Dynamic Risk Adjustment in Long-Run Event Study Tests

59 Pages Posted: 15 Feb 2020 Last revised: 15 Apr 2020

See all articles by Yao Han

Yao Han

Texas A&M University - Department of Finance

James W. Kolari

Texas A&M University - Department of Finance

Seppo Pynnonen

University of Vaasa, Department of Mathematics and Statistics

Date Written: January 21, 2020

Abstract

This study applies a rolling estimation window approach to adjust for time-varying risk parameters in asset pricing models to compute long-run abnormal returns after major corporate events. Abnormal returns are defined as realized returns minus predicted returns on each day in a five-year, post-event period. A variety of asset pricing models are employed to compute out-of-sample predicted returns in different estimation windows for seasoned equity offerings (SEOs) and mergers and acquisitions (M&As). We find that, after an initial significant return response in the month or two after corporate announcements, abnormal returns thereafter disappear over a five-year, post-event period. Robustness checks corroborate our results: (1) with or without matched and random control samples, (2) for different asset pricing models including the CAPM market model, and (3) in robustness tests of share repurchases (SRs) as well as different subperiods. We conclude that, after dynamic risk adjustment, long-run abnormal returns are not evident after these major corporate actions.

Keywords: Abnormal return, Long-run event study, Merger and acquisition, Seasoned equity offering, Share repurchases, Short-run event study

JEL Classification: C10, G14, G32, G34, G35

Suggested Citation

Han, Yao and Kolari, James W. and Pynnonen, Seppo, Dynamic Risk Adjustment in Long-Run Event Study Tests (January 21, 2020). Available at SSRN: https://ssrn.com/abstract=3523270 or http://dx.doi.org/10.2139/ssrn.3523270

Yao Han

Texas A&M University - Department of Finance ( email )

430 Wehner
College Station, TX 77843-4218
United States

James W. Kolari (Contact Author)

Texas A&M University - Department of Finance ( email )

MS-4218
Department of Finance
College Station, TX TX 77843-4218
United States
979-845-4803 (Phone)
979-845-3884 (Fax)

Seppo Pynnonen

University of Vaasa, Department of Mathematics and Statistics ( email )

Wolffintie 34
65200 Vaasa
Finland
+358-21-449 8311 (Phone)

HOME PAGE: http://www.uva.fi/~sjp/

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