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Evolving dynamics of trading behavior based on coordination game in complex networks

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  • Bian, Yue-tang
  • Xu, Lu
  • Li, Jin-sheng

Abstract

This work concerns the modeling of evolvement of trading behavior in stock markets. Based on the assumption of the investors’ limited rationality, the evolution mechanism of trading behavior is modeled according to the investment strategy of coordination game in network, that investors are prone to imitate their neighbors’ activity through comprehensive analysis on the risk dominance degree of certain investment behavior, the network topology of their relationship and its heterogeneity. We investigate by mean-field analysis and extensive simulations the evolution of investors’ trading behavior in various typical networks under different risk dominance degree of investment behavior. Our results indicate that the evolution of investors’ behavior is affected by the network structure of stock market and the effect of risk dominance degree of investment behavior; the stability of equilibrium states of investors’ behavior dynamics is directly related with the risk dominance degree of some behavior; connectivity and heterogeneity of the network plays an important role in the evolution of the investment behavior in stock market.

Suggested Citation

  • Bian, Yue-tang & Xu, Lu & Li, Jin-sheng, 2016. "Evolving dynamics of trading behavior based on coordination game in complex networks," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 449(C), pages 281-290.
    • Handle: RePEc:eee:phsmap:v:449:y:2016:i:c:p:281-290
    DOI: 10.1016/j.physa.2015.12.113
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    References listed on IDEAS

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    Cited by:

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    2. Shen, Ai-Zhong & Guo, Jin-Li & Suo, Qi, 2017. "Study of the variable growth hypernetworks influence on the scaling law," Chaos, Solitons & Fractals, Elsevier, vol. 97(C), pages 84-89.
    3. Wang, Chengjin & Gao, Yudong & Li, Honggang, 2021. "Information interaction, behavioral synchronization and asset market volatility," The North American Journal of Economics and Finance, Elsevier, vol. 56(C).

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