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Voter interacting systems applied to Chinese stock markets

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  • Wang, Tiansong
  • Wang, Jun
  • Zhang, Junhuan
  • Fang, Wen

Abstract

Applying the theory of statistical physics systems – the voter model, a random stock price model is modeled and studied in this paper, where the voter model is a continuous time Markov process. In this price model, for the different parameters values of the intensity λ, the lattice dimension d, the initial density θ, and the multivariate set (θ, λ), we discuss and analyze the statistical behaviors of the price model. Moreover, we investigate the power-law distributions, the long-term memory of returns and the volatility clustering phenomena for the Chinese stock indices. The database is from the indices of Shanghai and Shenzhen in the 6-year period from July 2002 to June 2008. Further, the comparisons of the empirical research and the simulation data are given.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:matcom:v:81:y:2011:i:11:p:2492-2506
    DOI: 10.1016/j.matcom.2011.03.013
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    1. V. Plerou & P. Gopikrishnan & L. A. N. Amaral & M. Meyer & H. E. Stanley, 1999. "Scaling of the distribution of price fluctuations of individual companies," Papers cond-mat/9907161, arXiv.org.
    2. Kirill Ilinski, 1997. "Physics of Finance," Papers hep-th/9710148, arXiv.org.
    3. Lo, Andrew W, 1991. "Long-Term Memory in Stock Market Prices," Econometrica, Econometric Society, vol. 59(5), pages 1279-1313, September.
    4. Pilar Grau-Carles, 2005. "Tests of Long Memory: A Bootstrap Approach," Computational Economics, Springer;Society for Computational Economics, vol. 25(1), pages 103-113, February.
    5. Ferreira, Nuno B. & Menezes, Rui & Mendes, Diana A., 2007. "Asymmetric conditional volatility in international stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 382(1), pages 73-80.
    6. Black, Fischer & Scholes, Myron S, 1973. "The Pricing of Options and Corporate Liabilities," Journal of Political Economy, University of Chicago Press, vol. 81(3), pages 637-654, May-June.
    7. 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.
    8. Maekawa, Koichi & Lee, Sangyeol & Morimoto, Takayuki & Kawai, Ken-ichi, 2008. "Jump diffusion model with application to the Japanese stock market," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 78(2), pages 223-236.
    9. Xavier Gabaix & Parameswaran Gopikrishnan & Vasiliki Plerou & H. Eugene Stanley, 2003. "A theory of power-law distributions in financial market fluctuations," Nature, Nature, vol. 423(6937), pages 267-270, May.
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    Cited by:

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    9. Korotin, Vladimir & Dolgonosov, Maxim & Popov, Victor & Korotina, Olesya & Korolkova, Inna, 2019. "The Ukrainian crisis, economic sanctions, oil shock and commodity currency: Analysis based on EMD approach," Research in International Business and Finance, Elsevier, vol. 48(C), pages 156-168.

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