Objective estimation versus subjective perceptions of earnings patterns and post-earnings-announcement drift

摘要

We investigate how the market's subjective estimates of autocorrelation in quarterly earnings vary with objective time-series estimates. Our results suggest that investors increasingly underestimate the correlation as the autocorrelation level increases, and as a result, the post-earnings-announcement drift (PEAD) increases with the level of autocorrelation. We further show that the ability of autocorrelation to explain variation in the PEAD is robust to alternative explanations based on risk and institutional factors. Additional analysis indicates that the market's inefficiency in assessing the existence and magnitude of autocorrelation (and the related impact on PEAD) is inversely related to the richness of the information environment.