ABSTRACT Event studies of market efficiency measure earnings surprises using the consensus error ( CE ), given as actual earnings minus the average professional forecast. If a subset of forecasts can be biased, the ideal but difficult to estimate parameter‐dependent alternative to CE is a nonlinear filter of individual errors that adjusts for bias. We show that CE is a poor parameter‐free approximation of this ideal measure. The fraction of misses on the same side ( FOM ), which discards the magnitude of misses, offers a far better approximation. FOM performs particularly well against CE in predicting the returns of U.S. stocks, where bias is potentially large.

ABSTRACT: This study tests whether nai¨ve trading by individual investors, or some class of individual investors, causes post-earnings announcement drift (PEAD). Inconsistent with the individual trading hypothesis, individual investor trading fails to subsume any of the power of extreme earnings surprises to predict future abnormal returns. Moreover, individuals are significant net buyers after both negative and positive extreme earnings surprises, consistent with an attention effect, but not with their trades causing PEAD. Finally, we find no indication that trading by individuals explains the concentration of drift at subsequent earnings announcement dates.