Motivated by the behavior of asset prices, trading volume and price volatility during historical episodes of asset price bubbles, we present a continuous time equilibrium model where overconfidence generates disagreements among agents regarding asset fundamentals. With short-sale constraints, an asset owner has an option to sell the asset to other overconfident agents when they have more optimistic beliefs. As in Harrison and Kreps (1978), this re-sale option has a recursive structure, that is, a buyer of the asset gets the option to resell it. Agents pay prices that exceed their own valuation of future dividends because they believe that in the future they will find a buyer willing to pay even more. This causes a significant bubble component in asset prices even when small differences of beliefs are sufficient to generate a trade. In equilibrium, large bubbles are accompanied by large trading volume and high price volatility. Our model has an explicit solution, which allows for several comparative statics exercises. Our analysis shows that while Tobin’s tax can substantially reduce speculative trading when transaction costs are small, it has only a limited impact on the size of the bubble or on price volatility. We also give an example where the price of a subsidiary is larger than its parent firm. This paper was previously circulated under the title “Overconfidence, Short-Sale Constraints and Bubbles.”

We provide evidence that stocks with higher dispersion in analysts ’ earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks and stocks that have performed poorly over the past year. Interpreting dispersion in analysts ’ forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts ’ forecasts proxies for risk. IN THIS PAPER WE ANALYZE THE ROLE of dispersion in analysts ’ earnings forecasts in predicting the cross section of future stock returns. We find that stocks with higher dispersion in analysts ’ earnings forecasts earn significantly lower future returns than otherwise similar stocks. In particular, a portfolio of stocks in the highest quintile of dispersion underperforms a portfolio of stocks in the lowest quintile of dispersion by 9.48 percent per year. This effect is

We provide evidence that stocks with higher dispersion in analysts ’ earnings forecasts earn lower future returns than otherwise similar stocks. This effect is most pronounced in small stocks, and stocks that have performed poorly over the past year. Interpreting dispersion in analysts ’ forecasts as a proxy for differences in opinion about a stock, we show that this evidence is consistent with the hypothesis that prices will reflect the optimistic view whenever investors with the lowest valuations do not trade. By contrast, our evidence is inconsistent with a view that dispersion in analysts ’ forecasts proxies for risk.

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The market dynamics of technology stocks in the late 1990s have stimulated a growing body of theory that analyzes the joint effects of short-sales constraints and heterogeneous beliefs on stock prices and trading volume. This paper examines several implications of these theories using a unique data sample from a market with stringent short-sales constraints and perfectly segmented dual-class shares. The identical rights of the dual-class shares allow us to control for stock fundamentals. We find that trading caused by investors’ speculative motives can help explain a significant fraction of the price difference between the dual-class shares.

Motivated by the behavior of internet stock prices in 1998-2000, we present a continuous time equilibrium model of bubbles where overconfidence generates agreements to disagree among agents about asset fundamentals. With a short-sale constraint, an asset owner has an option to sell the asset to other agents when they have more optimistic beliefs. This re-sale option has a recursive structure, that is a buyer of the asset gets the option to resell it, causing a significant bubble component in asset prices even when small differences of beliefs are sufficient to generate a trade. The model generates prices that are above fundamentals, excessive trading, and excess volatility. We also give an example where the price of a subsidiary is larger than its parent firm. Our analysis shows that while Tobin's tax can substantially reduce speculative trading when transaction costs are small, it has only a limited impact on the size of the bubble or on price volatility.

Abstract: We study the implications of learning in an environment where the true model of the world is a multivariate one, but where agents update only over the class of simple univariate models. If a particular simple model does a poor job of forecasting over a period of time, it is eventually discarded in favor of an alternative—yet equally simple—model that would have done better over the same period. This theory makes several distinctive predictions, which, for concreteness, we develop in a stock-market setting. For example, starting with symmetric and homoskedastic fundamentals, the theory yields forecastable variation in the size of the value/glamour differential, in volatility, and in the skewness of returns. Some of these features mirror familiar accounts of stock-price bubbles.

We analyze a binary prediction market in which traders have heterogeneous prior beliefs and private information. Realistically, we assume that traders are allowed to invest a limited amount of money (or have decreasing absolute risk aversion). We show that the rational expectations equilibrium price underreacts to information. When favorable information to an event is available and is revealed by the market, the price increases and this forces optimists to reduce the number of assets they can (or want to) buy. For the market to equilibrate, the price must increase less than a posterior belief of an outside observer.

In this paper we use data from China’s stock markets to analyze non-fundamental components in stock prices. During the period 1993-2000, several dozen Chinese firms offered two classes of shares: class A, which could only be held by domestic investors, and class B, which could only be traded by foreigners. Despite their identical rights, A-share prices were on average 400 % higher than the corresponding B shares. We use a model of investor overconfidence (Scheinkman and Xiong (2003)) that produces correlations among prices, turnover, and volatility, to explain this premium. By adopting a panel regression method, we find that the turnover rate of A shares is able to explain 20 % of the cross-sectional variation in A-B share premium. We also conduct various specification analyses, and examine the relation between float, turnover rate, and volatility.

Towards developing a theory of systematic biases about strategies, I analyze strategic implications of a particular bias: wishful thinking about the strategies. I identify a player as a wishful thinker if she hopes to enjoy the highest payoff that is consistent with her information about the others’ strategies. I develop a straightforward elimination process that characterizes the strategy profiles that are consistent with wishful thinking, mutual knowledge of wishful thinking, and so on. Every pure-strategy Nash equilibrium is consistent with common knowledge of wishful thinking. For generic two-person games, I further show that the pure Nash equilibrium strategies are the only strategies that are consistent with common knowledge of wishful thinking. My analysis also illustrates how one can characterize the strategic implications of general decision rules using the tools of game theory.