Abstract
Event studies have been used to examine the direction, magnitude, and speed of security price reactions to various phenomenon. Concerns over the lack of normality in stock return distributions motivated the introduction of nonparametric test statistics in the event study literature. A parametric procedure (OLS), however, has been extensively employed in the estimation of parameters for the market model. This paper, in contrast, applies Theil's nonparametric regression in the estimation of abnormal returns; an approach which is distribution free and provides a complete nonparametric approach for the detection of abnormal performance. Simulation results indicate Theil's estimation procedure offers a slight improvement in power in the detection of abnormal performance over the traditionally employed methodology. The results suggest employing Theil's nonparametric estimation procedure combined with the rank statistic. This complete nonparametric combination offers similar power with fewer underlying assumptions.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Andrews, D.F., Robust Estimates of Location, Princeton: Princeton University Press, 1972.
Barber, B.M. and J.D. Lyon, “Detecting Long-run Abnormal Stock Returns: The Empirical Power and Specification of Test Statistics.” Journal of Financial Economics 43, 341–372, (1997).
Boehmer, E., J. Musumeci, and A.B. Poulsen, “Event-Study Methodology Under Conditions of Event-Induced Variance.” Journal of Financial Economics 30, 253–272, (1991).
Brown, S. and J. Warner, “Measuring Security Price Performance.” Journal of Financial Economics 8, 205–258, (1980).
Brown, S. and J. Warner, “Using Daily Stock Returns: The Case of Event Studies.” Journal of Financial Economics 14, 3–31, (1985).
Campbell, C. and C. Wasley, “Measuring Security Price Performance Using Daily NASDAQ Returns.” Journal of Financial Economics 33, 73–92, (1993).
Chan, K.C.L. and J. Lakonishok, “Robust Measurement of Beta Risk.” Journal of Financial and Quantitative Analysis 27, 265–282, (1992).
Corrado, C., “A Nonparametric Test for Abnormal Security Price Performance in Event Studies.” The Journal of Financial Economics 23, 385–395, (1989).
Cowan, A. “Nonparametric Event Study Tests.” Review of Quantitative Finance and Accounting 2, 343–358, (1992).
Dielman, T. and R. Pfaffenberger, “LAV (Least Absolute Value) Estimation in Linear Regression: A Review.” TIMS Studies in Management Sciences: Optimization in Statistics, S. Zonakis and J. Rustagi eds. Amsterdam North Holland Publishing Company 31–52, (1982).
Dodd, P. and J. Warner, “On Corporate Governance.” Journal of Financial Economics 11, 401–438, (1983).
Fama, E.F., L. Fisher, M.C. Jensen, and R. Roll, “The Adjustment of Stock Prices to New Information.” International Economic Review 10, 1–21, (1969).
Hussain, S.S. and P. Sprent, “Nonparametric Regression.” Journal of the Royal Statistical Society Series A 146, 182–191, (1983).
Kothari, S.P. and J.B. Warner, “Measuring Long-Horizon Security Price Performance.” Journal of Financial Economics 43, 301–339, (1997).
MacKinlay, A.C., “Event Studies in Economics and Finance.” Journal of Economic Literature 35, 13–39, (1997).
Patell, J.M. “Corporate Forecasts of Earnings per Share and Stock Price Behavior: Empirical Tests.” Journal of Accounting Research 246–276, (1976).
Peterson, P.P., “Event Studies: A Review of Issues and Methodology.” Quarterly Journal of Business and Economics 28, 36–66, (1989).
Sanger, G.C. and J.D. Peterson, “An Empirical Analysis of Common Stock Delistings.” Journal of Financial and Quantitative Analysis 25, 261–272, (1990).
Talwar, P.P. “A Simulation Study of Some Nonparametric Regression Estimators.” Computational Statistics and Data Analysis, 15, 309–327, (1993).
Theil, H., “A Rank Invariant Method of Linear and Polynomial Regression Analysis.” I, II, and III Nederl. Akad. Wektensch. Proc. 53, 386–392, 521-525 and 1897-1912, (1950).
Author information
Authors and Affiliations
Rights and permissions
About this article
Cite this article
Dombrow, J., Rodriguez, M. & Sirmans, C. A Complete Nonparametric Event Study Approach. Review of Quantitative Finance and Accounting 14, 361–380 (2000). https://doi.org/10.1023/A:1008371810113
Issue Date:
DOI: https://doi.org/10.1023/A:1008371810113