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Towards evolutionary game models of financial markets

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  • D. Friedman

Abstract

Evolutionary game models analyse strategic interaction over time; equilibrium emerges (or fails to emerge) as players/traders adjust their actions in response to the payoffs they earn. This paper sketches some early and some recent evolutionary game models that contain ideas useful in modelling financial markets. It spotlights recent work on adaptive landscapes. In an extended example, the distribution of player/trader behaviour obeys a variant of Burgers' partial differential equation, and solutions involve travelling shock waves. It is conjectured that financial market crashes might insightfully be modelled in a similar fashion.

Suggested Citation

  • D. Friedman, 2001. "Towards evolutionary game models of financial markets," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 177-185.
    • Handle: RePEc:taf:quantf:v:1:y:2001:i:1:p:177-185
    DOI: 10.1080/713665544
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    Cited by:

    1. Jinbo Pang & Lingfei Deng & Gangyi Wang, 2017. "An evolutionarily stable strategy and the critical point of hog futures trading entities based on replicator dynamic theory: 2006–2015 data for China’s 22 provinces," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-18, February.
    2. Faggini, Marisa & Parziale, Anna, 2011. "Fitness landscape and tax planning: NK model for fiscal federalism," MPRA Paper 33770, University Library of Munich, Germany.
    3. Thomas Holtfort, 2019. "From standard to evolutionary finance: a literature survey," Management Review Quarterly, Springer, vol. 69(2), pages 207-232, June.
    4. Giovanni Villani & Marta Biancardi, 2023. "An Evolutionary Game to Study Banks–Firms Relationship: Monitoring Intensity and Private Benefit," Computational Economics, Springer;Society for Computational Economics, vol. 61(3), pages 1075-1093, March.

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