Journal of Finance Vol. 55 No. 5 2000
Inference in Long‐Horizon Event Studies: A Bayesian Approach with Application to Initial Public Offerings
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.
- DOI
- 10.1111/0022-1082.00279
- Volume
- 55
- Issue
- 5
- Pages
- 1979-2016
- Language
- en
- Sources
- bibtex:phds-export.bib openalex crossref