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A nonparametric test for marginal conditional stochastic dominance

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  • Edward Seiler

Abstract

This paper offers a nonparametric statistics test for Marginal Conditional Stochastic Dominance, that is then applied to a sample of stock returns. The test has three purposes: first, it offers a relatively simpleway to test for Stochastic Dominance, that is lacking in the literature. Second, it can be used to 'filter' results, aiding the decision taking of an agent who wants to satisfy a large group of investors whose preferences are not accurately known. Third, it can be used by a principal to check if an agent is acting in good faith.

Suggested Citation

  • Edward Seiler, 2001. "A nonparametric test for marginal conditional stochastic dominance," Applied Financial Economics, Taylor & Francis Journals, vol. 11(2), pages 173-177.
    • Handle: RePEc:taf:apfiec:v:11:y:2001:i:2:p:173-177
    DOI: 10.1080/096031001750071569
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    References listed on IDEAS

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    1. Shalit, Haim & Yitzhaki, Shlomo, 1984. "Mean-Gini, Portfolio Theory, and the Pricing of Risky Assets," Journal of Finance, American Finance Association, vol. 39(5), pages 1449-1468, December.
    2. Yitzhaki, Shlomo, 1991. "Calculating Jackknife Variance Estimators for Parameters of the Gini Method," Journal of Business & Economic Statistics, American Statistical Association, vol. 9(2), pages 235-239, April.
    3. Haim Levy, 1992. "Stochastic Dominance and Expected Utility: Survey and Analysis," Management Science, INFORMS, vol. 38(4), pages 555-593, April.
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    Cited by:

    1. Schumann, Keith D., 2011. "Semi-nonparametric test of second degree stochastic dominance with respect to a function," Journal of Econometrics, Elsevier, vol. 162(1), pages 71-78, May.
    2. Clark, Ephraim & Jokung, Octave & Kassimatis, Konstantinos, 2011. "Making inefficient market indices efficient," European Journal of Operational Research, Elsevier, vol. 209(1), pages 83-93, February.

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