This article examines the issue of cross-sectional correlation in event studies. When there is event-date clustering, we find that even relatively low cross-correlation among abnormal returns is serious in terms of over-rejecting the null hypothesis of zero average abnormal returns.We propose a...

This study applies a rolling estimation window approach to adjust for time-varying risk parameters in asset pricing models to compute long-run abnormal returns after major corporate events. Abnormal returns are defined as realized returns minus predicted returns on each day in a five-year,...

This paper proposes a novel standardized test for abnormal returns in long-horizon event studies that takes into account cross-sectional correlation, autocorrelation, and hetersoskedasticity of stock returns. Extensive simulation analyses demonstrate improved size and power of testing relative...

This article re-examines the issue of cross-sectional correlation. Kolari and Pynnonen (2010) find that, in the case of event-date clustering with the same event window for all firms, relatively low cross-sectional correlation among abnormal returns can seriously bias standard tests to...