Location of Repository

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

By Andrea Morone


In the 40's and early 50''s two decision theories were proposed and have dominated the scene of the fascinating field of decision-making. Since 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. Since then, both models were analyzed from virtually all possible points of view and were tested against several generalizations. However, these two models should be tested against each other. This paper tries to fill this gap, investigating (using experimental data) which of these two models better approximate subjects'' preferences.preference functional

OAI identifier:

Suggested articles



  1. (1994). The Predictive Utility of Generalized Expected Utility Theories,
  2. (1995). Experimental investigations of error in decision making under risk.”
  3. (2001). Does repetition improve consistency?”
  4. (1994). Investigating generalizations of expected utility theory using experimental data.”
  5. (1984). Mean Variance versus direct utility maximization.”
  6. (1979). Approximating expected utility by function of mean and variance.”
  7. (1952). Portfolio Selection,"
  8. (1964). Capital Asset Prices: A Theory of Market Equilibrium Under Conditions of Risk,"
  9. (1958). Liquidity Preferences as Behavior Towards Risk,"
  10. (1944). Theory of games and economic behavior,
  11. (1989). Likelihood Ratio Test for Model Selection and Non Nested Hypotheses”,

To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.