| Abstract: | We analyze event abnormal returns when returns predict events.In fixed samples, we show that the expected abnormal returnis negative and becomes more negative as the holding periodincreases. Asymptotically, abnormal returns converge to zeroprovided that the process of the number of events is stationary.Nonstationarity in the process of the number of events is neededto generate a large negative bias. We present theory and simulationsfor the specific case of a lognormal model to characterize themagnitude of the small-sample bias. We illustrate the theoryby analyzing long-term returns after initial public offerings(IPOs) and seasoned equity offerings (SEOs). |
