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Measuring Abnormal Performance: The Event Parameter Approach Using Joint Generalized Least Squares
Paul H. Malatesta
The Journal of Financial and Quantitative Analysis
Vol. 21, No. 1 (Mar., 1986), pp. 27-38
Published by: Cambridge University Press on behalf of the University of Washington School of Business Administration
Stable URL: http://www.jstor.org/stable/2330988
Page Count: 12
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Event studies generally seek to measure abnormal security performance associated with firm-specific events. In principle, estimators of and tests for abnormal performance should appropriately reflect cross-sectional dependence between abnormal returns to different securities. Joint generalized least squares provides a natural framework for developing such estimators and tests. This paper derives a joint generalized least squares estimator and related test statistic applicable in the typical event study context. Simulation techniques comparable to those of Brown and Warner  are used to assess the frequency distribution of the estimator and power of the test statistic. Several simpler procedures are simulated for comparison. The results provide no evidence that joint generalized least squares is superior to simpler procedures.
The Journal of Financial and Quantitative Analysis © 1986 University of Washington School of Business Administration