Event Studies and Outlier Returns: Symptoms, Consequences and Treatment

31 Pages Posted: 19 Aug 2019

See all articles by Panayiotis Theodossiou

Panayiotis Theodossiou

Cyprus University of Technology

Alexandra K. Theodossiou

Texas A&M University-Corpus Christi-College of Business

Date Written: August 16, 2019

Abstract

This paper makes specifics contributions in the methodology of event studies. First, it develops a financial econometrics framework for understanding, measuring and testing the impact of outlier returns on the estimated parameters of stock return models. Second, it presents a maximum likelihood robust estimation method that enables the decomposition of a firm’s stock returns into regular and outlier returns for the purpose of computing robust or outlier resistant CAR statistics. Third, it presents analytical results on how outliers in the estimation sample affect OLS-CAR statistics. Results based on extensive Monte Carlo and actual data simulations, depict that outliers in the estimation sample affect adversely and significantly the performance of the OLS-CAR statistics in event studies. Outliers, however, do not impair the forecasting ability of the robust-CAR statistics introduced in this paper.

Keywords: Multifactor stock return models, CAR-cumulative abnormal returns, outlier resistant estimators, Monte Carlo simulations

JEL Classification: C58, G12, G14, G34

Suggested Citation

Theodossiou, Panayiotis and Theodossiou, Alexandra K., Event Studies and Outlier Returns: Symptoms, Consequences and Treatment (August 16, 2019). Available at SSRN: https://ssrn.com/abstract=3438274 or http://dx.doi.org/10.2139/ssrn.3438274

Panayiotis Theodossiou (Contact Author)

Cyprus University of Technology ( email )

Limassol, 3603
Cyprus

Alexandra K. Theodossiou

Texas A&M University-Corpus Christi-College of Business ( email )

6300 Ocean Drive
Corpus Christi, TX 78412
United States

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