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How market ecology explains market malfunction

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  • Maarten P. Scholl

    (Institute for New Economic Thinking, Oxford Martin School, University of Oxford, Oxford OX1 3QD, United Kingdom; Computer Science Department, University of Oxford, Oxford OX1 3QD, United Kingdom;)

  • Anisoara Calinescu

    (Computer Science Department, University of Oxford, Oxford OX1 3QD, United Kingdom)

  • J. Doyne Farmer

    (Institute for New Economic Thinking, Oxford Martin School, University of Oxford, Oxford OX1 3QD, United Kingdom; Mathematical Institute, University of Oxford, Oxford OX1 3QD, United Kingdom; Santa Fe Institute, Santa Fe, NM 87501)

Abstract

Standard approaches to the theory of financial markets are based on equilibrium and efficiency. Here we develop an alternative based on concepts and methods developed by biologists, in which the wealth invested in a financial strategy is like the abundance of a species. We study a toy model of a market consisting of value investors, trend followers, and noise traders. We show that the average returns of strategies are strongly density dependent; that is, they depend on the wealth invested in each strategy at any given time. In the absence of noise, the market would slowly evolve toward an efficient equilibrium, but the statistical uncertainty in profitability (which is calibrated to match real markets) makes this noisy and uncertain. Even in the long term, the market spends extended periods of time away from perfect efficiency. We show how core concepts from ecology, such as the community matrix and food webs, give insight into market behavior. For example, at the efficient equilibrium, all three strategies have a mutualistic relationship, meaning that an increase in the wealth of one increases the returns of the others. The wealth dynamics of the market ecosystem explain how market inefficiencies spontaneously occur and gives insight into the origins of excess price volatility and deviations of prices from fundamental values.

Suggested Citation

  • Maarten P. Scholl & Anisoara Calinescu & J. Doyne Farmer, 2021. "How market ecology explains market malfunction," Proceedings of the National Academy of Sciences, Proceedings of the National Academy of Sciences, vol. 118(26), pages 2015574118-, June.
  • Handle: RePEc:nas:journl:v:118:y:2021:p:e2015574118
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    References listed on IDEAS

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    Cited by:

    1. Schmitt, Noemi & Westerhoff, Frank, 2021. "Trend followers, contrarians and fundamentalists: Explaining the dynamics of financial markets," Journal of Economic Behavior & Organization, Elsevier, vol. 192(C), pages 117-136.
    2. Edgardo Brigatti & Estevan Augusto Amazonas Mendes, 2021. "Testing macroecological theories in cryptocurrency market: neutral models can not describe diversity patterns and their variation," Papers 2111.02067, arXiv.org, revised Jul 2022.
    3. Gardini, L. & Radi, D. & Schmitt, N. & Sushko, I. & Westerhoff, F., 2022. "Causes of fragile stock market stability," Journal of Economic Behavior & Organization, Elsevier, vol. 200(C), pages 483-498.
    4. Didier Wernli & Lucas Böttcher & Flore Vanackere & Yuliya Kaspiarovich & Maria Masood & Nicolas Levrat, 2023. "Understanding and governing global systemic crises in the 21st century: A complexity perspective," Global Policy, London School of Economics and Political Science, vol. 14(2), pages 207-228, May.
    5. Xiao-Yang Liu & Jingyang Rui & Jiechao Gao & Liuqing Yang & Hongyang Yang & Zhaoran Wang & Christina Dan Wang & Jian Guo, 2021. "FinRL-Meta: A Universe of Near-Real Market Environments for Data-Driven Deep Reinforcement Learning in Quantitative Finance," Papers 2112.06753, arXiv.org, revised Mar 2022.
    6. Hirshleifer, David & Lo, Andrew W. & Zhang, Ruixun, 2023. "Social contagion and the survival of diverse investment styles," Journal of Economic Dynamics and Control, Elsevier, vol. 154(C).
    7. de Moura, Fernanda Senra & Barbrook-Johnson, Peter, 2022. "Using data-driven systems mapping to contextualise complexity economics insights," INET Oxford Working Papers 2022-27, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.

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