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Percolation Models Of Financial Market Dynamics

Author

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  • DIETRICH STAUFFER

    (Institute for Theoretical Physics, Cologne University, 50923 Köln, Germany)

Abstract

Microscopic models dealing with the decisions of traders on the market have tried to reproduce real market behaviour. Possibly the simplest of these models is the herding approach of Cont and Bouchaud. Variations include letting the concentration varying between zero and unity (or zero and percolation threshold); changing the price proportionally not to the difference between demand and supply, but to the square root of this difference; influencing the buy/sell decisions by the actual price and price change. As a result, the probability to find a market change greater than someRwas found to vary asR-2.9; this distribution gets wings which might correspond to outliers like the 1929 crash on Wall Street; bubbles lead to sharp peaks separated by flat valleys; and the log-periodic variations after the Japanese crash of 1990 were reproduced to get rich from the prediction made in January 1999 by Johansen and Sornette that Nikkei will rise appreciably during 1999. As it did.

Suggested Citation

  • Dietrich Stauffer, 2001. "Percolation Models Of Financial Market Dynamics," Advances in Complex Systems (ACS), World Scientific Publishing Co. Pte. Ltd., vol. 4(01), pages 19-27.
    • Handle: RePEc:wsi:acsxxx:v:04:y:2001:i:01:n:s0219525901000061
    DOI: 10.1142/S0219525901000061
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    Citations

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    Cited by:

    1. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    2. Alexander Smirnov, 2016. "A Simple Model of Credit Expansion," Papers 1609.05055, arXiv.org.
    3. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    4. Gudrun Ehrenstein, 2002. "Cont-Bouchaud percolation model including Tobin tax," Papers cond-mat/0205320, arXiv.org.
    5. Iwao Maeda & David deGraw & Michiharu Kitano & Hiroyasu Matsushima & Hiroki Sakaji & Kiyoshi Izumi & Atsuo Kato, 2020. "Deep Reinforcement Learning in Agent Based Financial Market Simulation," JRFM, MDPI, vol. 13(4), pages 1-17, April.
    6. Marcel Ausloos, 2014. "A biased view of a few possible components when reflecting on the present decade financial and economic crisis," Papers 1412.0127, arXiv.org.

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