Does the Stock Market Overreact ?

Research in experimental psychology suggests that, in violation of Bayes' rule, most people tend to "overreact" to unexpected and dramatic news events. This study of market efficiency investigates whether such behavior affects stock prices. The empirical evidence, based on CRSP monthly return data, is consistent with the overreaction hypothesis. Substantial weak form market inefficiencies are discovered. The results also shed new light on the January returns earned by prior "winners" and "losers." Portfolios of losers experience exceptionally large January returns as late as five years after portfolio formation. As ECONOMISTS INTERESTED IN both market behavior and the psychology of individual decision making, we have been struck by the similarity of two sets of empirical findings. Both classes of behavior can be characterized as displaying ouerreaction. This study was undertaken to investigate the possibility that these phenomena are related by more than just appearance. We begin by describing briefly the individual and market behavior that piqued our interest. The term overreaction carries with it an implicit comparison to some degree of reaction that is considered to be appropriate. What is an appropriate reaction? One class.of tasks which have a well-established norm are probability revision problems for which Bayes' rule prescribes the correct reaction to new information. It has now been well-established that Bayes' rule is not an apt characterization of how individuals actually respond to new data (Kahneman et al. [14]). In revising their beliefs, individuals tend to overweight recent information and underweight prior (or base rate) data. People seem to make predictions according to a simple matching rule: "The predicted value is selected so that the standing of the case in the distribution of outcomes matches its standing in the distribution of impressions" (Kahneman and Tversky [14, p. 4161). This rule-of-thumb, an instance of what Kahneman and Tversky call the representativeness heuristic, violates the basic statistical principal that the extremeness of predictions must be moderated by considerations of predictability. Grether [12] has replicated this finding under incentive compatible conditions. There is also considerable evidence that the actual expectations of professional security analysts and economic forecasters display the same overreaction bias (for a review, see De Bondt [7]). One of the earliest observations about overreaction in markets was made by J. M. Keynes:". . .day-to-day fluctuations in the profits of existing investments, * University of Wisconsin at Madison and Cornell University, respectively. The financial support of the C.I.M. Doctoral Fellowship Program (Brussels, Belgium) and the Cornell Graduate School of Management is gratefully acknowledged. We received helpful comments from Seymour Smidt, Dale Morse, Peter Bernstein, Fischer Black, Robert Jarrow, Edwin Elton, and Ross Watts. 794 The Journal of Finance which are obviously of an ephemeral and nonsignificant character, tend to have an altogether excessive, and even an absurd, influence on the market" [17, pp. 153-1541. About the same time, Williams noted in this Theory of Investment Value that "prices have been based too much on current earning power and too little on long-term dividend paying power" [28, p. 191. More recently, Arrow has concluded that the work of Kahneman and Tversky "typifies very precisely the exessive reaction to current information which seems to characterize all the securities and futures markets" [I, p. 51. Two specific examples of the research to which Arrow was referring are the excess volatility of security prices and the so-called price earnings ratio anomaly. The excess volatility issue has been investigated most thoroughly by Shiller [27]. Shiller interprets the Miller-Modigliani view of stock prices as a constraint on the likelihood function of a price-dividend sample. Shiller concludes that, at least over the last century, dividends simply do not vary enough to rationally justify observed aggregate price movements. Combining the results with Kleidon's [18] findings that stock price movements are strongly correlated with the following year's earnings changes suggests a clear pattern of overreaction. In spite of the observed trendiness of dividends, investors seem to attach disproportionate importance to short-run economic developments.' The price earnings ratio (PIE) anomaly refers to the observation that stocks with extremely low PIE ratios (i.e., lowest decile) earn larger risk-adjusted returns than high PIE stocks (Basu [3]). Most financial economists seem to regard the anomaly as a statistical artifact. Explanations are usually based on alleged misspecification of the capital asset pricing model (CAPM). Ball [2] emphasizes the effects of omitted risk factors. The PIE ratio is presumed to be a proxy for some omitted factor which, if included in the "correct" equilibrium valuation model, would eliminate the anomaly. Of course, unless these omitted factors can be identified, the hypothesis is untestable. Reinganum [21] has claimed that the small firm effect subsumes the PIE effect and that both are related to the same set of missing (and again unknown) factors. However, Basu [4] found a significant PIE effect after controlling for firm size, and earlier Graham [ l l ] even found an effect within the thirty Dow Jones Industrials, hardly a group of small firms! An alternative behavioral explanation for the anomaly based on investor overreaction is what Basu called the "price-ratio" hypothesis (e.g., Dreman [8]). Companies with very low PIE'Sare thought to be temporarily "undervalued" because investors become excessively pessimistic after a series of bad earnings reports or other bad news. Once future earnings turn out to be better than the unreasonably gloomy forecasts, the price adjusts. Similarly, the equity of companies with very high PIE'Sis thought to be "overvalued," before (predictably) falling in price. While the overreaction hypothesis has considerable a priori appeal, the obvious question to ask is: How does the anomaly survive the process of arbitrage? There Of course, the variability of stock prices may also reflect changes in real interest rates. If so, the price movements of other assets-such as land or housing-should match those of stocks. However, this is not actually observed. A third hypothesis, advocated by Marsh and Merton [19], is that Shiller's findings are a result of his misspecification of the dividend process. 795 Does the Stock Market Overreact? is really a more general question here. What are the equilibria conditions for markets in which some agents are not rational in the sense that they fail to revise their expectations according to Bayes' rule? Russell and Thaler [24] address this issue. They conclude that the existence of some rational agents is not sufficient to guarantee a rational expectations equilibrium in an economy with some of what they call quasi-rational agents. (The related question of market equilibria with agents having heterogeneous expectations is investigated by Jarrow [13].) While we are highly sensitive to these issues, we do not have the space to address them here. Instead, we will concentrate on an empirical test of the overreaction hypothesis. If stock prices systematically overshoot, then their reversal should be predictable from past return data alone, with no use of any accounting data such as earnings. Specifically, two hypotheses are suggested: (1)Extreme movements in stock prices will be followed by subsequent price movements in the opposite direction. (2) The more extreme the initial price movement, the greater will be the subsequent adjustment. Both hypotheses imply a violation of weak-form market efficiency. To repeat, our goal is to test whether the overreaction hypothesis is predictive. In other words, whether it does more for us than merely to explain, ex post, the PIE effect or Shiller's results on asset price dispersion. The overreaction effect deserves attention because it represents a behavioral principle that may apply in many other contexts. For example, investor overreaction possibly explains Shiller's earlier [26] findings that when long-term interest rates are high relative to short rates, they tend to move down later on. Ohlson and Penman [20] have further suggested that the increased volatility of security returns following stock splits may also be linked to overreaction. The present empirical tests are to our knowledge the first attempt to use a behavioral principle to predict a new market anomaly. The remainder of the paper is organized as follows. The next section describes the actual empirical tests we have performed. Section I1 describes the results. Consistent with the overreaction hypothesis, evidence of weak-form market inefficiency is found. We discuss the implications for other empirical work on asset pricing anomalies. The paper ends with a brief summary of conclusions. I. The Overreaction Hypothesis: Empirical Tests The empirical testing procedures are a variant on a design originally proposed by Beaver and Landsman [5] in a different context. Typically, tests of semistrong form market efficiency start, at time t = 0, with the formation of portfolios on the basis of some event that affects all stocks in the portfolio, say, an earnings announcement. One then goes on to investigate whether later on ( t > 0) the estimated residual portfolio return rip,--measured relative to the single-period CAPM-equals zero. Statistically significant departures from zero are interpreted as evidence consistent with semistrong form market inefficiency, even though the results may also be due to misspecification of the CAPM, misestimation of the relevant alphas and/or betas, or simply market inefficiency of the weak form. 796 The Journal of Finance In contrast, the tests in this study assess the extent to which systematic nonzero