Heat baths and computational agent-based models

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 gen...

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Bibliographic Details
Published inPhysica A Vol. 391; no. 22; pp. 5512 - 5520
Main Author Clark, Andrew
Format Journal Article
LanguageEnglish
Published Elsevier B.V 15.11.2012
Subjects
Agent based models
Approximation
Bifurcations
Computation
Mathematical models
Mean field models
Power laws
Statistical mechanics
Time series
Volatility
Mean field models
Bifurcations
Power laws
Agent based models
Volatility
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Summary: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. ► This paper reviews mean field and computational agent financial markets modeling. ► Mean field models–small and fast but do not provide factors or context. ► Agent-based models provide factors and context. ► We recommend the use of both models to understand financial markets.
Bibliography:ObjectType-Article-2
SourceType-Scholarly Journals-1
ObjectType-Feature-1
content type line 23
ISSN:0378-4371
1873-2119
DOI:10.1016/j.physa.2012.06.011