Stochastic Dominance Decision Rules

  • Haim Levy
Part of the Studies in Risk and Uncertainty book series (SIRU, volume 12)

Abstract

We have seen that the MEUC is the optimal investment criterion. If there is full information on preferences (e.g., U(w) = log (w)), we simply calculate EU(w) of all the competing investments and choose the one with the highest expected utility. In such a case, we arrive at a complete ordering of the investments under consideration: there will be one investment which is better than (or equal to) all of the other available investments. Moreover, with a complete ordering, we can order the investments from best to worst. Generally, however, we have only partial information on preferences (e.g., risk aversion) and, therefore, we arrive only at a partial ordering of the available investments. Stochastic dominance rules as well as other investment rules (e.g., the mean-variance rule) employ partial information on the investor’s preferences or the random variables (returns) and, therefore, they produce only partial ordering.

Keywords

Utility Function Risk Aversion Mutual Fund Stochastic Dominance Positive Skewness 
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Notes

  1. 1.
    Hanoch, G. and H. Levy, “The Efficiency Analysis of Choices Involving Risk,” Review of Economic Studies, 36, 1969, pp. 335–346.CrossRefGoogle Scholar
  2. 2.
    Tesfatsion, L., “Stochastic Dominance and the Maximization of Expected Utility,” Review of Economic Studies, 43, 1976, pp. 301–15.CrossRefGoogle Scholar
  3. 10.
    See K.J. Arrow, Aspects of the Theory of Risk: Bearings, Helsenki, Yrjö Jahnssonin Säätiö, 1965.Google Scholar
  4. 17.
    Hanoch, G. and H. Levy, “The Efficiency Analysis of Choices Involving Risk,” Review of Economic Studies, 36, pp. 335–346, 1969.CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media New York 1998

Authors and Affiliations

  • Haim Levy
    • 1
  1. 1.The Hebrew University of JerusalemIsrael

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