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Microscopic Spin Model For The Stock Market With Attractor Bubbling And Heterogeneous Agents

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  • A. KRAWIECKI

    (Faculty of Physics, and Center of Excellence for the Complex System Research, Warsaw University of Technology, Koszykowa 75, PL-00-662 Warsaw, Poland)

Abstract

A multi-agent spin model for changes of prices in the stock market is considered, based on the Ising-like cellular automaton with global, randomly varying in time interactions between traders. The presence of "fundamentalists" is taken into account by introducing additional term in the local field acting on each agent, dependent on the ratio between the actual stock price and its fundamental value. Numerical multi-agent as well as mean-field simulations show that for properly chosen parameters, the time series of logarithmic price returns exhibit bursting typical of volatility clustering, due to appearance of attractor bubbling in the model. Distributions of price returns show the power-law tails, and the corresponding cumulative distributions have regions of power scaling, with exponents comparable to those observed in empirical time series of stock price returns.

Suggested Citation

  • A. Krawiecki, 2005. "Microscopic Spin Model For The Stock Market With Attractor Bubbling And Heterogeneous Agents," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 16(04), pages 549-559.
    • Handle: RePEc:wsi:ijmpcx:v:16:y:2005:i:04:n:s0129183105007285
    DOI: 10.1142/S0129183105007285
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    References listed on IDEAS

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    1. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
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    Cited by:

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    2. B. Zhang & J. Wang & W. Zhang & G. C. Wang, 2020. "Nonlinear Scaling Behavior of Visible Volatility Duration for Financial Statistical Physics Dynamics," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 373-389, August.
    3. Wang, Jie & Wang, Jun, 2020. "Cross-correlation complexity and synchronization of the financial time series on Potts dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 541(C).
    4. Zhang, Bo & Wang, Guochao & Wang, Yiduan & Zhang, Wei & Wang, Jun, 2019. "Multiscale statistical behaviors for Ising financial dynamics with continuum percolation jump," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 525(C), pages 1012-1025.
    5. Wang, Tiansong & Wang, Jun & Zhang, Junhuan & Fang, Wen, 2011. "Voter interacting systems applied to Chinese stock markets," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 81(11), pages 2492-2506.
    6. Xiao, Di & Wang, Jun, 2021. "Attitude interaction for financial price behaviours by contact system with small-world network topology," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 572(C).
    7. Zhang, Yali & Wang, Jun, 2017. "Nonlinear complexity of random visibility graph and Lempel-Ziv on multitype range-intensity interacting financial dynamics," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 482(C), pages 741-756.
    8. Zheng, Zhiyong & Lu, Yunfan & Zhang, Junhuan, 2022. "Multiscale complexity fluctuation behaviours of stochastic interacting cryptocurrency price model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 593(C).
    9. Yue Chen & Xiaojian Niu & Yan Zhang, 2019. "Exploring Contrarian Degree in the Trading Behavior of China's Stock Market," Complexity, Hindawi, vol. 2019, pages 1-12, April.
    10. Wang, Guochao & Zheng, Shenzhou & Wang, Jun, 2019. "Complex and composite entropy fluctuation behaviors of statistical physics interacting financial model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 97-113.
    11. Zhang, Bo & Wang, Jun & Fang, Wen, 2015. "Volatility behavior of visibility graph EMD financial time series from Ising interacting system," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 432(C), pages 301-314.

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