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

  • Author(s): Alon Brav
  • Published: Dec 17, 2002
  • Pages: 1979-2016
  • DOI: 10.1111/0022-1082.00279

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.

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