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Journal of Finance Vol. 54 No. 1 1999

Improved Methods for Tests of Long‐Run Abnormal Stock Returns

John D. Lyon; Brad M. Barber; Chih‐Ling Tsai

Graduate School of Management, University of California , Davis

Abstract

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.

DOI
10.1111/0022-1082.00101
Volume
54
Issue
1
Pages
165-201
Language
en
Sources
openalex crossref

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