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Testing excess returns on event days: Log returns vs. dollar returns

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  • Duarte-Silva, Tiago
  • Tripolski Kimel, Maria

Abstract

The results of academic and practitioners’ event studies are often translated from excess log returns into excess dollar returns. The prior literature argues for a difference between the statistical significance of excess log returns and that of excess dollar returns. In contrast, we show analytically and using simulations that specifying event study hypotheses in terms of excess dollar returns is equivalent to specifying them in terms of excess log returns. The prior literature’s result was due to a bias in the estimator of expected excess dollar returns, an incorrect assumption that it is approximately normally distributed, and a misapplication of the delta method.

Suggested Citation

  • Duarte-Silva, Tiago & Tripolski Kimel, Maria, 2014. "Testing excess returns on event days: Log returns vs. dollar returns," Finance Research Letters, Elsevier, vol. 11(2), pages 173-182.
  • Handle: RePEc:eee:finlet:v:11:y:2014:i:2:p:173-182
    DOI: 10.1016/j.frl.2014.03.001
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    1. Grinblatt, Mark & Titman, Sheridan, 1993. "Performance Measurement without Benchmarks: An Examination of Mutual Fund Returns," The Journal of Business, University of Chicago Press, vol. 66(1), pages 47-68, January.
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    3. Jonathan B. Berk & Jules H. van Binsbergen, 2012. "Measuring Managerial Skill in the Mutual Fund Industry," NBER Working Papers 18184, National Bureau of Economic Research, Inc.
    4. Asquith, Paul, 1948- & Bruner, Robert F., 1949- & Mullins, David W., 1990. "Merger returns and the form of financing," Working papers 3203-90., Massachusetts Institute of Technology (MIT), Sloan School of Management.
    5. Francis, J & Philbrick, D & Schipper, K, 1994. "Shareholder Litigation And Corporate Disclosures," Journal of Accounting Research, Wiley Blackwell, vol. 32(2), pages 137-164.
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    Cited by:

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    More about this item

    Keywords

    Event study; Dollar return; Statistical significance;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • K22 - Law and Economics - - Regulation and Business Law - - - Business and Securities Law
    • C12 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Hypothesis Testing: General
    • C13 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods and Methodology: General - - - Estimation: General

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