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Information Processing and Non-Bayesian Learning in Financial Markets

Author

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  • Stefanie Schraeder

    (University of New South Wales)

Abstract

Ample empirical and experimental evidence documents that individuals place greater weight on information gained through personal experience -- a phenomenon that Tversky and Kahneman (1982) call availability bias. I embed this bias in an overlapping generations equilibrium model in which the period that investors first enter the market establishes the starting point of their experience history. The difference in the individuals' experience leads to heterogeneity among agents and perceived noise trading. The model captures several empirical findings. It explains why returns on high-volume trading days tend to revert. Furthermore, it provides explanations for a high trading volume, a connection between trading volume and volatility, excess volatility, and overreaction and reversal patterns. Consistent with empirical evidence, young investors buy high and sell low, trade frequently, and obtain lower returns. For intraday trading, it predicts a high trading volume around the opening hours, especially for cross-listed stocks.

Suggested Citation

  • Stefanie Schraeder, 2014. "Information Processing and Non-Bayesian Learning in Financial Markets," Swiss Finance Institute Research Paper Series 14-14, Swiss Finance Institute.
    • Handle: RePEc:chf:rpseri:rp1414
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