Comparing the Post–Earnings Announcement Drift for Surprises Calculated from Analyst and Time Series Forecasts


  • The authors gratefully acknowledge the preliminary and unrestated Compustat quarterly data provided by Charter Oak Investment Systems Inc. The authors are also grateful for the contribution of Thomson Financial for providing forecast data available through the Institutional Brokers Estimate System, as part of a broad academic program to encourage earnings expectations research. The authors also thank Shai Levi, an anonymous reviewer, and the editor for their comments on earlier versions of this paper.


Post–earnings announcement drift is the tendency for a stock's cumulative abnormal returns to drift in the direction of an earnings surprise for several weeks following an earnings announcement. We show that the drift is significantly larger when defining the earnings surprise using analysts' forecasts and actual earnings from I/B/E/S than when using a time series model based on Compustat earnings data. Neither Compustat's policy of restating earnings nor the inclusion of “special items” in reported earnings contribute significantly to the disparity in drift magnitudes. Rather, our results suggest that this disparity is attributable to differences between analyst forecasts and those of time-series models—or at least to factors correlated with these differences. Further, we document that analyst forecasts lead to return patterns around future earnings announcements that differ from those observed when using time-series models, suggesting that the two types of surprises may capture somewhat different forms of mispricing.