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Fundamentalists Clashing over the Book: A Study of Order-Driven Stock Markets

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Author Info

  • Marco LiCalzi

    (Universita' di Venezia)

  • Paolo Pellizzari

    (Universita' di Venezia)

Abstract

Agent-based models of market dynamics must strike a compromise between the structural assumptions that represent the trading mechanism and the behavioral assumptions that describe the rules by which traders take their decisions. We present a structurally detailed model of an order- driven stock market and show that a minimal set of behavioral assumptions suffices to generate a leptokurtic distribution of short- term log-returns. This result backs up the conjecture that the emergence of some statistical properties of financial time series is due to the microstructure of stock markets.

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File URL: http://128.118.178.162/eps/comp/papers/0207/0207001.pdf
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Bibliographic Info

Paper provided by EconWPA in its series Computational Economics with number 0207001.

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Length: 19 pages
Date of creation: 12 Jul 2002
Date of revision: 04 Mar 2003
Handle: RePEc:wpa:wuwpco:0207001

Note: Type of Document - pdf; prepared on Macintosh; to print on Postcript; pages: 19; figures: included
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Web page: http://128.118.178.162

Related research

Keywords: price dynamics; statistical properties of returns; behavioral and structural assumptions; agent-based simulations;

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References

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  8. Maslov, Sergei, 2000. "Simple model of a limit order-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 278(3), pages 571-578.
  9. Carl Chiarella & Giulia Iori, 2002. "A simulation analysis of the microstructure of double auction markets," Quantitative Finance, Taylor and Francis Journals, vol. 2(5), pages 346-353.
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Citations

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Cited by:
  1. LiCalzi, Marco & Pellizzari, Paolo, 2007. "Simple market protocols for efficient risk sharing," Journal of Economic Dynamics and Control, Elsevier, vol. 31(11), pages 3568-3590, November.
  2. Paolo Pellizzari & Arianna Forno, 2007. "A comparison of different trading protocols in an agent-based market," Journal of Economic Interaction and Coordination, Springer, vol. 2(1), pages 27-43, June.
  3. Kirchler, Michael & Huber, Jurgen, 2007. "Fat tails and volatility clustering in experimental asset markets," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1844-1874, June.
  4. LiCalzi, Marco & Pellizzari, Paolo, 2006. "Breeds of risk-adjusted fundamentalist strategies in an order-driven market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 359(C), pages 619-633.
  5. Dan Ladley & Klaus Reiner Schenk-Hoppe, 2007. "Do Stylised Facts of Order Book Markets Need Strategic Behaviour?," Swiss Finance Institute Research Paper Series 07-20, Swiss Finance Institute.
  6. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
  7. Scalas, Enrico & Kaizoji, Taisei & Kirchler, Michael & Huber, Jürgen & Tedeschi, Alessandra, 2006. "Waiting times between orders and trades in double-auction markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 366(C), pages 463-471.
  8. Carl Chiarella & Giulia Iori, 2005. "The Impact of Heterogeneous Trading Rules on the Limit Order Book and Order Flows," Research Paper Series 152, Quantitative Finance Research Centre, University of Technology, Sydney.
  9. Tedeschi, Gabriele & Iori, Giulia & Gallegati, Mauro, 2012. "Herding effects in order driven markets: The rise and fall of gurus," Journal of Economic Behavior & Organization, Elsevier, vol. 81(1), pages 82-96.
  10. Anufriev, Mikhail & Panchenko, Valentyn, 2009. "Asset prices, traders' behavior and market design," Journal of Economic Dynamics and Control, Elsevier, vol. 33(5), pages 1073-1090, May.
  11. Consiglio, Andrea & Russino, Annalisa, 2007. "How does learning affect market liquidity? A simulation analysis of a double-auction financial market with portfolio traders," Journal of Economic Dynamics and Control, Elsevier, vol. 31(6), pages 1910-1937, June.

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