Event Study Testing with Cross-sectional Correlation of Abnormal Returns
发现事件日期聚类时，异常收益率的低度横截面相关也会导致零假设被过度拒绝，并提出了一个修正的t统计量来处理该问题，该统计量也适用于多日累积异常收益率的检验。
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 new test statistic that modifies the t-statistic of Boehmer, Musumeci, and Poulsen (1991) to take into account cross-correlation and show that it performs well in competition with others, including the portfolio approach, which is less powerful than other alternatives under study. Also, our statistic is readily useable to test multiple-day cumulative abnormal returns. The Author 2010. Published by Oxford University Press on behalf of The Society for Financial Studies. All rights reserved. For Permissions, please e-mail: journals.permissions@oxfordjournals.org., Oxford University Press.