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Strategically biased learning in market interactions

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  • Giulio Bottazzi
  • Daniele Giachini

Abstract

We consider a market economy where two rational agents are able to learn the distribution of future events. In this context, we study whether moving away from the standard Bayesian belief updating, in the sense of under-reaction to some degree to new information, may be strategically convenient for traders. We show that, in equilibrium, strong under-reaction occurs, thus rational agents may strategically want to bias their learning process. Our analysis points out that the underlying mechanism driving ex-ante strategical decisions is diversity seeking. Finally, we show that, even if robust with respect to strategy selection, strong under-reaction can generate low realized welfare levels because of a long transient phase in which the agent makes poor predictions.

Suggested Citation

  • Giulio Bottazzi & Daniele Giachini, 2022. "Strategically biased learning in market interactions," LEM Papers Series 2022/02, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    • Handle: RePEc:ssa:lemwps:2022/02
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    References listed on IDEAS

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    1. Bottazzi, Giulio & Dindo, Pietro, 2014. "Evolution and market behavior with endogenous investment rules," Journal of Economic Dynamics and Control, Elsevier, vol. 48(C), pages 121-146.
    2. Barberis, Nicholas & Shleifer, Andrei & Vishny, Robert, 1998. "A model of investor sentiment," Journal of Financial Economics, Elsevier, vol. 49(3), pages 307-343, September.
    3. Elyès Jouini & Clotilde Napp, 2016. "Live fast, die young," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 62(1), pages 265-278, June.
    4. Dindo, Pietro & Massari, Filippo, 2020. "The wisdom of the crowd in dynamic economies," Theoretical Economics, Econometric Society, vol. 15(4), November.
    5. Epstein Larry G & Noor Jawwad & Sandroni Alvaro, 2010. "Non-Bayesian Learning," The B.E. Journal of Theoretical Economics, De Gruyter, vol. 10(1), pages 1-20, January.
    6. Filippo Massari, 2021. "Price probabilities: a class of Bayesian and non-Bayesian prediction rules," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 72(1), pages 133-166, July.
    7. Dindo, Pietro, 2019. "Survival in speculative markets," Journal of Economic Theory, Elsevier, vol. 181(C), pages 1-43.
    8. Giulio Bottazzi & Pietro Dindo & Daniele Giachini, 2019. "Momentum and reversal in financial markets with persistent heterogeneity," Annals of Finance, Springer, vol. 15(4), pages 455-487, December.
    9. Daniele Giachini, 2021. "Rationality and asset prices under belief heterogeneity," Journal of Evolutionary Economics, Springer, vol. 31(1), pages 207-233, January.
    10. Giulio Bottazzi & Pietro Dindo & Daniele Giachini, 2018. "Long-run heterogeneity in an exchange economy with fixed-mix traders," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 66(2), pages 407-447, August.
    11. Jiang, Hao & Li, Sophia Zhengzi & Wang, Hao, 2021. "Pervasive underreaction: Evidence from high-frequency data," Journal of Financial Economics, Elsevier, vol. 141(2), pages 573-599.
    12. Giulio Bottazzi & Pietro Dindo, 2013. "Selection in asset markets: the good, the bad, and the unknown," Journal of Evolutionary Economics, Springer, vol. 23(3), pages 641-661, July.
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    Cited by:

    1. Bottazzi, Giulio & Giachini, Daniele & Ottaviani, Matteo, 2023. "Market selection and learning under model misspecification," Journal of Economic Dynamics and Control, Elsevier, vol. 156(C).
    2. Andrea Antico & Giulio Bottazzi & Daniele Giachini, 2022. "On the evolutionary stability of the sentiment investor," LEM Papers Series 2022/09, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.

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    Keywords

    Learning; Strategic interaction; Behavioral Bias; Financial Markets.;
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