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Market Dynamics and Agents Behaviors: a Computational Approach

In: Artificial Economics

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  • Julien Derveeuw

    (Université des Sciences et Technologies de Lille)

Abstract

Summary We explore market dynamics generated by the Santa-Fe Artificial Stock Market model. It allows to study how agents adapt themselves to a market dynamic without knowing its generation process. It was shown by Arthur and LeBaron, with the help of computer experiments, that agents in bounded rationality can make a rational global behavior emerge in this context. In the original model, agents do not ground their decision on an economic logic. Hence, we modify indicators used by agents to watch the market to give them more economic rationality. This leads us to divide agents in two groups: fundamentalists agents, who watch the market with classic economic indicators and speculator agents, who watch the market with technical indicators. This split allows us to study the influence of individual agents behaviors on global price dynamics. In this article, we show with the help of computational simulations that these two types of agents can generate classical market dynamics as well as perturbed ones (bubbles and kraches).

Suggested Citation

  • Julien Derveeuw, 2006. "Market Dynamics and Agents Behaviors: a Computational Approach," Lecture Notes in Economics and Mathematical Systems, in: M. Beckmann & H. P. Künzi & G. Fandel & W. Trockel & A. Basile & A. Drexl & H. Dawid & K. Inderfurth (ed.), Artificial Economics, pages 15-26, Springer.
    • Handle: RePEc:spr:lnechp:978-3-540-28547-2_2
    DOI: 10.1007/3-540-28547-4_2
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    Cited by:

    1. Khaldoun Khashanah & Talal Alsulaiman, 2017. "Connectivity, Information Jumps, and Market Stability: An Agent-Based Approach," Complexity, Hindawi, vol. 2017, pages 1-16, August.

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