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Fundamentalists clashing over the book: a study of order-driven stock markets

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  • Marco Licalzi
  • Paolo Pellizzari

Abstract

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

Suggested Citation

  • Marco Licalzi & Paolo Pellizzari, 2003. "Fundamentalists clashing over the book: a study of order-driven stock markets," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 470-480.
  • Handle: RePEc:taf:quantf:v:3:y:2003:i:6:p:470-480
    DOI: 10.1088/1469-7688/3/6/306
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    References listed on IDEAS

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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. 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.
    3. Zoltan Eisler & Janos Kertesz & Fabrizio Lillo & Rosario Mantegna, 2009. "Diffusive behavior and the modeling of characteristic times in limit order executions," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 547-563.
    4. Marko Petrovic & Bulent Ozel & Andrea Teglio & Marco Raberto & Silvano Cincotti, 2017. "Eurace Open: An agent-based multi-country model," Working Papers 2017/09, Economics Department, Universitat Jaume I, Castellón (Spain).
    5. Iori, G. & Porter, J., 2012. "Agent-Based Modelling for Financial Markets," Working Papers 12/08, Department of Economics, City University London.
    6. 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.
    7. Chiarella, Carl & Iori, Giulia, 2009. "The impact of heterogeneous trading rules on the limit order book and order flows," Journal of Economic Dynamics and Control, Elsevier, vol. 33(3), pages 525-537.
    8. 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.
    9. Gareth W. Peters & Efstathios Panayi & Francois Septier, 2015. "SMC-ABC methods for the estimation of stochastic simulation models of the limit order book," Papers 1504.05806, arXiv.org.
    10. 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.
    11. 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.
    12. Recchioni, Maria Cristina & Tedeschi, Gabriele & Berardi, Simone, 2014. "Bank's strategies during the financial crisis," FinMaP-Working Papers 25, Collaborative EU Project FinMaP - Financial Distortions and Macroeconomic Performance: Expectations, Constraints and Interaction of Agents.
    13. Chiarella, Carl & He, Xue-Zhong & Pellizzari, Paolo, 2012. "A Dynamic Analysis Of The Microstructure Of Moving Average Rules In A Double Auction Market," Macroeconomic Dynamics, Cambridge University Press, vol. 16(04), pages 556-575, September.
    14. Andrea Consiglio & Valerio Lacagnina & Annalisa Russino, 2005. "A simulation analysis of the microstructure of an order driven financial market with multiple securities and portfolio choices," Quantitative Finance, Taylor & Francis Journals, vol. 5(1), pages 71-87.
    15. Paolo Pellizzari & Arianna Forno, 2007. "A comparison of different trading protocols in an agent-based market," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 2(1), pages 27-43, June.
    16. Liu, Xinghua & Gregor, Shirley & Yang, Jianmei, 2008. "The effects of behavioral and structural assumptions in artificial stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(11), pages 2535-2546.
    17. Ladley, Dan & Schenk-Hoppé, Klaus Reiner, 2009. "Do stylised facts of order book markets need strategic behaviour?," Journal of Economic Dynamics and Control, Elsevier, vol. 33(4), pages 817-831, April.
    18. Raberto, Marco & Cincotti, Silvano, 2005. "Modeling and simulation of a double auction artificial financial market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 355(1), pages 34-45.
    19. Anufriev Mikhail & Bottazzi Giulio, 2012. "Asset Pricing with Heterogeneous Investment Horizons," Studies in Nonlinear Dynamics & Econometrics, De Gruyter, vol. 16(4), pages 1-38, October.
    20. 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.
    21. Kirchler, Michael & Huber, Jürgen, 2009. "An exploration of commonly observed stylized facts with data from experimental asset markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 388(8), pages 1631-1658.
    22. Kuroda, Koji & Murai, Joshin, 2007. "Limit theorems in financial market models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 383(1), pages 28-34.
    23. Krause, Andreas, 2006. "Fat tails and multi-scaling in a simple model of limit order markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 368(1), pages 183-190.
    24. Lijian Wei & Wei Zhang & Xue-Zhong He & Yongjie Zhang, 2013. "Learning and Information Dissemination in Limit Order Markets," Research Paper Series 333, Quantitative Finance Research Centre, University of Technology, Sydney.
    25. 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.

    More about this item

    JEL classification:

    • G19 - Financial Economics - - General Financial Markets - - - Other
    • D84 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Expectations; Speculations
    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques

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