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Learning About Unstable, Publicly Unobservable Payoffs

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  • Elise Payzan-LeNestour
  • Peter Bossaerts

Abstract

Neoclassical finance assumes that investors are Bayesian. In many realistic situations, Bayesian learning is challenging. Here, we consider investment opportunities that change randomly, while payoffs are observable only when invested. In a stylized version of the task, we wondered whether performance would be affected if one were to follow reinforcement learning principles instead. The answer is a definite yes. When asked to perform our task, participants overwhelmingly learned in a Bayesian way. They stopped being Bayesians, though, when not nudged into paying attention to contingency shifts. This raises an issue for financial markets: who has the incentive to nudge investors?

Suggested Citation

  • Elise Payzan-LeNestour & Peter Bossaerts, 2015. "Learning About Unstable, Publicly Unobservable Payoffs," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 1874-1913.
  • Handle: RePEc:oup:rfinst:v:28:y:2015:i:7:p:1874-1913.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhu069
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    Citations

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    Cited by:

    1. Brice Corgnet & Mark Desantis & David Porter, 2018. "What Makes a Good Trader? On the Role of Intuition and Reflection on Trader Performance," Journal of Finance, American Finance Association, vol. 73(3), pages 1113-1137, June.
    2. He, Xue-Zhong & Lin, Shen, 2022. "Reinforcement Learning Equilibrium in Limit Order Markets," Journal of Economic Dynamics and Control, Elsevier, vol. 144(C).
    3. Kuhnen, Camelia M. & Miu, Andrei C., 2017. "Socioeconomic status and learning from financial information," Journal of Financial Economics, Elsevier, vol. 124(2), pages 349-372.
    4. Cynthia Weiyi Cai, 2020. "Nudging the financial market? A review of the nudge theory," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 60(4), pages 3341-3365, December.
    5. Daniela Di Cagno & Werner Güth & Noemi Pace, 2021. "Experimental evidence of behavioral improvement by learning and intermediate advice," Theory and Decision, Springer, vol. 91(2), pages 173-187, September.
    6. Mauersberger, Felix, 2019. "Thompson Sampling: Endogenously Random Behavior in Games and Markets," VfS Annual Conference 2019 (Leipzig): 30 Years after the Fall of the Berlin Wall - Democracy and Market Economy 203600, Verein für Socialpolitik / German Economic Association.

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