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A Note on Testing for Skewness Persistence

Author

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  • Ravinder Nath

    (Department of Management Information Systems and Decision Science, Fogelman College of Business and Economics, The University of Memphis, Memphis, Tennessee 38152)

Abstract

This paper shows that the tests of skewness persistence considered by Muralidhar (Muralidhar, K. 1993. The bootstrap approach for testing skewness persistence. Management Sci. 39 487--491.) far exceed the true Type I error. That is, the probabilities of detecting an increase (decrease) in skewness from one time period to another when in fact there is no change are inflated. Consequently, higher power achieved by these tests comes at the cost of a higher than specified level of Type I error. We propose a new test which maintains the specified Type I error levels. Additionally, the power of this test for lognormal distributions is reported.

Suggested Citation

  • Ravinder Nath, 1996. "A Note on Testing for Skewness Persistence," Management Science, INFORMS, vol. 42(1), pages 138-141, January.
    • Handle: RePEc:inm:ormnsc:v:42:y:1996:i:1:p:138-141
    DOI: 10.1287/mnsc.42.1.138
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    Cited by:

    1. Peter Huber & Michael Pfaffermayr, 2010. "Testing for Conditional Convergence in Variance and Skewness: The Firm Size Distribution Revisited," Oxford Bulletin of Economics and Statistics, Department of Economics, University of Oxford, vol. 72(5), pages 648-668, October.
    2. Petchey, James & Wee, Marvin & Yang, Joey, 2016. "Pinning down an effective measure for probability of informed trading," Pacific-Basin Finance Journal, Elsevier, vol. 40(PB), pages 456-475.

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