Behavioral Finance

NBER Reporter: Summer 2000

Behavioral Finance

The NBER's Working Group on Behavioral Finance met in Cambridge on May 6. Robert Shiller, NBER and Yale University, and Richard H. Thaler, NBER and University of Chicago, organized the program and chose the following papers for discussion:

Nicholas C. Barberis, NBER and University of Chicago, and Ming Huang, Stanford University, "Mental Accounting, Loss Aversion, and Individual Stock Returns"

Discussant: Richard H. Thaler

Matthew Rabin, University of California, Berkeley, "Inference by Believers in the Law of Small Numbers"

Discussant: Sendhil Mullainathan, NBER and MIT

Bhaskaran Swaminathan and Charles M. C. Lee, Cornell University, "Do Stock Prices Overreact to Earnings News?"

Discussant: Andrei Shleifer, NBER and Harvard University

Alon Brav, Duke University, and James B. Heaton, Bartlit, Beek, Herman, Palenchar, & Scott (Chicago), "Competing Theories of Financial Anomalies"

Discussant: Jeremy C. Stein, NBER and MIT

David L. Ikenbery and Sundaresh Ramnath, Rice University, "Underreaction"

Discussant: Roni Michaely, Cornell University

William N. Goetzmann, NBER and Yale University; Massimo Massa, INSEAD; K. Geert Rouwenhorst, Yale University; "Behavioral Factors in Mutual Fund Flows"

Discussant: Andrew Metrick, NBER and University of Pennsylvania

Barberis and Huang study equilibrium asset prices in a model in which investors are loss averse. They consider two possibilities, corresponding to assumptions about how people do mental accounting and how they evaluate their investment performance. In one case, investors track their performance stock by stock and are loss averse in terms of individual stock fluctuations. In the other case, investors measure their performance at the portfolio level and are loss averse only about portfolio fluctuations. The authors find that loss aversion in regard to individual stock fluctuations is helpful for explaining a wide range of empirical facts. In simulated data, individual stock returns have a high mean and excess volatility, and are slightly predictable over time; moreover, there are large "value" and "size" premiums in the cross-section. The case where investors are loss averse over portfolio fluctuations, although normatively more appealing, is less successful in explaining the facts: individual returns are not volatile enough and are too correlated, while the premiums for value and size largely disappear.

Many people believe in the "law of small numbers," exaggerating the degree to which a small sample resembles the population from which it is drawn. To model this, Rabin assumes that a person exaggerates the likelihood that a short sequence of signals resembles the long-run rate at which those signals are generated. That person believes in the "gambler's fallacy," thinking that early draws of one signal increase the odds of subsequently drawing other signals. When uncertain about the rate, the person infers too much from short sequences of signals and is prone to thinking that the rate is more extreme than it is. When people make inferences about the frequency at which rates are generated by different sources -- such as the distribution of talent among financial analysts -- based on a few observations from each source, they tend to exaggerate how much the rates vary. Hence, Rabin's model predicts that people may pay for financial advice from "experts" whose expertise is entirely illusory. Swaminathan and Lee show that both intermediate-term momentum and long-term price reversal are linked to the release of specific public news about a firm's earnings. The authors also show that glamour winners -- positive surprise firms with a sequence of past positive earnings surprises, higher past trading volume, and low book-to-market ratios -- exhibit faster price reversals. Value losers -- whose characteristics are the opposite of glamour winners -- also exhibit faster price reversals. In other words, the post-earnings announcement drift is attenuated when the most recent signal confirms the older signal, and vice versa. Overall, the evidence suggests a price formation process in which the market systematically underreacts to recent news and overreacts to longer-term (older) news.

Brav and Heaton compare two competing theories of financial anomalies: "behavioral" theories relying on investor irrationality and rational "structural uncertainty" theories relying on investor uncertainty about the structure of the economic environment. Each relaxes the traditional rational expectations theory in a certain way. However, the resulting theories are virtually indistinguishable empirically, although their implications differ radically. Given the mathematical and predictive similarities of the theories, the authors argue that attention should probably shift from the behavioral-rational debate toward a greater (and perhaps less philosophical) focus on investor concern with structural uncertainty.

In the last decade, an emerging body of empirical literature examining self-selected corporate news events makes the observation that markets appear to underreact. In this paper, Ikenbery and Ramnath revisit the issue of underreaction by focusing on the simplest of corporate transactions: the stock split. Using a matched-control firm approach, the authors find abnormal returns of 9 percent in the year following the stock-split announcement for a recent sample of cases. They then examine how earnings expectations are revised subsequent to this type of news event. If the positive drift reported in this study and elsewhere is attributable to benchmark problems, then one might not expect to find surprising results with respect to revisions in earnings expectations. Yet this is not the case. Instead, revisions in earnings forecasts are just as sluggish as stock prices. This gradual revision in earnings expectations explains a significant portion of the drift in abnormal returns. At least with respect to this most simple of news events, it would indeed appear that markets underreact to news.

Using a sample of daily net flows to nearly 1,000 U.S. mutual funds over a year and a half, Goetzmann, Massa, and Rouwenhorst identify a set of systematic factors that explain a significant amount of the variation in those flows. The authors find that flows into equity funds -- both domestic and international -- are negatively correlated with flows into money market funds and precious metals funds. This suggests that investor rebalancing between cash and equity explains a significant amount of trade in mutual fund shares. The negative correlation of equities to metals suggests that this timing is not simply caused by liquidity concerns but rather by sentiment about the equity premium. To address the question of whether behavioral factors spread returns, the authors use the mutual fund flow factors in a Fama-MacBeth asset pricing framework. They find that the factors derived from flows alone explain as much as 45 percent of the cross-sectional variation in mutual fund returns. The fund flow factors provide significant incremental explanatory power in the cross-sectional regressions on daily returns. The authors consider a number of alternatives to explain their evidence, including causality from returns to flows and vice versa. The evidence is consistent with the existence of a pervasive investor sentiment variable.

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