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μ – σ Games

Author

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  • Uwe Dulleck

    (Centre for Behavioural Economics, Society and Technology (BEST), Queensland University of Technology, Brisbane, QLD 4000, Australia
    Crawford School of Public Policy, Australian National University, Canberra, ACT 4000, Australia
    These authors contributed equally to this work. The authors would like to thank Adam Clements for comments and feedback.)

  • Andreas Löffler

    (Freie Universität Berlin, 14195 Berlin, Germany
    These authors contributed equally to this work. The authors would like to thank Adam Clements for comments and feedback.)

Abstract

Risk aversion in game theory is usually modeled using expected utility, which was criticized early on, leading to an extensive literature on generalized expected utility. In this paper we are the first to apply μ – σ theory to the analysis of (static) games. μ – σ theory is widely accepted in the finance literature; using it allows us to study the effect on uncertainty endogenous to the game, i.e., mixed equilibria. In particular, we look at the case of linear μ – σ utility functions and determine the best response strategy. In the case of 2 × 2 and N × M games, we are able to characterize all mixed equilibria.

Suggested Citation

  • Uwe Dulleck & Andreas Löffler, 2021. "μ – σ Games," Games, MDPI, vol. 12(1), pages 1-12, January.
    • Handle: RePEc:gam:jgames:v:12:y:2021:i:1:p:5-:d:478873
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    References listed on IDEAS

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    More about this item

    Keywords

    μ – σ utility; game theory; mixed strategies; equilibrium;
    All these keywords.

    JEL classification:

    • C - Mathematical and Quantitative Methods
    • C7 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory
    • C70 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - General
    • C71 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Cooperative Games
    • C72 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Noncooperative Games
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games

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