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

Alon Brav

Journal of Finance, 2000, vol. 55, issue 5, 1979-2016

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.

Date: 2000
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Persistent link: https://EconPapers.repec.org/RePEc:bla:jfinan:v:55:y:2000:i:5:p:1979-2016

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