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Comparison of Mean-Variance Theory and Expected-Utility Theory through a Laboratory Experiment

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  • Andrea Morone

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Abstract

In the 40's and early 50' two decision theories were proposed and have since dominated the scene of the fascinating field of decision-making. In 1944 - when von Neumann and Morgenstern showed that if preferences are consistent with a set of axioms then it is possible to represent these preferences by the expectation of some utility function - Expected Utility theory provides a natural way to establish "measurable utility". In the early 50's Markowitz introduced the Mean-Variance theory that is the basis of modern portfolio selection theory. Even if both models were analyzed from virtually all possible points of view; although they were tested against several generalizations; even though they seem to be the most attractive theories of decision making, they were never tested against each other. This paper will try to fill this gap. It investigates, using experimental data, which of these two models represent a better approximation of subjects' preferences.

Suggested Citation

  • Andrea Morone, 2005. "Comparison of Mean-Variance Theory and Expected-Utility Theory through a Laboratory Experiment," Papers on Strategic Interaction 2005-20, Max Planck Institute of Economics, Strategic Interaction Group.
  • Handle: RePEc:esi:discus:2005-20
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    References listed on IDEAS

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    9. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-1289, November.
    10. Kroll, Yoram & Levy, Haim & Markowitz, Harry M, 1984. " Mean-Variance versus Direct Utility Maximization," Journal of Finance, American Finance Association, vol. 39(1), pages 47-61, March.
    11. Levy, H & Markowtiz, H M, 1979. "Approximating Expected Utility by a Function of Mean and Variance," American Economic Review, American Economic Association, vol. 69(3), pages 308-317, June.
    12. Carbone, Enrica, 1997. "Investigation of stochastic preference theory using experimental data," Economics Letters, Elsevier, vol. 57(3), pages 305-311, December.
    13. Hey, John D., 1995. "Experimental investigations of errors in decision making under risk," European Economic Review, Elsevier, vol. 39(3-4), pages 633-640, April.
    14. Holt, Charles A, 1986. "Preference Reversals and the Independence Axiom," American Economic Review, American Economic Association, vol. 76(3), pages 508-515, June.
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    Citations

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    Cited by:

    1. Morone, Andrea, 2010. "On price data elicitation: A laboratory investigation," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 39(5), pages 540-545, October.
    2. Andrea Morone & Ulrich Schmidt, 2008. "An Experimental Investigation of Alternatives to Expected Utility Using Pricing Data," Economics Bulletin, AccessEcon, vol. 4(20), pages 1-12.
    3. Andrea Morone & Piergiuseppe Morone, 2012. "Are small groups Expected Utility?," Working Papers 2012/08, Economics Department, Universitat Jaume I, Castellón (Spain).
    4. Morone, Andrea & Ozdemir, Ozlem, 2012. "Black swan protection: an experimental investigation," MPRA Paper 38842, University Library of Munich, Germany.
    5. Fatma Lajeri-Chaherli, 2016. "On The Concavity And Quasiconcavity Properties Of ( Σ , Μ ) Utility Functions," Bulletin of Economic Research, Wiley Blackwell, vol. 68(3), pages 287-296, April.
    6. Morone, Andrea & Temerario, Tiziana, 2015. "Eliciting Preferences Over Risk: An Experiment," MPRA Paper 68519, University Library of Munich, Germany.
    7. Zonna, Davide, 2016. "Sprechi di cibo e tentativi di riduzione. Un caso sperimentale
      [Avoiding food waste. A field experiment]
      ," MPRA Paper 76097, University Library of Munich, Germany.
    8. Temerario, Tiziana, 2014. "Individual and Group Behaviour Toward Risk: A Short Survey," MPRA Paper 58079, University Library of Munich, Germany.
    9. A. Morone & P. Morone, 2014. "Estimating individual and group preference functionals using experimental data," Theory and Decision, Springer, vol. 77(3), pages 403-422, October.

    More about this item

    Keywords

    Expected utility; Mean variance; preference functional; pair wise choice; experiments;

    JEL classification:

    • C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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