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Almost marginal conditional stochastic dominance

Author

Listed:
  • Denuit, Michel M.
  • Huang, Rachel J.
  • Tzeng, Larry Y.
  • Wang, Christine W.

Abstract

Marginal Conditional Stochastic Dominance (MCSD) developed by Shalit and Yitzhaki (1994) gives the conditions under which all risk-averse individuals prefer to increase the share of one risky asset over another in a given portfolio. In this paper, we extend this concept to provide conditions under which most (and not all) risk-averse investors behave in this way. Instead of stochastic dominance rules, almost stochastic dominance is used to assess the superiority of one asset over another in a given portfolio. Switching from MCSD to Almost MCSD (AMCSD) helps to reconcile common practices in asset allocation and the decision rules supporting stochastic dominance relations. A financial application is further provided to demonstrate that using AMCSD can indeed improve investment efficiency.

Suggested Citation

  • Denuit, Michel M. & Huang, Rachel J. & Tzeng, Larry Y. & Wang, Christine W., 2014. "Almost marginal conditional stochastic dominance," Journal of Banking & Finance, Elsevier, vol. 41(C), pages 57-66.
  • Handle: RePEc:eee:jbfina:v:41:y:2014:i:c:p:57-66
    DOI: 10.1016/j.jbankfin.2013.12.014
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    References listed on IDEAS

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    1. Haim Shalit & Shlomo Yitzhaki, 2003. "An Asset Allocation Puzzle: Comment," American Economic Review, American Economic Association, vol. 93(3), pages 1002-1008, June.
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    3. Haim Shalit & Shlomo Yitzhaki, 2010. "How does beta explain stochastic dominance efficiency?," Review of Quantitative Finance and Accounting, Springer, vol. 35(4), pages 431-444, November.
    4. Ephraim Clark & Konstantinos Kassimatis, 2013. "International equity flows, marginal conditional stochastic dominance and diversification," Review of Quantitative Finance and Accounting, Springer, vol. 40(2), pages 251-271, February.
    5. Louis Eeckhoudt & Harris Schlesinger, 2006. "Putting Risk in Its Proper Place," American Economic Review, American Economic Association, vol. 96(1), pages 280-289, March.
    6. 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.
    7. Chow, K Victor, 2001. "Marginal Conditional Stochastic Dominance, Statistical Inference, and Measuring Portfolio Performance," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 24(2), pages 289-307, Summer.
    8. Schechtman, Edna & Shelef, Amit & Yitzhaki, Shlomo & Zitikis, Ričardas, 2008. "Testing Hypotheses About Absolute Concentration Curves And Marginal Conditional Stochastic Dominance," Econometric Theory, Cambridge University Press, vol. 24(04), pages 1044-1062, August.
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    10. Moshe Leshno & Haim Levy, 2002. "Preferred by "All" and Preferred by "Most" Decision Makers: Almost Stochastic Dominance," Management Science, INFORMS, vol. 48(8), pages 1074-1085, August.
    11. Clark, Ephraim & Kassimatis, Konstantinos, 2012. "An empirical analysis of marginal conditional stochastic dominance," Journal of Banking & Finance, Elsevier, vol. 36(4), pages 1144-1151.
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    Citations

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    Cited by:

    1. Gleb Gersman & Haim Shalit, 2014. "Optimizing MCSD Portfolios," Working Papers 1410, Ben-Gurion University of the Negev, Department of Economics.
    2. Bruni, Renato & Cesarone, Francesco & Scozzari, Andrea & Tardella, Fabio, 2017. "On exact and approximate stochastic dominance strategies for portfolio selection," European Journal of Operational Research, Elsevier, vol. 259(1), pages 322-329.

    More about this item

    Keywords

    Marginal conditional stochastic dominance; Almost stochastic dominance; Asset allocation; Optimal investment;

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty

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