Transmission of Information and Herd Behavior: an Application to Financial Markets

V. M. Eguíluz, M. G. Zimmermann
Instituto Mediterráneo de Estudios Avanzados (IMEDEA) CSIC-UIB, E-07071 Palma de Mallorca, Spain


We propose a model for stochastic formation of opinion clusters, modelled by an evolving network, and herd behaviour to account for the observed fat-tail distribution in returns of financial-price data. The only parameter of the model is h, the rate of information dispersion per trade, which is a measure of herding behavior. For h below a critical h* the system displays a power-law distribution of the returns with exponential cut-off. However for h > h* an increase in the probability of large returns is found, and may be associated to the occurrence of large crashes.

PACS: 87.23.Ge, 02.50.Le, 05.45.Tp, 05.65.+b

V.M. Eguíluz and M.G. Zimmermann, Phys. Rev. Lett. 85, 5659-5662 (2000).

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Citing Articles

  1. Non-universal scaling and dynamical feedback in generalized models of financial markets,
    D. Zheng et al, cond-mat/0108399.
  2. Transition from coherence to bistability in a model of financial markets,
    R. D'Hulst and G.J. Rodgers, Eur. Phys. J. B 20, 619 (2001)
  3. Non-universal scaling in a model of information transmission and herd behavior,
    D. Zheng et al, cond-mat/0105474.
  4. A simple model of price formation,
    K. Sznajd-Weron, R. Weron, cond-mat/0101001.
  5. On coordination and continuous hawk-dove games on small-world networks,
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  6. On the nature of the stock market: Simulations and experiments,
    Hendrik J. Blok, PhD thesis; [also in cond-mat/0010211].
  7. Model for correlations in stock markets,
    J.D. Noh, Phys. Rev. E 61, 5981-5982 (2000)
  8. Self-organized model for information spread in financial markets,
    Zhi-Feng Huang, Eur. Phys. J. B. 16, 379-385 (2000)
  9. Democracy versus dictatorship in self-organized models of financial markets,
    R. D'Hulst and G.J. Rodgers, Physica A 280, 554 (2000)
  10. Exact Solution of a Model for Crowding and Information Transmission in Financial Markets,
    R. D'Hulst, G. J. Rodgers, Int. J. Theor. and Appl. Finance 3, 609 (2000).

Press releases:
 

  • Physical Review Focus 6, 28 (2000) [22 December 2000]
    STOCK MARKET: FOLLOW THE LEADER, by David Ehrenstein
    To make money in the stock market, you have to understand risk.
    Physicists have been using statistical physics methods to analyze
    markets in order to better understand market risks, such as the
    probability that a large shift in market value will occur during a
    year-long interval. Real markets have a higher probability of
    experiencing large changes than conventional "pure chance" would
    predict, and econophysicists have suggested many schemes to explain
    this fact. The latest idea, reported in the 25 December PRL, points
    to the "herding behavior" for which traders are famous. The authors
    describe a simple computer model where information networks grow
    randomly until entire "clusters" of traders act on the news and then
    wait for the next "rumor mill" to grow. The model predicts price
    fluctuations similar to those of real markets.
    (V. M. Egu¡luz and M. G. Zimmermann, Phys. Rev. Lett. 85, 5659.
    COMPLETE Focus story at http://focus.aps.org/v6/st28.html
    Link to the paper: http://publish.aps.org/abstract/PRL/v85/p5659/)
  • Nature science update [4 January 2001]
    phenomena: Stockbrokers may act like sheep,  by Mark Haw.
    Herd mentality could be driving the fierce world of finance, a new
    mathematical model shows.
  • New Scientist [13 January 2001]
    Herd mentality

    Last update: Jan. 2001.