Recent empirical research in finance has uncovered two families of pervasive regularities: underreaction of stock prices to news such as earnings announcements, and overreaction of stock prices to a series of good or bad news. In this paper, we present a parsimonious model of investor sentiment, or of how investors form beliefs, which is consistent with the empirical findings. The model is based on psychological evidence and produces both underreaction and overreaction for a wide range of parameter values. � 1998 Elsevier Science S.A. All rights reserved. JEL classification: G12; G14

We model a market populated by two groups of boundedly rational agents: “newswatchers” and “momentum traders.” Each newswatcher observes some private information, but fails to extract other newswatchers’ information from prices. If information diffuses gradually across the population, prices underreact in the short run. The underreaction means that the momentum traders can profit by trendchasing. However, if they can only implement simple (i.e., univariate) strategies, their attempts at arbitrage must inevitably lead to overreaction at long horizons. In addition to providing a unified account of under- and overreactions, the model generates several other distinctive implications.

This paper was developed with financial support from the SBF Bourse de Paris and the New York Stock Exchange, and the assistance of George Sofianos, Bill Tschirhart, and Didier Davidoff is gratefully acknowledged. We appreciate comments received on this paper from Anthony Boardman, Bernardo Bortolotti, Narjess Boubakri, JeanClaude Cosset, Kathy Dewenter, Alexander Dyck, Ivan Ivanov, Ranko Jelic, Claude Laurin, Marc Lipson, Luis Lopez-Calva, John McMillan (the editor), Harold Mulherin, Rob Nash, John Nellis, David Newberry, David Parker, Enrico Perotti, Annette Poulsen, Ravi Ramamurti, Susan Rose-Ackerman, Nemat Shafik, Mary Shirley, Aidan Vining and three anonymous referees. Additionally, we appreciate comments received from participants at the NYSE/Paris Bourse Global Equity Markets conference (Paris, December 1998), the Harvard Institute for International Development Privatization Workshop (June 2000), the International Federation of Stock Exchanges' Third Global Emerging Markets Conference (Istanbul, April 2000), four World Bank and/or International Finance Corporation meetings, two OECD conferences (Paris and Beijing), the 1999 Conference on Privatization and the Kuwaiti Economy in the Next Century, the 1998 Financial Management Association meeting, the 1999 European Financial Management Association meeting, the Fondazione ENI Enrico Mattei (FFEM), the Swiss Banking Institute and Credit Suisse, and seminars at the City University Business School (London), London Guildhall University and the University of Oklahoma. All remaining errors are the authors' alone. Please address correspondence to: William L. Megginson Price College of Business 307 West Brooks, 205A Adams Hall The University of Oklahoma Norman, OK 73019-4005 Tel: (405) 325-2058; Fax: (405) 325-1957 e-mail:...

We analyze tests for long-run abnormal returns and document that two approaches yield well-specified test statistics in random samples. The first uses a traditional event study framework and buy-and-hold abnormal returns calculated using carefully constructed reference portfolios. Inference is based on either a skewnessadjusted t-statistic or the empirically generated distribution of long-run abnormal returns. The second approach is based on calculation of mean monthly abnormal returns using calendar-time portfolios and a time-series t-statistic. Though both approaches perform well in random samples, misspecification in nonrandom samples is pervasive. Thus, analysis of long-run abnormal returns is treacherous. COMMONLY USED METHODS TO TEST for long-run abnormal stock returns yield misspecified test statistics, as documented by Barber and Lyon ~1997a! and Kothari and Warner ~1997!. 1 Simulations reveal that empirical rejection levels routinely exceed theoretical rejection levels in these tests. In combination, these papers highlight three causes for this misspecification. First, the

As in previous decades, merger activity clusters by industry during the 1990s. One particular kind of industry shock, deregulation, becomes a dominant factor, accounting for nearly half of the merger activity since the late 1980s. In contrast to the 1980s, mergers in the 1990s are mostly stock swaps, and hostile takeovers virtually disappear. Over our 1973 to 1998 sample period, the announcement-period stock market response to mergers is positive for the combined merging parties, suggesting that mergers create value on behalf of shareholders. Consistent with that, we find evidence of improved operating performance following mergers, relative to industry peers.

It is well known that firms are more likely to issue equity when their market values are high, relative to book and past market values, and to repurchase equity when their market values are low. We document that the resulting effects on capital structure are very persistent. As a consequence, current capital structure is strongly related to historical market values. The results suggest the theory that capital structure is the cumulative outcome of past attempts to time the equity market.

Various theories have been proposed to explain momentum in stock returns. We test the gradual-information-diffusion model of Hong and Stein (1999) and establish three key results. First, once one moves past the very smallest stocks, the profitability of momentum strategies declines sharply with firm size. Second, holding size fixed, momentum strategies work better among stocks with low analyst coverage. Finally, the effect of analyst coverage is greater for stocks that are past losers than for past winners. These findings are consistent with the hypothesis that firm-specific information, especially negative information, diffuses only gradually across the investing public. SEVERAL RECENT PAPERS HAVE DOCUMENTED that, at medium-term horizons ranging from three to 12 months, stock returns exhibit momentum-that is, past winners continue to perform well, and past losers continue to perform poorly. For example, Jegadeesh and Titman (1993), using a U.S. sample of NYSE/ AMEX stocks over the period from 1965 to 1989, find that a strategy that buys past six-month winners (stocks in the top performance decile) and shorts past six-month losers (stocks in the bottom performance decile) earns approximately one percent per month over the subsequent six months. Not only is this an economically interesting magnitude, but the result also appears to be robust: Rouwenhorst (1998) obtains very similar numbers in a

The share of equity issues in total new equity and debt issues is a strong predictor of U.S. stock market returns between 1928 and 1997. In particular, firms issue relatively more equity than debt just before periods of low market returns. The equity share in new issues has stable predictive power in both halves of the sample period and after controlling for other known predictors. We do not find support for efficient market explanations of the results. Instead, the fact that the equity share sometimes predicts significantly negative market returns suggests inefficiency and that firms time the market component of their returns when issuing securities.

This paper provides one potential explanation for the rise, persistence and eventual fall of internet stock prices. Specifically, we appeal to a model of heterogenous agents with varying degrees of beliefs about asset payoffs who are subject to short sales constraints. In this framework, it is possible that "optimistic" investors overwhelm "pessimistic" ones, leading to prices not reflecting fundamental values about cash flows. Empirical support for this explanation is provided by exploring the behavior of internet stock prices during the period January 1998 to November 2000. In particular, we document four important elements to our story: (i) the high level of internet stock prices given their underlying fundamentals, (ii) responses of stock prices to a shift towards potentially optimistic investors, (iii) empirical results consistent with shorting being at its maximum possible level for internet stocks, and (iv) the eventual fall, or bubble bursting, of intemet stocks being tied to the increase in the number of sellers to the market via expiration of lockup agreements.

People are overconfident. Overconfidence affects financial markets. How depends on who in the market is overconfident and on how information is distributed. This paper examines markets in which price-taking traders, a strategic-trading insider, and risk-averse marketmakers are overconfident. Overconfidence increases expected trading volume, increases market depth, and decreases the expected utility of overconfident traders. Its effect on volatility and price quality depend on who is overconfident. Overconfident traders can cause markets to underreact to the information of rational traders. Markets also underreact to abstract, statistical, and highly relevant information, and they overreact to salient, anecdotal, and less relevant information. MODELS OF FINANCIAL MARKETS are often extended by incorporating the imperfections that we observe in real markets. For example, models may not consider transactions costs, an important feature of real markets; so Constantinides ~1979!, Leland ~1985!, and others incorporate transactions costs into their models. Just as the observed features of actual markets are incorporated into models, so too are the observed traits of economic agents. In 1738 Daniel Bernoulli noted that people behave as if they are risk averse. Prior to Bernoulli most scholars considered it normative behavior to value a gamble at its expected value. Today, economic models usually assume agents are risk averse, though, for tractability, they are also modeled as risk neutral. In reality, people are not always risk averse or even risk neutral; millions of people engage in regular risk-seeking activity, such as buying lottery tickets. Kahne-