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Multi-scaling in the Cont–Bouchaud microscopic stock market model

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  • Castiglione, Filippo
  • Stauffer, Dietrich

Abstract

The Cont–Bouchaud percolation model is one of the simplest microsimulation models yet able to account for the main stylized fact of financial markets, e.g. fat tails of the histogram of log-returns. In the present paper we show that for a certain range of the parameters it is possible to generate price time-series that cannot be described in terms of a unique scaling exponent.

Suggested Citation

  • Castiglione, Filippo & Stauffer, Dietrich, 2001. "Multi-scaling in the Cont–Bouchaud microscopic stock market model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 300(3), pages 531-538.
    • Handle: RePEc:eee:phsmap:v:300:y:2001:i:3:p:531-538
    DOI: 10.1016/S0378-4371(01)00365-X
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    References listed on IDEAS

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    1. R. Baviera & M. Pasquini & M. Serva & D. Vergni & A. Vulpiani, 1999. "Efficiency in foreign exchange markets," Papers cond-mat/9901225, arXiv.org.
    2. J-F. Muzy & D. Sornette & J. delour & A. Arneodo, 2001. "Multifractal returns and hierarchical portfolio theory," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 131-148.
    3. Stauffer, Dietrich & Sornette, Didier, 1999. "Self-organized percolation model for stock market fluctuations," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 271(3), pages 496-506.
    4. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    5. Cont, Rama & Bouchaud, Jean-Philipe, 2000. "Herd Behavior And Aggregate Fluctuations In Financial Markets," Macroeconomic Dynamics, Cambridge University Press, vol. 4(2), pages 170-196, June.
    6. Stauffer, D. & Jan, N., 2000. "Sharp peaks in the percolation model for stock markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 277(1), pages 215-219.
    7. Giulia Iori, 2000. "Scaling and Multi-scaling in Financial Markets," Papers cond-mat/0007385, arXiv.org.
    8. J. Rotyis & G. Vattay, 1997. "Statistical Analysis of the Stock Index of the Budapest Stock Exchange," Papers cond-mat/9711008, arXiv.org.
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    Citations

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    Cited by:

    1. Thomas Lux, 2009. "Applications of Statistical Physics in Finance and Economics," Chapters, in: J. Barkley Rosser Jr. (ed.), Handbook of Research on Complexity, chapter 9, Edward Elgar Publishing.
    2. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2007. "Agent-based Models of Financial Markets," Papers physics/0701140, arXiv.org.
    3. E. Samanidou & E. Zschischang & D. Stauffer & T. Lux, 2001. "Microscopic Models of Financial Markets," Papers cond-mat/0110354, arXiv.org.
    4. Makowiec, D. & Gnaciński, P. & Miklaszewski, W., 2004. "Amplified imitation in percolation model of stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 331(1), pages 269-278.

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