We report simulations of one-, three-, and five-year abnormal buy-and-hold stock return tests. Using benchmark portfolios purged of new-listings and rebalancing biases, we find severe misspecification of most tests, due in part to skewness. Control-firm matching also results in misspecification, particularly in large samples. We document a negative relation between skewness bias and sample size, and an overlapping-horizons bias. Both biases become more severe as the holding period lengthens. The biases interact such that tests can be well-specified in one situation but not another. A two groups test using winsorized abnormal returns yields correct specification and considerable power in many situations.

We examine the effects of thin trading on the specification of event study tests. Simulations of upper and lower tail tests are reported with and without variance increases on the event date across levels of trading volume. The traditional standardized test is misspecified for thinly traded samples. If return variance is unlikely to increase, then Corrado's rank test provides the best specification and power. With variance increases, the rank test is misspecified. The Boehmer et al. standardized cross-sectional test (Event-study methodology under conditions of event-induced variance, Journal of Financial Economics 30, pp. 253–272) is properly specified, but not powerful, for upper-tailed tests. Lower-tailed alternative hypotheses can best be evaluated using the generalized sign test.