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Learning and risk aversion

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  • Oyarzun, Carlos
  • Sarin, Rajiv
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    Abstract

    We study how learning shapes behavior towards risk when individuals are not assumed to know, or to have beliefs about, probability distributions. In any period, the behavior change induced by learning is assumed to depend on the action chosen and the payoff obtained. We characterize learning processes that, in expected value, increase the probability of choosing the safest actions and provide sufficient conditions for them to converge to the choices of risk averse expected utility maximizers. We provide a learning theoretic motivation for long run risk choices, such as those in expected utility theory with known payoff distributions.

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    File URL: http://www.sciencedirect.com/science/article/pii/S0022053112001044
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    Bibliographic Info

    Article provided by Elsevier in its journal Journal of Economic Theory.

    Volume (Year): 148 (2013)
    Issue (Month): 1 ()
    Pages: 196-225

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    Handle: RePEc:eee:jetheo:v:148:y:2013:i:1:p:196-225

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    Web page: http://www.elsevier.com/locate/inca/622869

    Related research

    Keywords: Reinforcement learning; Risk aversion; Expected utility;

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    References

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    8. Tilman Borgers & Antonio Morales & Rajiv Sarin, 2010. "Expedient and Monotone Learning Rules," Levine's Working Paper Archive 625018000000000099, David K. Levine.
    9. Izquierdo, Luis R. & Izquierdo, Segismundo S. & Gotts, Nicholas M. & Polhill, J. Gary, 2007. "Transient and asymptotic dynamics of reinforcement learning in games," Games and Economic Behavior, Elsevier, vol. 61(2), pages 259-276, November.
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    17. repec:ebl:ecbull:v:4:y:2002:i:10:p:1-13 is not listed on IDEAS
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