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

Author

Listed:
  • Panayiotis C. Andreou

    (Cyprus University of Technology
    Mill Hill Lane)

  • Christodoulos Louca

    (Cyprus University of Technology
    Mill Hill Lane)

  • Christos S. Savva

    (Cyprus University of Technology
    University of Manchester)

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.

Suggested Citation

  • Panayiotis C. Andreou & Christodoulos Louca & Christos S. Savva, 2016. "Short-horizon event study estimation with a STAR model and real contaminated events," Review of Quantitative Finance and Accounting, Springer, vol. 47(3), pages 673-697, October.
    • Handle: RePEc:kap:rqfnac:v:47:y:2016:i:3:d:10.1007_s11156-015-0515-3
    DOI: 10.1007/s11156-015-0515-3
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    Cited by:

    1. Yasser Alhenawi & Martha Stilwell, 2017. "Value creation and the probability of success in merger and acquisition transactions," Review of Quantitative Finance and Accounting, Springer, vol. 49(4), pages 1041-1085, November.
    2. Onur Enginar & Kazim Baris Atici, 2022. "Optimal forecast error as an unbiased estimator of abnormal return: A proposition," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(1), pages 158-166, January.
    3. Liam Gallagher & Mark Hutchinson & John O’Brien, 2018. "Does Convertible Arbitrage Risk Exposure Vary Through Time?," Review of Pacific Basin Financial Markets and Policies (RPBFMP), World Scientific Publishing Co. Pte. Ltd., vol. 21(04), pages 1-25, December.

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    More about this item

    Keywords

    Event studies; Test statistics; Contaminated events; Markov switching regression model; Smooth Transition Auto Regressive model;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G34 - Financial Economics - - Corporate Finance and Governance - - - Mergers; Acquisitions; Restructuring; Corporate Governance

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