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Evolutionary model on market ecology of investors and investments

Author

Listed:
  • Gao, Ya-Chun
  • Cai, Shi-Min
  • Lü, Linyuan
  • Wang, Bing-Hong

Abstract

The interactions between investors and investments are of significant importance to understand the dynamics of financial markets. An evolutionary model is proposed to investigate the dynamic behaviors of investors and investments in a market ecology. The investors are divided into two groups, active ones and passive ones, distinguished by different selection capabilities based on the partial information, while the investments are simply categorized as good ones and bad ones. Without external influence, the system consisting of both investors and investments can self-organize to a quasi-stationary state according to their own strategies associating with the gains of market information. The model suggests that the partial information asymmetry of investors and various qualities of investments commonly give rise to a diverse dynamic behavior of the system by quantifying the fraction of active investors and of good investment at the quasi-stationary state.

Suggested Citation

  • Gao, Ya-Chun & Cai, Shi-Min & Lü, Linyuan & Wang, Bing-Hong, 2013. "Evolutionary model on market ecology of investors and investments," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(16), pages 3385-3391.
    • Handle: RePEc:eee:phsmap:v:392:y:2013:i:16:p:3385-3391
    DOI: 10.1016/j.physa.2013.04.007
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    Cited by:

    1. Zhu, Lirong & Chen, Jiawei & Di, Zengru & Chen, Liujun & Liu, Yan & Stanley, H. Eugene, 2017. "The mechanisms of labor division from the perspective of individual optimization," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 488(C), pages 112-120.
    2. de Oliveira, Viviane M. & Campos, Paulo R.A., 2019. "The emergence of division of labor in a structured response threshold model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 517(C), pages 153-162.
    3. Gao, Yang & Wang, Yaojun & Wang, Chao & Liu, Chao, 2018. "Internet attention and information asymmetry: Evidence from Qihoo 360 search data on the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 510(C), pages 802-811.
    4. Cai Gao & Xin Lan & Xiaoge Zhang & Yong Deng, 2013. "A Bio-Inspired Methodology of Identifying Influential Nodes in Complex Networks," PLOS ONE, Public Library of Science, vol. 8(6), pages 1-11, June.
    5. M. Fern'andez-Mart'inez & M. A S'anchez-Granero & Mar'ia Jos'e Mu~noz Torrecillas & Bill McKelvey, 2016. "A comparison among some Hurst exponent approaches to predict nascent bubbles in $500$ company stocks," Papers 1601.04188, arXiv.org.

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