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μ-σ Games

Author

Listed:
  • Uwe Dulleck

    (QUT)

  • Andreas Loffler

Abstract

Risk aversion in game theory is usually modelled using expected utility, which has been critized early on leading to an extensive literature on generalized expected utility. In this paper we are 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 2x2- and NxM-games we are able to characterize all mixed equilibria.

Suggested Citation

  • Uwe Dulleck & Andreas Loffler, 2012. "μ-σ Games," NCER Working Paper Series 78, National Centre for Econometric Research.
    • Handle: RePEc:qut:auncer:2012_1
    as

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    File URL: http://www.ncer.edu.au/papers/documents/WP78.pdf
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    Other versions of this item:

    • Uwe Dulleck & Andreas Löffler, 2021. "μ – σ Games," Games, MDPI, vol. 12(1), pages 1-12, January.

    References listed on IDEAS

    as
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    More about this item

    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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