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Improved Methods for Tests of Long‐Run Abnormal Stock Returns

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

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.

Suggested Citation

  • John D. Lyon & Brad M. Barber & Chih‐Ling Tsai, 1999. "Improved Methods for Tests of Long‐Run Abnormal Stock Returns," Journal of Finance, American Finance Association, vol. 54(1), pages 165-201, February.
    • Handle: RePEc:bla:jfinan:v:54:y:1999:i:1:p:165-201
    DOI: 10.1111/0022-1082.00101
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