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Inference in Long-Horizon Event Studies: A Bayesian Approach with Application to Initial Public Offerings

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  • Alon Brav

    (Duke University, Fuqua School of Business)

Abstract

Statistical inference in long-horizon event studies has been hampered by the fact that abnormal returns are neither normally distributed nor independent. This study presents a new approach to inference that overcomes these difficulties and dominates other popular testing methods. I illustrate the use of the methodology by examining the long-horizon returns of initial public offerings (IPOs). I find that the Fama and French (1993) three-factor model is inconsistent with the observed long-horizon price performance of these IPOs, whereas a characteristic-based model cannot be rejected. Copyright The American Finance Association 2000.

Suggested Citation

  • Alon Brav, 2000. "Inference in Long-Horizon Event Studies: A Bayesian Approach with Application to Initial Public Offerings," Journal of Finance, American Finance Association, vol. 55(5), pages 1979-2016, October.
  • Handle: RePEc:bla:jfinan:v:55:y:2000:i:5:p:1979-2016
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