Warner’s scientific contributions

This paper examines properties of daily stock returns and how the particular characteristics of these data can affect event study methodologies. We find no evidence that either nonnormality in the time-series of daily excess returns or bias in OLS estimates of Market Model parameters affect the specification or power of tests for abnormal performance. However, under plausible conditions, both autocorrelation in excess returns and changes in the variance of daily returns conditional on an event can affect the tests; simple procedures to deal with these issues are sometimes quite useful. We also show that taking into account dependence in the cross-section of the daily excess returns can be harmful, resulting in tests with relatively low power and which are no better specified than those which assume independence.

Thesis (M. Sc.)--McGill University, 1996. Includes bibliographical references.