volatility puzzle 1083 4.2.1. Beliefs 1084 4.2.2. Preferences 1086 5. Application: The cross-section of average returns 1087 5.1. Belief-based models 1092 ° We are very grateful to Markus Brunnermeier, George Constantinides, Kent Daniel, Milt Harris, Ming Huang, Owen Lamont, Jay Ritter, Andrei Shleifer, Jeremy Stein and Tuomo Vuolteenaho for extensive comments. Handbook of the Economics of Finance, Edited by G.M. Constantinides, M. Harris and R. Stulz © 2003 Elsevier Science B.V. All rights reserved
1054 N.Barberis and R.Thaler 5.2.Belief-based models with institutional frictions 1095 5.3.Preferences 1097 6.Application:Closed-end funds and comovement 1098 6.1.Closed-end funds 1098 6.2.Comovement 1099 7.Application:Investor behavior 1101 7.1.Insufficient diversification 1101 7.2.Naive diversification 1103 7.3.Excessive trading 1103 7.4.The selling decision 1104 7.5.The buying decision 1105 8.Application:Corporate finance 1106 8.1.Security issuance,capital structure and investment 1106 8.2.Dividends 1109 8.3.Models of managerial irrationality 1111 9.Conclusion 1113 Appendix A 1115 References 1116 Abstract Behavioral finance argues that some financial phenomena can plausibly be understood using models in which some agents are not fully rational.The field has two building blocks:limits to arbitrage,which argues that it can be difficult for rational traders to undo the dislocations caused by less rational traders;and psychology.which catalogues the kinds of deviations from full rationality we might expect to see.We discuss these two topics,and then present a number of behavioral finance applications:to the aggregate stock market,to the cross-section of average returns,to individual trading behavior,and to corporate finance.We close by assessing progress in the field and speculating about its future course. Keywords behavioral finance,market efficiency,prospect theory,limits to arbitrage,investor psychology,investor behavior JEL classification:G11,G12,G30
1054 N. Barberis and R. Thaler 5.2. Belief-based models with institutional frictions 1095 5.3. Preferences 1097 6. Application: Closed-end funds and comovement 1098 6.1. Closed-end funds 1098 6.2. Comovement 1099 7. Application: Investor behavior 1101 7.1. Insufficient diversification 1101 7.2. Naive diversification 1103 7.3. Excessive trading 1103 7.4. The selling decision 1104 7.5. The buying decision 1105 8. Application: Corporate finance 1106 8.1. Security issuance, capital structure and investment 1106 8.2. Dividends 1109 8.3. Models of managerial irrationality 1111 9. Conclusion 1113 Appendix A 1115 References 1116 Abstract Behavioral finance argues that some financial phenomena can plausibly be understood using models in which some agents are not fully rational. The field has two building blocks: limits to arbitrage, which argues that it can be difficult for rational traders to undo the dislocations caused by less rational traders; and psychology, which catalogues the kinds of deviations from full rationality we might expect to see. We discuss these two topics, and then present a number of behavioral finance applications: to the aggregate stock market, to the cross-section of average returns, to individual trading behavior, and to corporate finance. We close by assessing progress in the field and speculating about its future course. Keywords behavioral finance, market efficiency, prospect theory, limits to arbitrage, investor psychology, investor behavior JEL classification: G11, G12, G30
Ch.18:A Survey of Behavioral Finance 1055 1.Introduction The traditional finance paradigm.which underlies many of the other articles in this handbook,seeks to understand financial markets using models in which agents are "rational".Rationality means two things.First,when they receive new information agents update their beliefs correctly,in the manner described by Bayes'law.Second, given their beliefs,agents make choices that are normatively acceptable,in the sense that they are consistent with Savage's notion of Subjective Expected Utility(SEU). This traditional framework is appealingly simple,and it would be very satisfying if its predictions were confirmed in the data.Unfortunately,after years of effort,it has become clear that basic facts about the aggregate stock market,the cross-section of average returns and individual trading behavior are not easily understood in this framework. Behavioral finance is a new approach to financial markets that has emerged,at least in part,in response to the difficulties faced by the traditional paradigm.In broad terms, it argues that some financial phenomena can be better understood using models in which some agents are not fully rational.More specifically,it analyzes what happens when we relax one,or both,of the two tenets that underlie individual rationality. In some behavioral finance models,agents fail to update their beliefs correctly.In other models,agents apply Bayes'law properly but make choices that are normatively questionable,in that they are incompatible with SEU1. This review essay evaluates recent work in this rapidly growing field.In Section 2, we consider the classic objection to behavioral finance,namely that even if some agents in the economy are less than fully rational,rational agents will prevent them from influencing security prices for very long,through a process known as arbitrage.One of the biggest successes of behavioral finance is a series of theoretical papers showing that in an economy where rational and irrational traders interact,irrationality can have a substantial and long-lived impact on prices.These papers,known as the literature on"limits to arbitrage",form one of the two buildings blocks of behavioral finance. 1 It is important to note that most models of asset pricing use the Rational Expectations Equilibrium framework (REE),which assumes not only individual rationality but also consistent beliefs [Sargent (1993)].Consistent beliefs means that agents'beliefs are correct:the subjective distribution they use to forecast future realizations of unknown variables is indeed the distribution that those realizations are drawn from.This requires not only that agents process new information correctly,but that they have enough information about the structure of the economy to be able to figure out the correct distribution for the variables of interest. Behavioral finance departs from REE by relaxing the assumption of individual rationality.An alternative departure is to retain individual rationality but to relax the consistent beliefs assumption:while investors apply Bayes'law correctly,they lack the information required to know the actual distribution variables are drawn from.This line of research is sometimes referred to as the literature on bounded rationality,or on structural uncertainty.For example,a model in which investors do not know the growth rate of an asset's cash flows but learn it as best as they can from available data,would fall into this class.Although the literature we discuss also uses the term bounded rationality,the approach is quite different
Ch. 18: A Survey of Behavioral Finance 1055 1. Introduction The traditional finance paradigm, which underlies many of the other articles in this handbook, seeks to understand financial markets using models in which agents are “rational”. Rationality means two things. First, when they receive new information, agents update their beliefs correctly, in the manner described by Bayes’ law. Second, given their beliefs, agents make choices that are normatively acceptable, in the sense that they are consistent with Savage’s notion of Subjective Expected Utility (SEU). This traditional framework is appealingly simple, and it would be very satisfying if its predictions were confirmed in the data. Unfortunately, after years of effort, it has become clear that basic facts about the aggregate stock market, the cross-section of average returns and individual trading behavior are not easily understood in this framework. Behavioral finance is a new approach to financial markets that has emerged, at least in part, in response to the difficulties faced by the traditional paradigm. In broad terms, it argues that some financial phenomena can be better understood using models in which some agents are not fully rational. More specifically, it analyzes what happens when we relax one, or both, of the two tenets that underlie individual rationality. In some behavioral finance models, agents fail to update their beliefs correctly. In other models, agents apply Bayes’ law properly but make choices that are normatively questionable, in that they are incompatible with SEU1. This review essay evaluates recent work in this rapidly growing field. In Section 2, we consider the classic objection to behavioral finance, namely that even if some agents in the economy are less than fully rational, rational agents will prevent them from influencing security prices for very long, through a process known as arbitrage. One of the biggest successes of behavioral finance is a series of theoretical papers showing that in an economy where rational and irrational traders interact, irrationality can have a substantial and long-lived impact on prices. These papers, known as the literature on “limits to arbitrage”, form one of the two buildings blocks of behavioral finance. 1 It is important to note that most models of asset pricing use the Rational Expectations Equilibrium framework (REE), which assumes not only individual rationality but also consistent beliefs [Sargent (1993)]. Consistent beliefs means that agents’ beliefs are correct: the subjective distribution they use to forecast future realizations of unknown variables is indeed the distribution that those realizations are drawn from. This requires not only that agents process new information correctly, but that they have enough information about the structure of the economy to be able to figure out the correct distribution for the variables of interest. Behavioral finance departs from REE by relaxing the assumption of individual rationality. An alternative departure is to retain individual rationality but to relax the consistent beliefs assumption: while investors apply Bayes’ law correctly, they lack the information required to know the actual distribution variables are drawn from. This line of research is sometimes referred to as the literature on bounded rationality, or on structural uncertainty. For example, a model in which investors do not know the growth rate of an asset’s cash flows but learn it as best as they can from available data, would fall into this class. Although the literature we discuss also uses the term bounded rationality, the approach is quite different
1056 N.Barberis and R.Thaler To make sharp predictions,behavioral models often need to specify the form of agents'irrationality.How exactly do people misapply Bayes law or deviate from SEU?For guidance on this,behavioral economists typically turn to the extensive experimental evidence compiled by cognitive psychologists on the biases that arise when people form beliefs,and on people's preferences,or on how they make decisions, given their beliefs.Psychology is therefore the second building block of behavioral finance,and we review the psychology most relevant for financial economists in Section 32. In Sections 48,we consider specific applications of behavioral finance:to understanding the aggregate stock market,the cross-section of average returns,and the pricing of closed-end funds in Sections 4,5 and 6 respectively;to understanding how particular groups of investors choose their portfolios and trade over time in Section 7; and to understanding the financing and investment decisions of firms in Section 8. Section 9 takes stock and suggests directions for future research3. 2.Limits to arbitrage 2.1.Market efficiency In the traditional framework where agents are rational and there are no frictions. a security's price equals its "fundamental value".This is the discounted sum of expected future cash flows,where in forming expectations,investors correctly process all available information,and where the discount rate is consistent with a normatively acceptable preference specification.The hypothesis that actual prices reflect fundamental values is the Efficient Markets Hypothesis(EMH).Put simply, under this hypothesis,"prices are right",in that they are set by agents who understand Bayes'law and have sensible preferences.In an efficient market,there is "no free lunch":no investment strategy can earn excess risk-adjusted average returns,or average returns greater than are warranted for its risk. Behavioral finance argues that some features of asset prices are most plausibly interpreted as deviations from fundamental value,and that these deviations are brought about by the presence of traders who are not fully rational.A long-standing objection to this view that goes back to Friedman (1953)is that rational traders will quickly undo any dislocations caused by irrational traders.To illustrate the argument,suppose 2 The idea,now widely adopted,that behavioral finance rests on the two pillars of limits to arbitrage and investor psychology is originally due to Shleifer and Summers (1990). 3We draw readers'attention to two other recent surveys of behavioral finance.Shleifer(2000)provides a particularly detailed discussion of the theoretical and empirical work on limits to arbitrage,which we summarize in Section 2.Hirshleifer's (2001)survey is closer to ours in terms of material covered, although we devote less space to asset pricing,and more to corporate finance and individual investor behavior.We also organize the material somewhat differently
1056 N. Barberis and R. Thaler To make sharp predictions, behavioral models often need to specify the form of agents’ irrationality. How exactly do people misapply Bayes law or deviate from SEU? For guidance on this, behavioral economists typically turn to the extensive experimental evidence compiled by cognitive psychologists on the biases that arise when people form beliefs, and on people’s preferences, or on how they make decisions, given their beliefs. Psychology is therefore the second building block of behavioral finance, and we review the psychology most relevant for financial economists in Section 32. In Sections 4–8, we consider specific applications of behavioral finance: to understanding the aggregate stock market, the cross-section of average returns, and the pricing of closed-end funds in Sections 4, 5 and 6 respectively; to understanding how particular groups of investors choose their portfolios and trade over time in Section 7; and to understanding the financing and investment decisions of firms in Section 8. Section 9 takes stock and suggests directions for future research 3. 2. Limits to arbitrage 2.1. Market efficiency In the traditional framework where agents are rational and there are no frictions, a security’s price equals its “fundamental value”. This is the discounted sum of expected future cash flows, where in forming expectations, investors correctly process all available information, and where the discount rate is consistent with a normatively acceptable preference specification. The hypothesis that actual prices reflect fundamental values is the Efficient Markets Hypothesis (EMH). Put simply, under this hypothesis, “prices are right”, in that they are set by agents who understand Bayes’ law and have sensible preferences. In an efficient market, there is “no free lunch”: no investment strategy can earn excess risk-adjusted average returns, or average returns greater than are warranted for its risk. Behavioral finance argues that some features of asset prices are most plausibly interpreted as deviations from fundamental value, and that these deviations are brought about by the presence of traders who are not fully rational. A long-standing objection to this view that goes back to Friedman (1953) is that rational traders will quickly undo any dislocations caused by irrational traders. To illustrate the argument, suppose 2 The idea, now widely adopted, that behavioral finance rests on the two pillars of limits to arbitrage and investor psychology is originally due to Shleifer and Summers (1990). 3 We draw readers’ attention to two other recent surveys of behavioral finance. Shleifer (2000) provides a particularly detailed discussion of the theoretical and empirical work on limits to arbitrage, which we summarize in Section 2. Hirshleifer’s (2001) survey is closer to ours in terms of material covered, although we devote less space to asset pricing, and more to corporate finance and individual investor behavior. We also organize the material somewhat differently
Ch.18:A Survey of Behavioral Finance 1057 that the fundamental value of a share of Ford is $20.Imagine that a group of irrational traders becomes excessively pessimistic about Ford's future prospects and through its selling,pushes the price to $15.Defenders of the EMH argue that rational traders, sensing an attractive opportunity,will buy the security at its bargain price and at the same time,hedge their bet by shorting a"substitute"security,such as General Motors, that has similar cash flows to Ford in future states of the world.The buying pressure on Ford shares will then bring their price back to fundamental value. Friedman's line of argument is initially compelling,but it has not survived careful theoretical scrutiny.In essence,it is based on two assertions.First.as soon as there is a deviation from fundamental value-in short,a mispricing-an attractive investment opportunity is created.Second,rational traders will immediately snap up the opportunity,thereby correcting the mispricing.Behavioral finance does not take issue with the second step in this argument:when attractive investment opportunities come to light,it is hard to believe that they are not quickly exploited.Rather,it disputes the first step.The argument,which we elaborate on in Sections 2.2 and 2.3,is that even when an asset is wildly mispriced,strategies designed to correct the mispricing can be both risky and costly,rendering them unattractive.As a result,the mispricing can remain unchallenged. It is interesting to think about common finance terminology in this light.While irrational traders are often known as "noise traders",rational traders are typically referred to as"arbitrageurs".Strictly speaking,an arbitrage is an investment strategy that offers riskless profits at no cost.Presumably,the rational traders in Friedman's fable became known as arbitrageurs because of the belief that a mispriced asset immediately creates an opportunity for riskless profits.Behavioral finance argues that this is not true:the strategies that Friedman would have his rational traders adopt are not necessarily arbitrages;quite often,they are very risky. An immediate corollary of this line of thinking is that"prices are right"and"there is no free lunch"are not equivalent statements.While both are true in an efficient market,"no free lunch"can also be true in an inefficient market:just because prices are away from fundamental value does not necessarily mean that there are any excess risk-adjusted average returns for the taking.In other words, prices are right'”→"no free lunch" but no free lunch”“prices are right". This distinction is important for evaluating the ongoing debate on market efficiency. First,many researchers still point to the inability of professional money managers to beat the market as strong evidence of market efficiency [Rubinstein(2001),Ross (2001)].Underlying this argument,though,is the assumption that "no free lunch" implies"prices are right."If,as we argue in Sections 2.2 and 2.3,this link is broken,the
Ch. 18: A Survey of Behavioral Finance 1057 that the fundamental value of a share of Ford is $20. Imagine that a group of irrational traders becomes excessively pessimistic about Ford’s future prospects and through its selling, pushes the price to $15. Defenders of the EMH argue that rational traders, sensing an attractive opportunity, will buy the security at its bargain price and at the same time, hedge their bet by shorting a “substitute” security, such as General Motors, that has similar cash flows to Ford in future states of the world. The buying pressure on Ford shares will then bring their price back to fundamental value. Friedman’s line of argument is initially compelling, but it has not survived careful theoretical scrutiny. In essence, it is based on two assertions. First, as soon as there is a deviation from fundamental value – in short, a mispricing – an attractive investment opportunity is created. Second, rational traders will immediately snap up the opportunity, thereby correcting the mispricing. Behavioral finance does not take issue with the second step in this argument: when attractive investment opportunities come to light, it is hard to believe that they are not quickly exploited. Rather, it disputes the first step. The argument, which we elaborate on in Sections 2.2 and 2.3, is that even when an asset is wildly mispriced, strategies designed to correct the mispricing can be both risky and costly, rendering them unattractive. As a result, the mispricing can remain unchallenged. It is interesting to think about common finance terminology in this light. While irrational traders are often known as “noise traders”, rational traders are typically referred to as “arbitrageurs”. Strictly speaking, an arbitrage is an investment strategy that offers riskless profits at no cost. Presumably, the rational traders in Friedman’s fable became known as arbitrageurs because of the belief that a mispriced asset immediately creates an opportunity for riskless profits. Behavioral finance argues that this is not true: the strategies that Friedman would have his rational traders adopt are not necessarily arbitrages; quite often, they are very risky. An immediate corollary of this line of thinking is that “prices are right” and “there is no free lunch” are not equivalent statements. While both are true in an efficient market, “no free lunch” can also be true in an inefficient market: just because prices are away from fundamental value does not necessarily mean that there are any excess risk-adjusted average returns for the taking. In other words, “prices are right” ⇒ “no free lunch” but “no free lunch” “prices are right”. This distinction is important for evaluating the ongoing debate on market efficiency. First, many researchers still point to the inability of professional money managers to beat the market as strong evidence of market efficiency [Rubinstein (2001), Ross (2001)]. Underlying this argument, though, is the assumption that “no free lunch” implies “prices are right.” If, as we argue in Sections 2.2 and 2.3, this link is broken, the