The advantages of using quarterly returns for long-term event studies

The advantages of using quarterly returns for long-term event studies 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. http://www.deepdyve.com/assets/images/DeepDyve-Logo-lg.png Review of Quantitative Finance and Accounting Springer Journals

The advantages of using quarterly returns for long-term event studies

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Publisher
Springer US
Copyright
Copyright © 2010 by Springer Science+Business Media, LLC
Subject
Finance; Corporate Finance; Accounting/Auditing; Econometrics; Operation Research/Decision Theory
ISSN
0924-865X
eISSN
1573-7179
D.O.I.
10.1007/s11156-010-0191-2
Publisher site
See Article on Publisher Site

Abstract

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.

Journal

Review of Quantitative Finance and AccountingSpringer Journals

Published: Jul 11, 2010

References

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