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Order Placement in a Continuous Double Auction Agent Based Model

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  • Alexandru Mandes

    (University of Gießen)

Abstract

Modeling intraday financial markets by means of agent based models requires an additional building block which reflects the order execution, i.e. the trading process. Current implementations rely only on stochastic placement strategies, ranging from total randomness to adding some budget constraints. This contribution addresses the issue of order placement for low-tech traders, by replacing the zero-intelligence assumption with a microtrading-based approach. The results show that the power-law decaying relative price distribution of off-spread limit orders and the concave shape of the overall market price impact can be replicated when rational order submission strategies are used.

Suggested Citation

  • Alexandru Mandes, 2014. "Order Placement in a Continuous Double Auction Agent Based Model," MAGKS Papers on Economics 201443, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    • Handle: RePEc:mar:magkse:201443
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    File URL: http://www.uni-marburg.de/fb02/makro/forschung/magkspapers/43-2014_mandes.pdf
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    References listed on IDEAS

    as
    1. 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.
    2. P. Weber & B. Rosenow, 2005. "Order book approach to price impact," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 357-364.
    3. Arthur, W.B. & Holland, J.H. & LeBaron, B. & Palmer, R. & Tayler, P., 1996. "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Working papers 9625, Wisconsin Madison - Social Systems.
    4. Thomas Lux & Michele Marchesi, 2000. "Volatility Clustering In Financial Markets: A Microsimulation Of Interacting Agents," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 3(04), pages 675-702.
    5. repec:bla:jecsur:v:22:y:2008:i:4:p:711-751 is not listed on IDEAS
    6. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Science & Finance (CFM) working paper archive 0203511, Science & Finance, Capital Fund Management.
    7. Carl Hopman, 2007. "Do supply and demand drive stock prices?," Quantitative Finance, Taylor & Francis Journals, vol. 7(1), pages 37-53.
    8. Thomas Lux & Michele Marchesi, 1999. "Scaling and criticality in a stochastic multi-agent model of a financial market," Nature, Nature, vol. 397(6719), pages 498-500, February.
    9. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2002. "On the emergent properties of artificial stock markets: the efficient market hypothesis and the rational expectations hypothesis," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 217-239, October.
    10. William A. Brock & Cars H. Hommes, 1997. "A Rational Route to Randomness," Econometrica, Econometric Society, vol. 65(5), pages 1059-1096, September.
    11. Alessandro Beber & Cecilia Caglio, 2005. "Order Submission Strategies and Information: Empirical Evidence from the NYSE," FAME Research Paper Series rp146, International Center for Financial Asset Management and Engineering.
    12. Farmer, J. Doyne & Joshi, Shareen, 2002. "The price dynamics of common trading strategies," Journal of Economic Behavior & Organization, Elsevier, vol. 49(2), pages 149-171, October.
    13. Lux, Thomas, 1998. "The socio-economic dynamics of speculative markets: interacting agents, chaos, and the fat tails of return distributions," Journal of Economic Behavior & Organization, Elsevier, vol. 33(2), pages 143-165, January.
    14. William A. Brock & Cars H. Hommes, 2001. "A Rational Route to Randomness," Chapters, in: W. D. Dechert (ed.), Growth Theory, Nonlinear Dynamics and Economic Modelling, chapter 16, pages 402-438, Edward Elgar Publishing.
    15. Chen, Shu-Heng & Yeh, Chia-Hsuan, 2001. "Evolving traders and the business school with genetic programming: A new architecture of the agent-based artificial stock market," Journal of Economic Dynamics and Control, Elsevier, vol. 25(3-4), pages 363-393, March.
    16. Rama Cont & Arseniy Kukanov, 2012. "Optimal order placement in limit order markets," Working Papers hal-00737491, HAL.
    17. Gode, Dhananjay K & Sunder, Shyam, 1993. "Allocative Efficiency of Markets with Zero-Intelligence Traders: Market as a Partial Substitute for Individual Rationality," Journal of Political Economy, University of Chicago Press, vol. 101(1), pages 119-137, February.
    18. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    19. J. Doyne Farmer & Paolo Patelli & Ilija I. Zovko, 2003. "The Predictive Power of Zero Intelligence in Financial Markets," Papers cond-mat/0309233, arXiv.org, revised Feb 2004.
    20. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Quantitative Finance, Taylor & Francis Journals, vol. 2(4), pages 251-256.
    21. R. Cont, 2001. "Empirical properties of asset returns: stylized facts and statistical issues," Quantitative Finance, Taylor & Francis Journals, vol. 1(2), pages 223-236.
    22. Kovaleva, P. & Iori, G., 2012. "Optimal Trading Strategies in a Limit Order Market with Imperfect Liquidity," Working Papers 12/05, Department of Economics, City University London.
    23. Ilija Zovko & J Doyne Farmer, 2002. "The power of patience: a behavioural regularity in limit-order placement," Quantitative Finance, Taylor & Francis Journals, vol. 2(5), pages 387-392.
    24. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2002. "Single Curve Collapse of the Price Impact Function for the New York Stock Exchange," Papers cond-mat/0207428, arXiv.org.
    25. Lux, Thomas, 1995. "Herd Behaviour, Bubbles and Crashes," Economic Journal, Royal Economic Society, vol. 105(431), pages 881-896, July.
    26. Potters, Marc & Bouchaud, Jean-Philippe, 2003. "More statistical properties of order books and price impact," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 324(1), pages 133-140.
    27. W. Brian Arthur & Paul Tayler, "undated". "Asset Pricing Under Endogenous Expectations in an Artificial Stock Market," Computing in Economics and Finance 1997 57, Society for Computational Economics.
    28. Roberto Pascual & David Veredas, 2009. "What pieces of limit order book information matter in explaining order choice by patient and impatient traders?," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 527-545.
    29. Vasiliki Plerou & Parameswaran Gopikrishnan & Xavier Gabaix & H. Eugene Stanley, 2001. "Quantifying Stock Price Response to Demand Fluctuations," Papers cond-mat/0106657, arXiv.org.
    30. F. Lillo, 2007. "Limit order placement as an utility maximization problem and the origin of power law distribution of limit order prices," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 55(4), pages 453-459, February.
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    Cited by:

    1. Veryzhenko, Iryna & Harb, Etienne & Louhichi, Waël & Oriol, Nathalie, 2017. "The impact of the French financial transaction tax on HFT activities and market quality," Economic Modelling, Elsevier, vol. 67(C), pages 307-315.
    2. Alexandru Mandes, 2015. "Impact of inventory-based electronic liquidity providers within a high-frequency event- and agent-based modeling framework," MAGKS Papers on Economics 201515, Philipps-Universität Marburg, Faculty of Business Administration and Economics, Department of Economics (Volkswirtschaftliche Abteilung).
    3. Nathalie Oriol & Iryna Veryzhenko, 2019. "Market structure or traders' behavior? A multi agent model to assess flash crash phenomena and their regulation," Quantitative Finance, Taylor & Francis Journals, vol. 19(7), pages 1075-1092, July.
    4. Iryna Veryzhenko & Lise Arena & Etienne Harb & Nathalie Oriol, 2017. "Time to Slow Down for High‐Frequency Trading? Lessons from Artificial Markets," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 24(2-3), pages 73-79, April.
    5. Iryna Veryzhenko & Lise Arena, 2017. "A Reexamination of High Frequency Trading Regulation Effectiveness in an Artificial Market Framework," Post-Print halshs-01444738, HAL.

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    More about this item

    Keywords

    agent based modeling; high-frequency financial markets; continuous double auction; order placement; market impact;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • N20 - Economic History - - Financial Markets and Institutions - - - General, International, or Comparative

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