Detecting Long-Run Abnormal Stock Returns: The Empirical Power and Specification of Test Statistics
Posted: 9 May 1998
Date Written: January 1996
We analyze the empirical power and specification of test- statistics in event studies designed to detect long-run (one to five-year) abnormal stock returns. We consider (1) the calculation of long-run abnormal returns by comparing summed monthly abnormal returns (cumulative abnormal returns) to holding period abnormal returns (buy-and-hold abnormal returns), (2) the construction of an appropriate return benchmark by considering the use of reference portfolios, control firms, and an application of the Fama-French three-factor model, and (3) the impact of sampling biases. When long-run abnormal returns are calculated as the buy-and-hold return of a sample firm less the buy-and-hold return of a reference portfolio (such as a market index), we document that test-statistics are significantly negatively biased. However, this negative bias is alleviated when buy-and-hold abnormal returns are calculated as returns of sample firms less returns of an appropriately selected control firm.
JEL Classification: G12, G14
Suggested Citation: Suggested Citation