Asymmetric Learning from Prices and Post‐Earnings‐Announcement Drift
假设投资者只在价格明确显示他人获得与自己不同的私有信息时才从中学习，这种不对称学习导致了盈余公告后漂移，并产生套利机会，模型还预测漂移集中在非应计盈余意外中。
ABSTRACT Motivated by research in psychology and experimental economics, we assume that investors update their beliefs about an asset's value upon observing the price, but only when the price clearly reveals that others obtained private information that differs from their own private information. Specifically, we assume that investors learn from the price of an asset in an asymmetric manner—they learn from the price if they observe good (bad) private information and the price is worse (better) than what is justified based on public information alone. We show that asymmetric learning from an asset's price leads to post‐earnings‐announcement drift (PEAD), and that it generates arbitrage opportunities that are less attractive than alternative explanations of PEAD. In addition, our model predicts that PEAD will be concentrated in earnings surprises that are not dominated by accruals, and it also predicts that earnings response coefficients will decline in the magnitude of the earnings surprises.