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Opinion formation model for markets with a social temperature and fear

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  • Sebastian M. Krause
  • Stefan Bornholdt

Abstract

In the spirit of behavioral finance, we study the process of opinion formation among investors using a variant of the 2D Voter Model with a tunable social temperature. Further, a feedback acting on the temperature is introduced, such that social temperature reacts to market imbalances and thus becomes time dependent. In this toy market model, social temperature represents nervousness of agents towards market imbalances representing speculative risk. We use the knowledge about the discontinuous Generalized Voter Model phase transition to determine critical fixed points. The system exhibits metastable phases around these fixed points characterized by structured lattice states, with intermittent excursions away from the fixed points. The statistical mechanics of the model is characterized and its relation to dynamics of opinion formation among investors in real markets is discussed.

Suggested Citation

  • Sebastian M. Krause & Stefan Bornholdt, 2012. "Opinion formation model for markets with a social temperature and fear," Papers 1212.4751, arXiv.org.
    • Handle: RePEc:arx:papers:1212.4751
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    Cited by:

    1. Stefan Bornholdt, 2021. "A q-spin Potts model of markets: Gain-loss asymmetry in stock indices as an emergent phenomenon," Papers 2112.06290, arXiv.org.
    2. Kristoufek, Ladislav & Vošvrda, Miloslav S., 2016. "Herding, minority game, market clearing and efficient markets in a simple spin model framework," FinMaP-Working Papers 68, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    3. Christoph J. Borner & Ingo Hoffmann & John H. Stiebel, 2023. "On the Connection between Temperature and Volatility in Ideal Agent Systems," Papers 2303.15164, arXiv.org.
    4. Krause, Sebastian M. & Bornholdt, Stefan, 2013. "Spin models as microfoundation of macroscopic market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(18), pages 4048-4054.
    5. Quanbo Zha & Gang Kou & Hengjie Zhang & Haiming Liang & Xia Chen & Cong-Cong Li & Yucheng Dong, 2020. "Opinion dynamics in finance and business: a literature review and research opportunities," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 6(1), pages 1-22, December.
    6. Bornholdt, Stefan, 2022. "A q-spin Potts model of markets: Gain–loss asymmetry in stock indices as an emergent phenomenon," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 588(C).

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