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

44 Pages Posted: 10 Aug 1998

See all articles by Alon Brav

Alon Brav

Duke University - Fuqua School of Business

Date Written: August 1998

Abstract

Statistical inference in many 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. To illustrate the use of the methodology, long-horizon returns of initial public offerings (IPOs) are examined. Inference using the new procedure is shown to be sensitive to both non-normality and cross-correlation and to dominate other popular testing methods.

JEL Classification: G12, G14

Suggested Citation

Brav, Alon, Inference in Long Horizon Event Studies: A Bayesian Approach with Application to Initial Public Offerings (August 1998). Available at SSRN: https://ssrn.com/abstract=90253 or http://dx.doi.org/10.2139/ssrn.90253

Alon Brav (Contact Author)

Duke University - Fuqua School of Business ( email )

Box 90120
Durham, NC 27708-0120
United States
919-660-2908 (Phone)
919-684-2818 (Fax)

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