Short-Horizon Event Study Estimation with a STAR Model and Real Contaminated Events

44 Pages Posted: 30 Oct 2014 Last revised: 24 Apr 2015

Panayiotis C. Andreou

Cyprus University of Technology

Christodoulos Louca

Cyprus University of Technology

Christos S. Savva

Cyprus University of Technology - Department of Commerce, Finance and Shipping

Date Written: February 2015

Abstract

We propose a test statistic for nonzero mean abnormal returns based on a Smooth Transition Auto Regressive (STAR) specification. Estimation of the STAR test statistic takes into account the probability of unrelated events that could otherwise bias the parameters of the market model and thus the specification and power of the resulting test statistics. Using both simulated and real stock returns data from mergers and acquisitions, we find that the STAR test statistic is robust to unrelated events happening in the event-study estimation window and in the presence of variance-induced events. Under the STAR test statistic the true null hypothesis is rejected at appropriate levels. Moreover, it exhibits the highest levels of power when compared with other test statistics that are widely and routinely applied in the event-study approach.

Keywords: Event studies, parametric test statistics, unrelated events, Markov switching regression model, Smooth Transition Auto Regressive (STAR) model

JEL Classification: G14, G34

Suggested Citation

Andreou, Panayiotis C. and Louca, Christodoulos and Savva, Christos S., Short-Horizon Event Study Estimation with a STAR Model and Real Contaminated Events (February 2015). Available at SSRN: https://ssrn.com/abstract=2516068 or http://dx.doi.org/10.2139/ssrn.2516068

Panayiotis C. Andreou (Contact Author)

Cyprus University of Technology ( email )

School Of Management and Economics
P.O. Box 50329
Lemesos, 3036
Cyprus

HOME PAGE: http://www.pandreou.com

Christodoulos Louca

Cyprus University of Technology ( email )

Limassol, 3603
Cyprus

Christos S. Savva

Cyprus University of Technology - Department of Commerce, Finance and Shipping ( email )

Limassol, 3603
Cyprus
00357252349 (Phone)
00357252674 (Fax)

HOME PAGE: http://www.csavva.com

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