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Mean-Field Price Formation on Trees: with Multi-Population and Non-Rational Agents

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  • Masaaki Fujii

    (Graduate School of Economics, The University of Tokyo)

Abstract

This work solves the equilibrium price formation problem for the risky stock by combining mean-field game theory with the binomial tree framework, following the classic approach of Cox, Ross & Rubinstein. For agents with exponential and recursive utilities of exponential-type, we prove the existence of a unique mean-field market-clearing equilibrium and derive an explicit analytic formula for equilibrium transition probabilities of the stock price on the binomial lattice. The agents face stochastic terminal liabilities and incremental endowments that depend on unhedgeable common and idiosyncratic factors, in addition to the stock price path. We also incorporate an external order flow. Furthermore, the analytic tractability of the proposed approach allows us to extend the framework in two important directions: First, we incorporate multi-population heterogeneity, allowing agents to differ in functional forms for their liabilities, endowments, and risk coefficients. Second, we relax the rational expectations hypothesis by modeling agents operating under subjective probability measures which induce stochastically biased views on the stock transition probabilities. Our numerical examples illustrate the qualitative effects of these components on the equilibrium price distribution.

Suggested Citation

  • Masaaki Fujii, 2025. "Mean-Field Price Formation on Trees: with Multi-Population and Non-Rational Agents," CARF F-Series CARF-F-606, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Nov 2025.
  • Handle: RePEc:cfi:fseres:cf606
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    References listed on IDEAS

    as
    1. Masashi Sekine, 2024. "Mean field equilibrium asset pricing model under partial observation: An exponential quadratic Gaussian approach," Papers 2410.01352, arXiv.org, revised Apr 2025.
    2. Masaaki Fujii & Masashi Sekine, 2023. "Mean-field equilibrium price formation with exponential utility," CARF F-Series CARF-F-594, Center for Advanced Research in Finance, Faculty of Economics, The University of Tokyo, revised Jan 2025.
    3. René Aïd & Dylan Possamaï & Nizar Touzi, 2022. "Optimal Electricity Demand Response Contracting with Responsiveness Incentives," Mathematics of Operations Research, INFORMS, vol. 47(3), pages 2112-2137, August.
    4. René Aïd & Dylan Possamaï & Nizar Touzi, 2022. "Optimal Electricity Demand Response Contracting with Responsiveness Incentives," Post-Print hal-03670395, HAL.
    5. Ying Hu & Peter Imkeller & Matthias Muller, 2005. "Utility maximization in incomplete markets," Papers math/0508448, arXiv.org.
    6. Aïd, René & Bonesini, Ofelia & Callegaro, Giorgia & Campi, Luciano, 2025. "Continuous-time persuasion by filtering," Journal of Economic Dynamics and Control, Elsevier, vol. 176(C).
    7. Gianmarco Del Sarto & Marta Leocata & Giulia Livieri, 2024. "A Mean Field Game approach for pollution regulation of competitive firms," Papers 2407.12754, arXiv.org.
    8. Erhan Bayraktar & Indrajit Mitra & Jingjie Zhang, 2024. "Countercyclical unemployment benefits: a general equilibrium analysis of transition dynamics," Mathematics and Financial Economics, Springer, volume 18, number 3, December.
    9. Aïd, René & Bonesini, Ofelia & Callegaro, Giorgia & Campi, Luciano, 2025. "Continuous-time persuasion by filtering," LSE Research Online Documents on Economics 127889, London School of Economics and Political Science, LSE Library.
    10. Masaaki Fujii & Masashi Sekine, 2023. "Mean-field equilibrium price formation with exponential utility," Papers 2304.07108, arXiv.org, revised Jan 2025.
    11. Cox, John C. & Ross, Stephen A. & Rubinstein, Mark, 1979. "Option pricing: A simplified approach," Journal of Financial Economics, Elsevier, vol. 7(3), pages 229-263, September.
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