Post-Earnings Announcement Drift and the Dissemination of Predictable Information

Building on the work of Bernard and Thomas 1990, we develop a model to infer the degree to which the information in an earnings announcement is incorporated into investors' expectations for the subsequent earnings announcement at any point in time between the two announcements. We are unable to reject the null hypothesis that investors' earnings expectations are based on a seasonal random walk and reflect none of the implications of the immediately prior earnings announcement up to 15 trading days after that announcement. By mid-quarter, expectations are significantly more sophisticated than a seasonal random walk. Two trading days before the next earnings announcement, as much as one half of the information in the prior earnings announcement is reflected in earnings expectations. We also find that the dissemination of information, albeit predictable information, speeds the incorporation of prior earnings information into earnings expectations. Our results suggest that as information about future earnings that could have been discerned from the earlier announcements (because past earnings surprises predict future ones) is disseminated in a more transparent form, investors revise their earnings expectations to reflect this information. Thus, the investors' expectations appear to incorporate more and more of the serial correlation in earnings surprises as the quarter progresses, even though they do not consider per se the serial correlation in earnings surprises in forming their expectations.