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Order book, financial markets, and self-organized criticality

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  • Biondo, Alessio Emanuele
  • Pluchino, Alessandro
  • Rapisarda, Andrea

Abstract

We present a simple order book mechanism that regulates an artificial financial market with self-organized criticality dynamics and fat tails of returns distribution. The model shows the role played by individual imitation in determining trading decisions, while fruitfully replicates typical aggregate market behavior as the “self-fulfilling prophecy.” We also address the role of random traders as a possible decentralized solution to dampen market fluctuations.

Suggested Citation

  • Biondo, Alessio Emanuele & Pluchino, Alessandro & Rapisarda, Andrea, 2016. "Order book, financial markets, and self-organized criticality," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 196-208.
  • Handle: RePEc:eee:chsofr:v:88:y:2016:i:c:p:196-208
    DOI: 10.1016/j.chaos.2016.03.001
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    References listed on IDEAS

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    1. C. Chiarella & X-Z. He, 2001. "Asset price and wealth dynamics under heterogeneous expectations," Quantitative Finance, Taylor & Francis Journals, vol. 1(5), pages 509-526.
    2. C. H. Hommes, 2001. "Financial markets as nonlinear adaptive evolutionary systems," Quantitative Finance, Taylor & Francis Journals, vol. 1(1), pages 149-167.
    3. Mantegna,Rosario N. & Stanley,H. Eugene, 2007. "Introduction to Econophysics," Cambridge Books, Cambridge University Press, number 9780521039871, October.
    4. Hasbrouck, Joel, 2007. "Empirical Market Microstructure: The Institutions, Economics, and Econometrics of Securities Trading," OUP Catalogue, Oxford University Press, number 9780195301649.
    5. LeBaron, Blake, 2006. "Agent-based Computational Finance," Handbook of Computational Economics, in: Leigh Tesfatsion & Kenneth L. Judd (ed.), Handbook of Computational Economics, edition 1, volume 2, chapter 24, pages 1187-1233, Elsevier.
    6. Brock, W.A. & Hommes, C.H., 1997. "Models of Compelxity in Economics and Finance," Working papers 9706, Wisconsin Madison - Social Systems.
    7. 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. Alessio Emanuele Biondo, 2018. "Order book microstructure and policies for financial stability," Studies in Economics and Finance, Emerald Group Publishing Limited, vol. 35(1), pages 196-218, March.
    2. Biondo, A.E. & Pluchino, A. & Rapisarda, A., 2018. "Modeling surveys effects in political competitions," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 503(C), pages 714-726.
    3. Alessio Emanuele Biondo, 2019. "Order book modeling and financial stability," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 14(3), pages 469-489, September.
    4. Biondo, Alessio Emanuele, 2017. "Learning to forecast, risk aversion, and microstructural aspects of financial stability," Economics Discussion Papers 2017-104, Kiel Institute for the World Economy (IfW Kiel).
    5. Duarte Queirós, Sílvio M. & Anteneodo, Celia, 2016. "Complexity in quantitative finance and economics," Chaos, Solitons & Fractals, Elsevier, vol. 88(C), pages 1-2.

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