Improved methods for tests of long-run abnormal stock returns

• 成果类型: Article
• 署名作者: Lyon, JD; Barber, BM; Tsai, CL
• 署名单位: University of California System; University of California Davis
• 刊物名称: JOURNAL OF FINANCE
• ISSN/ISSBN: 0022-1082
• DOI: 10.1111/0022-1082.00101
• 发表日期: 1999
• 页码: 165-201
• 关键词: initial public offerings; Book-to-market; COMPUTED RETURNS; Trading rules; cross-section; firm size; performance; selection; biases

摘要

We analyze tests for long-run abnormal returns and document that two approaches yield well-specified test statistics in random samples. The first uses a traditional event study framework and buy-and-hold abnormal returns calculated using carefully constructed reference portfolios. Inference is based on either a skewness-adjusted t-statistic or the empirically generated distribution of long-run abnormal returns. The second approach is based on calculation of mean monthly abnormal returns using calendar-time portfolios and a time-series t-statistic. Though both approaches perform well in random samples, misspecification in nonrandom samples is pervasive. Thus, analysis of long-run abnormal returns is treacherous.