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Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model

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Listed:
  • V. Alfi
  • M. Cristelli
  • L. Pietronero
  • A. Zaccaria
Abstract
We present a detailed analysis of the self-organization phenomenon in which the stylized facts originate from finite size effects with respect to the number of agents considered and disappear in the limit of an infinite population. By introducing the possibility that agents can enter or leave the market depending on the behavior of the price, it is possible to show that the system self-organizes in a regime with a finite number of agents which corresponds to the stylized facts. The mechanism to enter or leave the market is based on the idea that a too stable market is unappealing for traders while the presence of price movements attracts agents to enter and speculate on the market. We show that this mechanism is also compatible with the idea that agents are scared by a noisy and risky market at shorter time scales. We also show that the mechanism for self-organization is robust with respect to variations of the exit/entry rules and that the attempt to trigger the system to self-organize in a region without stylized facts leads to an unrealistic dynamics. We study the self-organization in a specific agent based model but we believe that the basic ideas should be of general validity.

Suggested Citation

  • V. Alfi & M. Cristelli & L. Pietronero & A. Zaccaria, 2008. "Mechanisms of Self-Organization and Finite Size Effects in a Minimal Agent Based Model," Papers 0811.4256, arXiv.org.
    • Handle: RePEc:arx:papers:0811.4256
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    References listed on IDEAS

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    1. Alfarano, Simone & Lux, Thomas, 2007. "A Noise Trader Model As A Generator Of Apparent Financial Power Laws And Long Memory," Macroeconomic Dynamics, Cambridge University Press, vol. 11(S1), pages 80-101, November.
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    Cited by:

    1. Blaurock, Ivonne & Schmitt, Noemi & Westerhoff, Frank, 2018. "Market entry waves and volatility outbursts in stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 153(C), pages 19-37.
    2. Federico Garzarelli & Matthieu Cristelli & Andrea Zaccaria & Luciano Pietronero, 2011. "Memory effects in stock price dynamics: evidences of technical trading," Papers 1110.5197, arXiv.org.
    3. Monira Essa Aloud, 2016. "Profitability of Directional Change Based Trading Strategies: The Case of Saudi Stock Market," International Journal of Economics and Financial Issues, Econjournals, vol. 6(1), pages 87-95.

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