Improved Methods for Tests of Long-Run Abnormal Stock Returns

Posted: 8 Oct 1997

See all articles by Brad M. Barber

Brad M. Barber

University of California, Davis

Chih-Ling Tsai

University of California, Davis - Graduate School of Management

Date Written: July 31, 1997

Abstract

Barber and Lyon (1997a) and Kothari and Warner (1997) document that standard tests of long-run abnormal returns are misspecified. In this research, we evaluate alternative methods to test for long-run abnormal returns. We document that two general approaches yield well-specified test statistics in random samples. The first approach uses a traditional event study framework and buy-and-hold abnormal returns calculated using carefully constructed reference portfolios, such that the population mean abnormal return is identically zero. Inference is based on either a skewness-adjusted t statistic or the empirically generated distribution of mean long-run abnormal returns. The second approach is based on the 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. Our central message is that the analysis of long-run abnormal returns is treacherous.

JEL Classification: C12, G12

Suggested Citation

Barber, Brad M. and Tsai, Chih-Ling, Improved Methods for Tests of Long-Run Abnormal Stock Returns (July 31, 1997). Available at SSRN: https://ssrn.com/abstract=11198

Brad M. Barber

University of California, Davis ( email )

Graduate School of Management
One Shields Avenue
Davis, CA 95616
United States
530-752-0512 (Phone)
530-752-2924 (Fax)

Chih-Ling Tsai

University of California, Davis - Graduate School of Management ( email )

One Shields Avenue
Davis, CA 95616
United States

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