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Short-horizon event study estimation with a STAR model and real contaminated events

Short-horizon event study estimation with a STAR model and real contaminated events We propose a test statistic for nonzero mean abnormal returns based on a Smooth Transition Auto Regressive (STAR) model specification. Estimation of STAR takes into account the probability of contaminated events that could otherwise bias the parameters of the market model and thus the specification and power of the test statistic. Using both simulated and real stock returns data from mergers and acquisitions, we find that the STAR test statistic is robust to contaminated events occurring in the estimation window and in the presence of event-induced increase in return variance. 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 short-horizon event studies. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

Short-horizon event study estimation with a STAR model and real contaminated events

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References (56)

Publisher
Springer Journals
Copyright
Copyright © 2015 by Springer Science+Business Media New York
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
DOI
10.1007/s11156-015-0515-3
Publisher site
See Article on Publisher Site

Abstract

We propose a test statistic for nonzero mean abnormal returns based on a Smooth Transition Auto Regressive (STAR) model specification. Estimation of STAR takes into account the probability of contaminated events that could otherwise bias the parameters of the market model and thus the specification and power of the test statistic. Using both simulated and real stock returns data from mergers and acquisitions, we find that the STAR test statistic is robust to contaminated events occurring in the estimation window and in the presence of event-induced increase in return variance. 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 short-horizon event studies.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: May 7, 2015

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