A New Pseudo-Bayesian Model with Implications for Financial Anomalies and Investors’ Behavior

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Abstract
Barberis, Shleifer, and Vishny [1998] and others have developed Bayesian models to explain investors’ behavioral biases by using conservative heuristics and representative heuristics in making decisions. To extend their work, Lam, Liu, and Wong [2010] have developed a model of weight assignments using a pseudo-Bayesian approach that reflects investors’ behavioral biases. In this parsimonious model of investor sentiment, weights induced by investors’ conservative and representative heuristics are assigned to observations of the earning shocks of stock prices. Such weight assignments enable us to provide a quantitative link between some market anomalies and investors’ behavioral biases. This paper extends their work further by developing a theory to explain some market anomalies, including short-term underreaction, long-term overreaction, and excess volatility. We also explain in detail the linkage between these market anomalies and investors’ behavioral biases.

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