This study investigates the role of time-varying betas, event-induced variance
and conditional heteroskedasticity in the estimation of abnormal returns around important news announcements. Our analysis is based on the stock price reaction to profit warnings issued by a sample of firms listed on the Hong Kong Stock Exchange. The standard event study methodology indicates the presence of price reversal patterns following both positive and negative warnings. However, incorporating time-varying betas, event-induced variance and conditional heteroskedasticity in the modelling process results in post-negative-warning price patterns that are consistent with the predictions of the efficient market hypothesis. These adjustments also cause the statistical significance of
some post-positive-warning cumulative abnormal returns to disappear and their magnitude to drop to an extent that minor transaction costs would eliminate the profitability of the contrarian strategy.