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Heat baths and computational agent-based models

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  • Clark, Andrew

Abstract

In this paper, we examine an agent-based model, and an equation-based model in the form of a mean field model. We show how the mean field model is a small, fast model that identifies the high level properties of a subject, in this case financial time series’ stylized facts. The agent based model generates the granularity needed to understand the conditions and factors that generate the stylized financial facts. We conclude with the recommendation that both models be used in sequence so a complete description of a process be established or approximated.

Suggested Citation

  • Clark, Andrew, 2012. "Heat baths and computational agent-based models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(22), pages 5512-5520.
  • Handle: RePEc:eee:phsmap:v:391:y:2012:i:22:p:5512-5520
    DOI: 10.1016/j.physa.2012.06.011
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    References listed on IDEAS

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    1. Brock, William A. & Hommes, Cars H., 1998. "Heterogeneous beliefs and routes to chaos in a simple asset pricing model," Journal of Economic Dynamics and Control, Elsevier, vol. 22(8-9), pages 1235-1274, August.
    2. Gaunersdorfer, A. & Hommes, C.H., 2000. "A Nonlinear Structural Model for Volatility Clustering," CeNDEF Working Papers 00-02, Universiteit van Amsterdam, Center for Nonlinear Dynamics in Economics and Finance.
    3. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    4. Chiarella, Carl & He, Xue-Zhong, 2002. "Heterogeneous Beliefs, Risk and Learning in a Simple Asset Pricing Model," Computational Economics, Springer;Society for Computational Economics, vol. 19(1), pages 95-132, February.
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