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Computational modeling of collective human behavior: Example of financial markets

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  • Andy Kirou
  • Blazej Ruszczycki
  • Markus Walser
  • Neil F. Johnson

Abstract

We discuss how minimal financial market models can be constructed by bridging the gap between two existing, but incomplete, market models: a model in which a population of virtual traders make decisions based on common global information but lack local information from their social network, and a model in which the traders form a dynamically evolving social network but lack any decision-making based on global information. We show that a suitable combination of these two models -- in particular, a population of virtual traders with access to both global and local information -- produces results for the price return distribution which are closer to the reported stylized facts. We believe that this type of model can be applied across a wide range of systems in which collective human activity is observed.

Suggested Citation

  • Andy Kirou & Blazej Ruszczycki & Markus Walser & Neil F. Johnson, 2008. "Computational modeling of collective human behavior: Example of financial markets," Papers 0812.2603, arXiv.org.
    • Handle: RePEc:arx:papers:0812.2603
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    File URL: http://arxiv.org/pdf/0812.2603
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    Cited by:

    1. Matthew Oldham, 2019. "Understanding How Short-Termism and a Dynamic Investor Network Affects Investor Returns: An Agent-Based Perspective," Complexity, Hindawi, vol. 2019, pages 1-21, July.

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