Survey evidence suggests that many investors form beliefs about future stock market returns by extrapolating past returns. Such beliefs are hard to reconcile with existing models of the aggregate stock market. We study a consumption-based asset pricing model in which some investors form beliefs about future price changes in the stock market by extrapolating past price changes, while other investors hold fully rational beliefs. We find that the model captures many features of actual prices and returns; importantly, however, it is also consistent with the survey evidence on investor expectations.
We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals-an average of the asset's past price changes and the asset's degree of overvaluation. The two signals are in conflict, and investors "waver" over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles. We analyze the patterns of cash-flow news that generate the largest bubbles, the reasons why bubbles collapse, and the frequency with which they occur. The model also predicts that bubbles will be accompanied by high trading volume, and that volume increases with past asset returns. We present empirical evidence that bears on some of the model's distinctive predictions.
We present an extrapolative model of bubbles. In the model, many investors form their demand for a risky asset by weighing two signals-an average of the asset's past price changes and the asset's degree of overvaluation. The two signals are in conflict, and investors "waver" over time in the relative weight they put on them. The model predicts that good news about fundamentals can trigger large price bubbles. We analyze the patterns of cash-flow news that generate the largest bubbles, the reasons why bubbles collapse, and the frequency with which they occur. The model also predicts that bubbles will be accompanied by high trading volume, and that volume increases with past asset returns. We present empirical evidence that bears on some of the model's distinctive predictions. * The authors' affiliations are Yale School of Management, Harvard Business School, California Institute of Technology, and Harvard University, respectively. Comments are welcome.
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