Tests of Long-Term Abnormal Performance: Analysis of Power
49 Pages Posted: 23 Mar 2009 Last revised: 10 Apr 2014
Date Written: April 10, 2014
In tests of long-term performance, researchers are faced with several research design choices. For instance, when estimating abnormal returns, what specific firm characteristics should be used as matching criteria to select control firms? What weights should be placed on each characteristic? Should an event firm be matched with one control firm or multiple control firms or with a reference portfolio? Should we use the calendar-time portfolio approach? We provide guidance to researchers on these questions by evaluating the power of the test using simulation analyses. We find that the quality of matching when selecting control firms has little impact on the power of the test. Among the alternative approaches studied, the Fama-French calendar-time portfolio approach obtains the highest power in random samples. Interestingly, we find that the higher power of this approach is attributable to the return aggregation method rather than the use of multiple risk factors or the in-sample fit of the model. In most nonrandom samples, the Fama-French approach obtains the highest power – the one exception being samples with extreme event-time clustering. Overall, for a reasonable sample size, the power of the best available methodology to detect economically significant abnormal returns is quite low.
Keywords: matching, Fama-French, calendar-time, misspecification
JEL Classification: C12, C52, G14
Suggested Citation: Suggested Citation