Please use this identifier to cite or link to this item: https://ktisis.cut.ac.cy/handle/10488/14555
Title: Short-horizon event study estimation with a STAR model and real contaminated events
Authors: Andreou, Panayiotis C. 
Louca, Christodoulos 
Savva, Christos S. 
Keywords: Smooth Transition Auto Regressive model;Contaminated events;Event studies;Markov switching regression model;Test statistics
Category: Economics and Business
Field: Social Sciences
Issue Date: 2016
Source: Review of Quantitative Finance and Accounting Volume 47, Issue 3, 1 October 2016, Pages 673-697
Journal: Review of Quantitative Finance and Accounting 
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.
URI: https://ktisis.cut.ac.cy/handle/10488/14555
ISSN: 2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
0924865X
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
2-s2.0-84928974748
https://api.elsevier.com/content/abstract/scopus_id/84928974748
DOI: 10.1007/s11156-015-0515-3
Rights: © 2015, Springer Nature.
Type: Article
Appears in Collections:Άρθρα/Articles

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