The advantages of using quarterly returns for long-term event studies
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The main purpose of this paper is to explore the low power and methodological problems as they continue to plague long-term event study research. We investigate long-term tests (up to 2 years) performed on non-overlapping quarterly time frames as a solution. Components of commonly employed characteristic-based matching processes are examined as the source of low power. Single “best” matching firms don’t statistically match their event firms at the time of the event and are vastly inferior to matching with portfolios. A modified market mean method which uses the securities continuously traded during the calendar event period, is shown to be well specified, have comparable power and avoid the costs of more complex matching methodologies. Contrary to popular perception, increased power derives from the decreased variance in comparison returns; not from an increased covariance between comparison firm returns and event firm returns. The tests are easy to implement, well-specified and have higher power when based on quarterly versus monthly data.
KeywordsLong-horizon performance studies Matching characteristics
JEL ClassificationC100 C150 G120 G140
We would like to thank Stephen Brown, Kim Sawyer, Ted Moore, Jeff Netter, LeRoy Brooks, Terry Shevlin, Rob Brown, Steven Mann, participants at the 2006 Financial Management Association Meetings and 2007 Southern Finance Association Meetings for their valuable suggestions and conversations regarding this paper. Any remaining errors are our own.