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 trend‐chasing. 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 develops an equilibrium model of a competitive futures market in which investors trade to hedge positions and to speculate on their private information. Equilibrium return and trading patterns are examined. (1) In markets where the information asymmetry among investors is small, the return volatility of a futures contract decreases with time‐to‐maturity (i.e., the Samuelson effect holds). (2) However, in markets where the information asymmetry among investors is large, the Samuelson effect need not hold. (3) Additionally, the model generates rich time‐to‐maturity patterns in open interest and spot price volatility that are consistent with empirical findings.

The risk and return trade‐off, the cornerstone of modern asset pricing theory, is often of the wrong sign. Our explanation is that high‐beta assets are prone to speculative overpricing. When investors disagree about the stock market's prospects, high‐beta assets are more sensitive to this aggregate disagreement, experience greater divergence of opinion about their payoffs, and are overpriced due to short‐sales constraints. When aggregate disagreement is low, the Security Market Line is upward‐sloping due to risk‐sharing. When it is high, expected returns can actually decrease with beta. We confirm our theory using a measure of disagreement about stock market earnings.

We examine security analysts' career concerns by relating their earnings forecasts to job separations. Relatively accurate forecasters are more likely to experience favorable career outcomes like moving up to a high‐status brokerage house. Controlling for accuracy, analysts who are optimistic relative to the consensus are more likely to experience favorable job separations. For analysts who cover stocks underwritten by their houses, job separations depend less on accuracy and more on optimism. Job separations were less sensitive to accuracy and more sensitive to optimism during the recent stock market mania. Brokerage houses apparently reward optimistic analysts who promote stocks.

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 trend‐chasing. 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.

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.

A mutual fund manager is more likely to buy (or sell) a particular stock in any quarter if other managers in the same city are buying (or selling) that same stock. This pattern shows up even when the fund manager and the stock in question are located far apart, so it is distinct from anything having to do with local preference. The evidence can be interpreted in terms of an epidemic model in which investors spread information about stocks to one another by word of mouth.

We propose that stock‐market participation is influenced by social interaction. In our model, any given “social” investor finds the market more attractive when more of his peers participate. We test this theory using data from the Health and Retirement Study, and find that social households—those who interact with their neighbors, or attend church—are substantially more likely to invest in the market than non‐social households, controlling for wealth, race, education, and risk tolerance. Moreover, consistent with a peer‐effects story, the impact of sociability is stronger in states where stock‐market participation rates are higher.

This paper studies how market closures affect investors' trading policies and the resulting return‐generating process. It shows that closures generate rich patterns of time variation in trading and returns, including those consistent with empirical findings: (1) U‐shaped patterns in the mean and volatility of returns over trading periods, (2) higher trading activity around the close and open, (3) more volatile open‐to‐open returns than close‐to‐close returns, (4) higher returns over trading periods than over nontrading periods, (5) more volatile returns over trading periods than over nontrading periods. It also shows that closures can make prices more informative about future payoffs.

We model the relationship between asset float (tradeable shares) and speculative bubbles. Investors with heterogeneous beliefs and short‐sales constraints trade a stock with limited float because of insider lockups. A bubble arises as price overweighs optimists' beliefs and investors anticipate the option to resell to those with even higher valuations. The bubble's size depends on float as investors anticipate an increase in float with lockup expirations and speculate over the degree of insider selling. Consistent with the internet experience, the bubble, turnover, and volatility decrease with float and prices drop on the lockup expiration date.