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Microscopic understanding of heavy-tailed return distributions in an agent-based model

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  • Thilo A. Schmitt
  • Rudi Schafer
  • Michael C. Munnix
  • Thomas Guhr

Abstract

The distribution of returns in financial time series exhibits heavy tails. In empirical studies, it has been found that gaps between the orders in the order book lead to large price shifts and thereby to these heavy tails. We set up an agent based model to study this issue and, in particular, how the gaps in the order book emerge. The trading mechanism in our model is based on a double-auction order book, which is used on nearly all stock exchanges. In situations where the order book is densely occupied with limit orders we do not observe fat-tailed distributions. As soon as less liquidity is available, a gap structure forms which leads to return distributions with heavy tails. We show that return distributions with heavy tails are an order-book effect if the available liquidity is constrained. This is largely independent of the specific trading strategies.

Suggested Citation

  • Thilo A. Schmitt & Rudi Schafer & Michael C. Munnix & Thomas Guhr, 2012. "Microscopic understanding of heavy-tailed return distributions in an agent-based model," Papers 1207.2946, arXiv.org.
  • Handle: RePEc:arx:papers:1207.2946
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    File URL: http://arxiv.org/pdf/1207.2946
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    References listed on IDEAS

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    1. Carl Chiarella, 1992. "The Dynamics of Speculative Behaviour," Working Paper Series 13, Finance Discipline Group, UTS Business School, University of Technology, Sydney.
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    Cited by:

    1. Meudt, Frederik & Schmitt, Thilo A. & Schäfer, Rudi & Guhr, Thomas, 2016. "Equilibrium pricing in an order book environment: Case study for a spin model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 453(C), pages 228-235.
    2. Wagner, D.C. & Schmitt, T.A. & Schäfer, R. & Guhr, T. & Wolf, D.E., 2014. "Analysis of a decision model in the context of equilibrium pricing and order book pricing," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 415(C), pages 347-353.
    3. Vygintas Gontis & Aleksejus Kononovicius, 2014. "Consentaneous Agent-Based and Stochastic Model of the Financial Markets," PLOS ONE, Public Library of Science, vol. 9(7), pages 1-12, July.
    4. Roberto Mota Navarro & Hernán Larralde, 2017. "A detailed heterogeneous agent model for a single asset financial market with trading via an order book," PLOS ONE, Public Library of Science, vol. 12(2), pages 1-27, February.
    5. Roberto Mota Navarro & Hern'an Larralde Ridaura, 2016. "A detailed heterogeneous agent model for a single asset financial market with trading via an order book," Papers 1601.00229, arXiv.org, revised Jul 2016.
    6. Frederik Meudt & Thilo A. Schmitt & Rudi Schafer & Thomas Guhr, 2015. "Equilibrium Pricing in an Order Book Environment: Case Study for a Spin Model," Papers 1502.01125, arXiv.org.
    7. Daniel C. Wagner & Thilo A. Schmitt & Rudi Schafer & Thomas Guhr & Dietrich E. Wolf, 2014. "Analysis of a decision model in the context of equilibrium pricing and order book pricing," Papers 1404.7356, arXiv.org.
    8. Roberto Mota Navarro & Francois Leyvraz & Hern'an Larralde, 2023. "Dynamical properties of volume at the spread in the Bitcoin/USD market," Papers 2304.01907, arXiv.org, revised May 2023.

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