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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.

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Paper provided by Max Planck Institute of Economics, Strategic Interaction Group in its series Discussion Papers on Strategic Interaction with number 2005-20.

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Length: 16 pages
Date of creation: Jul 2005
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Handle: RePEc:esi:discus:2005-20

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Related research
Keywords: Expected utility Mean variance preference functional pair wise choice experiments

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Find related papers by JEL classification:
C92 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Group Behavior
G12 - Financial Economics - - General Financial Markets - - - Asset Pricing

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  1. John Hey & Enrica Carbone, . "Which Error Theory is Best?," Discussion Papers 99/31, Department of Economics, University of York. [Downloadable!]
  2. 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 308-17, June.
  3. Carbone, Enrica, 1997. "Investigation of stochastic preference theory using experimental data," Economics Letters, Elsevier, vol. 57(3), pages 305-311, December. [Downloadable!] (restricted)
  4. Hey, John D & Orme, Chris, 1994. "Investigating Generalizations of Expected Utility Theory Using Experimental Data," Econometrica, Econometric Society, vol. 62(6), pages 1291-1326, November. [Downloadable!] (restricted)
  5. John Hey, 2001. "Does Repetition Improve Consistency?," Experimental Economics, Springer, vol. 4(1), pages 5-54, June. [Downloadable!] (restricted)
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  6. Holt, Charles A, 1986. "Preference Reversals and the Independence Axiom," American Economic Review, American Economic Association, vol. 76(3), pages 508-15, June. [Downloadable!] (restricted)
  7. Loomes, Graham & Moffatt, Peter G & Sugden, Robert, 2002. " A Microeconometric Test of Alternative Stochastic Theories of Risky Choice," Journal of Risk and Uncertainty, Springer, vol. 24(2), pages 103-30, March. [Downloadable!] (restricted)
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  8. Harless, David W & Camerer, Colin F, 1994. "The Predictive Utility of Generalized Expected Utility Theories," Econometrica, Econometric Society, vol. 62(6), pages 1251-89, November. [Downloadable!] (restricted)
  9. Hey, John D. & Carbone, Enrica, 1995. "Stochastic choice with deterministic preferences: An experimental investigation," Economics Letters, Elsevier, vol. 47(2), pages 161-167, February. [Downloadable!] (restricted)
  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. [Downloadable!] (restricted)
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