Measuring Abnormal Performance: The Event Parameter Approach Using Joint Generalized Least Squares

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Abstract
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 [2] 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.

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