Starting with the self-organized evolution of the trader group’s structure, a parsimonious percolation model for stock market is established, which can be considered as a kind of betterment of the Cont-Bouchaud model. The return distribution of the present model obeys Lévy form in the center and displays fat-tail property, in accord with the stylized facts observed in real-life financial time series. Furthermore, this model reveals the power-law relationship between the peak value of the probability distribution and the time scales, in agreement with the empirical studies on the Hang Seng Index.
This is a preview of subscription content, log in to check access.
Buy single article
Instant access to the full article PDF.
Price includes VAT for USA
Gopikrishnan, P., Plerou, V., Amaral, L. A. N. et al., Scaling of the distribution of fluctuations of financial market indices, Phys. Rev. E, 1999, 60: 5305–5316.
Mantegna, R. N., Stanley, H. E., Scaling behaviour in the dynamics of an economic index, Nature, 1995, 376: 46–49.
Galluccio, S., Caldarelli, G., Marsili, M. et al., Scaling in currency exchange, Physica A, 1997, 245: 423–436.
Liu, Y., Cizeau, P., Meyer, M. et al., Correlations in economic time series, Physica A, 1997, 245: 437–440.
Wang, B. H., Hui, P. M., The distribution and scaling of fluctuations for Hang Seng index in Hong Kong stock market, Eur. Phys. J. B, 2001, 20: 573–579.
Cont, R., Bouchaud, J. P., Herd behavior and aggregate fluctuations in financial markets, Marcroeconomic Dynamics, 2000, 4: 170–196.
Lux, T., Marchesi, M., Volatility clustering in financial markets, Int. J. Theo. Appl. Finance, 2000, 3: 675–702.
LeBaron, B., Evolution and time horizons in an agent-based stock market, Macroeconomic Dynamics, 2001, 5: 225–254.
Zhou, P. L., Yang, C. X., Zhou, T. et al., Avalanche dynamics of the financial market, New Mathematics and Natural Computation, 2005, 1: 275–283.
Wang, J., Yang, C. X., Zhou, P. L. et al., Evolutionary percolation model of stock market with variable agent number, Physica A, 2005, 354: 505–517.
Yang, C. X., Zhou, T., Zhou, P. L. et al., Evolvement complexity in an artificial stock market, Chin. Phys. Lett., 2005, 22: 1014–1017.
Zhou, T., Zhou, P. L., Wang, B. H. et al., Modeling stock market based on genetic cellular automata, Int. J. Mod. Phys. B, 2004, 18: 2697–2702.
Stauffer, D., Minireview: New results for old percolation, Physica A, 1997, 242: 1–7.
Grimmett, G. R., Percolation, Berlin: Springer-Verlag, 1989.
Stauffer, D., Aharony, A., Introduction to Percolation Theory, London: Taylor & Francis, 1994.
Stauffer, D., Sornette, D., Self-organized percolation model for stock market fluctuations, Physica A, 1999, 271: 496–506.
Rohatgi, V. K., An Introduction to Probability Theory and Mathematical Statistics, New York: John Wiley & Sons, 1976.
Makowiec, D., Gnaciński, P., Miklaszewski, W., Amplified imitation in percolation model of stock market, Physica A, 2004, 331: 269–278.
Castiglione, F., Stauffer, D., Multi-scaling in the Cont-Bouchaud microscopic stock market model, Physica A, 2001, 300: 531–538.
Stauffer, D., Jan, N., Sharp peaks in the percolation model for stock markets, Physica A, 2000, 277: 215–219.
Kaheman, D., Tversky, A., Prospect theory: an analysis of decision under risk, Econometrica, 1979, 47: 263–291.
Farmer, J. D., Market force, ecology and evolution, Industrial and Corporate Change, 2002, 11: 895–953.
Cavalcante, F. S. A., Moreira, A. A., Costa, U. M. S. et al., Self-organized percolation growth in regular and disordered lattices, Physica A, 2002, 311: 313–319.
About this article
Cite this article
Yang, C., Wang, J., Zhou, T. et al. Financial market model based on self-organized percolation. Chin.Sci.Bull. 50, 2140–2144 (2005). https://doi.org/10.1007/BF03182660
- Lévy distribution
- financial market model