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Price drops, fluctuations, and correlation in a multi-agent model of stock markets

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  • Zawadowski, A.G
  • Karádi, R
  • Kertész, J

Abstract

In this paper, we compare market price fluctuations with the response to fundamental price drops within the Lux–Marchesi model which is able to reproduce the most important stylized facts of real market data. Major differences can be observed between the decay of spontaneous fluctuations and changes due to external perturbations reflecting the absence of detailed balance, i.e., of the validity of the fluctuation–dissipation theorem. We found that fundamental price drops are followed by an overshoot with a rather robust characteristic time.

Suggested Citation

  • Zawadowski, A.G & Karádi, R & Kertész, J, 2002. "Price drops, fluctuations, and correlation in a multi-agent model of stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 316(1), pages 403-412.
    • Handle: RePEc:eee:phsmap:v:316:y:2002:i:1:p:403-412
    DOI: 10.1016/S0378-4371(02)01213-X
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    References listed on IDEAS

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    1. J. Doyne Farmer, 2000. "Physicists Attempt To Scale The Ivory Towers Of Finance," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(03), pages 311-333.
    2. Yanhui Liu & Parameswaran Gopikrishnan & Pierre Cizeau & Martin Meyer & Chung-Kang Peng & H. Eugene Stanley, 1999. "The statistical properties of the volatility of price fluctuations," Papers cond-mat/9903369, arXiv.org, revised Mar 1999.
    3. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    4. Challet, D. & Zhang, Y.-C., 1997. "Emergence of cooperation and organization in an evolutionary game," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 246(3), pages 407-418.
    5. Egenter, E. & Lux, T. & Stauffer, D., 1999. "Finite-size effects in Monte Carlo simulations of two stock market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 268(1), pages 250-256.
    6. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
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    Cited by:

    1. Xiaoguang Gong & Renbin Xiao, 2007. "Research on Multi-Agent Simulation of Epidemic News Spread Characteristics," Journal of Artificial Societies and Social Simulation, Journal of Artificial Societies and Social Simulation, vol. 10(3), pages 1-1.
    2. Eisler, Z. & Kertész, J., 2004. "Multifractal model of asset returns with leverage effect," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 343(C), pages 603-622.
    3. Adam Zawadowski & Gyorgy Andor & Janos Kertesz, 2006. "Short-term market reaction after extreme price changes of liquid stocks," Quantitative Finance, Taylor & Francis Journals, vol. 6(4), pages 283-295.

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