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Mean and variance responsive learning

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  • Oyarzun, Carlos
  • Sarin, Rajiv

Abstract

Decision makers are often described as seeking higher expected payoffs and avoiding higher variance in payoffs. We provide some necessary and some sufficient conditions for learning rules, that assume the agent has little prior and feedback information about the environment, to reflect such preferences. We adopt the framework of Börgers, Morales and Sarin (2004, Econometrica) who provide similar results for learning rules that seek higher expected payoffs. Our analysis reveals that a concern for variance leads to quadratic transformations of payoffs to appear in the learning rule.

Suggested Citation

  • Oyarzun, Carlos & Sarin, Rajiv, 2012. "Mean and variance responsive learning," Games and Economic Behavior, Elsevier, vol. 75(2), pages 855-866.
    • Handle: RePEc:eee:gamebe:v:75:y:2012:i:2:p:855-866
    DOI: 10.1016/j.geb.2012.02.013
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    References listed on IDEAS

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    1. Fudenberg, Drew & Levine, David, 1998. "Learning in games," European Economic Review, Elsevier, vol. 42(3-5), pages 631-639, May.
    2. Tilman Börgers & Antonio J. Morales & Rajiv Sarin, 2004. "Expedient and Monotone Learning Rules," Econometrica, Econometric Society, vol. 72(2), pages 383-405, March.
    3. Fabio Maccheroni & Massimo Marinacci & Aldo Rustichini & Marco Taboga, 2009. "Portfolio Selection With Monotone Mean‐Variance Preferences," Mathematical Finance, Wiley Blackwell, vol. 19(3), pages 487-521, July.
    4. Haruvy, Ernan & Erev, Ido & Sonsino, Doron, 2001. "The Medium Prizes Paradox: Evidence from a Simulated Casino," Journal of Risk and Uncertainty, Springer, vol. 22(3), pages 251-261, May.
    5. Karni, Edi & Schmeidler, David, 1986. "Self-preservation as a foundation of rational behavior under risk," Journal of Economic Behavior & Organization, Elsevier, vol. 7(1), pages 71-81, March.
    6. Albert Burgos, 2002. "Learning to deal with risk: what does reinforcement learning tell us about risk attitudes?," Economics Bulletin, AccessEcon, vol. 4(10), pages 1-13.
    7. Roth, Alvin E. & Erev, Ido, 1995. "Learning in extensive-form games: Experimental data and simple dynamic models in the intermediate term," Games and Economic Behavior, Elsevier, vol. 8(1), pages 164-212.
    8. Colin Camerer & Teck-Hua Ho, 1999. "Experience-weighted Attraction Learning in Normal Form Games," Econometrica, Econometric Society, vol. 67(4), pages 827-874, July.
    9. Robson, Arthur J., 1996. "A Biological Basis for Expected and Non-expected Utility," Journal of Economic Theory, Elsevier, vol. 68(2), pages 397-424, February.
    10. Jerker Denrell & James G. March, 2001. "Adaptation as Information Restriction: The Hot Stove Effect," Organization Science, INFORMS, vol. 12(5), pages 523-538, October.
    11. Drew Fudenberg & David K. Levine, 1998. "The Theory of Learning in Games," MIT Press Books, The MIT Press, edition 1, volume 1, number 0262061945, April.
    12. Faruk Gul & Wolfgang Pesendorfer, 2006. "Random Expected Utility," Econometrica, Econometric Society, vol. 74(1), pages 121-146, January.
    13. Harry Markowitz, 1952. "Portfolio Selection," Journal of Finance, American Finance Association, vol. 7(1), pages 77-91, March.
    14. Meyer, Jack, 1987. "Two-moment Decision Models and Expected Utility Maximization," American Economic Review, American Economic Association, vol. 77(3), pages 421-430, June.
    15. repec:ebl:ecbull:v:4:y:2002:i:10:p:1-13 is not listed on IDEAS
    16. Erev, Ido & Bereby-Meyer, Yoella & Roth, Alvin E., 1999. "The effect of adding a constant to all payoffs: experimental investigation, and implications for reinforcement learning models," Journal of Economic Behavior & Organization, Elsevier, vol. 39(1), pages 111-128, May.
    17. John G. Cross, 1973. "A Stochastic Learning Model of Economic Behavior," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 87(2), pages 239-266.
    18. DellaVigna, Stefano & LiCalzi, Marco, 2001. "Learning to make risk neutral choices in a symmetric world," Mathematical Social Sciences, Elsevier, vol. 41(1), pages 19-37, January.
    19. Sarin, Rajiv & Vahid, Farshid, 1999. "Payoff Assessments without Probabilities: A Simple Dynamic Model of Choice," Games and Economic Behavior, Elsevier, vol. 28(2), pages 294-309, August.
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    Cited by:

    1. Oyarzun, Carlos & Sanjurjo, Adam & Nguyen, Hien, 2017. "Response functions," European Economic Review, Elsevier, vol. 98(C), pages 1-31.

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    More about this item

    Keywords

    Learning; Reinforcement learning; Mean and variance preferences;
    All these keywords.

    JEL classification:

    • D81 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Criteria for Decision-Making under Risk and Uncertainty
    • D83 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Search; Learning; Information and Knowledge; Communication; Belief; Unawareness

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