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Evaluating the Robustness of MarketAnomaly Evidence

In: Advances In Quantitative Analysis Of Finance And Accounting

Author

Listed:
  • William D. Brown Jr.

    (Stonehill College, USA)

  • Erin A. Moore

    (Lehigh University, USA)

  • Ray J. Pfeiffer Jr.

    (University of Massachusetts, USA)

Abstract

This study investigates two ways that sample selection can impact inferences about market efficiency: (1) unintentional, nonrandom exclusion of observations because of lack of available data for some firm-years (“passive deletion”); and (2) the effects of extreme return observations. The analysis proposes and illustrates a set of simple diagnostic tests designed to assess the sensitivity of estimated hedge portfolio returns to sample composition. These diagnostics are applied to the accrual anomaly and the forecast-to-price anomaly and the results indicate that the forecast-to-price anomaly is not robust to the effects of passive deletion. Moreover, extreme returns — as few as 100 firm-year observations — appear to generate the observed abnormal returns to both strategies.

Suggested Citation

  • William D. Brown Jr. & Erin A. Moore & Ray J. Pfeiffer Jr., 2008. "Evaluating the Robustness of MarketAnomaly Evidence," World Scientific Book Chapters, in: Cheng-Few Lee (ed.), Advances In Quantitative Analysis Of Finance And Accounting, chapter 3, pages 27-47, World Scientific Publishing Co. Pte. Ltd..
    • Handle: RePEc:wsi:wschap:9789812791696_0003
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    More about this item

    Keywords

    Hedging Strategies; Expense Mismatching; Stock Split; Trading Volume; Portfolio Optimization; Intraday Patterns; Earnings Management; International Winner-Loser Effect;
    All these keywords.

    JEL classification:

    • G2 - Financial Economics - - Financial Institutions and Services
    • G3 - Financial Economics - - Corporate Finance and Governance

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