Dynamic risk adjustment in long-run event study tests

Abstract

ABSTRACTThe existence of long-run abnormal returns after major corporate events has become a controversial subject of debate. We contribute new evidence by implementing a daily rolling prediction error (RPE) approach using popular asset pricing models to adjust for time-varying risk parameters in asset pricing models when estimating long-run abnormal returns. Using this simple approach, we find initial significant return responses in the month or two after SEOs and M&As but none thereafter. Robustness checks with different asset pricing models, corporate events, and subperiods corroborate our results. Also, simulation tests confirm the robustness of the RPE method to potential risk shifts. We conclude that, after dynamic risk adjustment, long-run abnormal returns do not occur after the major corporate actions under study.