IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1502.00680.html
   My bibliography  Save this paper

Quasi-Centralized Limit Order Books

Author

Listed:
  • Martin D. Gould
  • Mason A. Porter
  • Sam D. Howison

Abstract

A quasi-centralized limit order book (QCLOB) is a limit order book (LOB) in which financial institutions can only access the trading opportunities offered by counterparties with whom they possess sufficient bilateral credit. We perform an empirical analysis of a recent, high-quality data set from a large electronic trading platform that utilizes QCLOBs to facilitate trade. We find many significant differences between our results and those widely reported for other LOBs. We also uncover a remarkable empirical universality: although the distributions describing order flow and market state vary considerably across days, a simple, linear rescaling causes them to collapse onto a single curve. Motivated by this finding, we propose a semi-parametric model of order flow and market state in a QCLOB on a single trading day. Our model provides similar performance to that of parametric curve-fitting techniques, while being simpler to compute and faster to implement.

Suggested Citation

  • Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "Quasi-Centralized Limit Order Books," Papers 1502.00680, arXiv.org, revised Oct 2016.
  • Handle: RePEc:arx:papers:1502.00680
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1502.00680
    File Function: Latest version
    Download Restriction: no

    References listed on IDEAS

    as
    1. Eric Smith & J Doyne Farmer & Laszlo Gillemot & Supriya Krishnamurthy, 2003. "Statistical theory of the continuous double auction," Quantitative Finance, Taylor & Francis Journals, vol. 3(6), pages 481-514.
    2. Lo, Ingrid & Sapp, Stephen G., 2010. "Order aggressiveness and quantity: How are they determined in a limit order market?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 20(3), pages 213-237, July.
    3. Michael J. Sager & Mark P. Taylor, 2006. "Under the microscope: the structure of the foreign exchange market," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 11(1), pages 81-95.
    4. Bjonnes, Geir Hoidal & Rime, Dagfinn, 2005. "Dealer behavior and trading systems in foreign exchange markets," Journal of Financial Economics, Elsevier, vol. 75(3), pages 571-605, March.
    5. Aur'elien Alfonsi & Antje Fruth & Alexander Schied, 2007. "Optimal execution strategies in limit order books with general shape functions," Papers 0708.1756, arXiv.org, revised Feb 2010.
    6. Burton Hollifield & Robert A. Miller & Patrik Sandås, 2004. "Empirical Analysis of Limit Order Markets," Review of Economic Studies, Oxford University Press, vol. 71(4), pages 1027-1063.
    7. Mike, Szabolcs & Farmer, J. Doyne, 2008. "An empirical behavioral model of liquidity and volatility," Journal of Economic Dynamics and Control, Elsevier, vol. 32(1), pages 200-234, January.
    8. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical shape function of limit-order books in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(21), pages 5182-5188.
    9. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2010. "Limit Order Books," Papers 1012.0349, arXiv.org, revised Apr 2013.
    10. Challet, Damien & Stinchcombe, Robin, 2001. "Analyzing and modeling 1+1d markets," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 300(1), pages 285-299.
    11. 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.
    12. Gao-Feng Gu & Wei Chen & Wei-Xing Zhou, 2008. "Empirical shape function of limit-order books in the Chinese stock market," Papers 0801.3712, arXiv.org.
    13. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. " An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-1689, December.
    14. 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.
    15. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    16. Aurelien Alfonsi & Antje Fruth & Alexander Schied, 2010. "Optimal execution strategies in limit order books with general shape functions," Quantitative Finance, Taylor & Francis Journals, vol. 10(2), pages 143-157.
    17. 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.
    18. 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.
    19. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    20. Gu, Gao-Feng & Chen, Wei & Zhou, Wei-Xing, 2008. "Empirical regularities of order placement in the Chinese stock market," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 387(13), pages 3173-3182.
    21. William Barker, 2007. "The Global Foreign Exchange Market: Growth and Transformation," Bank of Canada Review, Bank of Canada, vol. 2007(Autumn), pages 4-13.
    22. Matthieu Wyart & Jean-Philippe Bouchaud & Julien Kockelkoren & Marc Potters & Michele Vettorazzo, 2008. "Relation between bid-ask spread, impact and volatility in order-driven markets," Quantitative Finance, Taylor & Francis Journals, vol. 8(1), pages 41-57.
    23. Stephan, Jens A & Whaley, Robert E, 1990. " Intraday Price Change and Trading Volume Relations in the Stock and Stock Option Markets," Journal of Finance, American Finance Association, vol. 45(1), pages 191-220, March.
    24. F. Lillo & Szabolcs Mike & J. Doyne Farmer, 2004. "A theory for long-memory in supply and demand," Papers cond-mat/0412708, arXiv.org, revised Mar 2005.
    25. Anirban Chakraborti & Ioane Muni Toke & Marco Patriarca & Frederic Abergel, 2011. "Econophysics review: I. Empirical facts," Quantitative Finance, Taylor & Francis Journals, vol. 11(7), pages 991-1012.
    26. Axioglou, Christos & Skouras, Spyros, 2011. "Markets change every day: Evidence from the memory of trade direction," Journal of Empirical Finance, Elsevier, vol. 18(3), pages 423-446, June.
    27. Rama Cont & Arseniy Kukanov, 2012. "Optimal order placement in limit order markets," Papers 1210.1625, arXiv.org, revised Nov 2014.
    28. G.-H. Mu & W. Chen & J. Kertész & W.-X. Zhou, 2009. "Preferred numbers and the distributions of trade sizes and trading volumes in the Chinese stock market," The European Physical Journal B: Condensed Matter and Complex Systems, Springer;EDP Sciences, vol. 68(1), pages 145-152, March.
    29. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Martin D. Gould & Mason A. Porter & Sam D. Howison, 2015. "The Long Memory of Order Flow in the Foreign Exchange Spot Market," Papers 1504.04354, arXiv.org, revised Oct 2015.

    More about this item

    NEP fields

    This paper has been announced in the following NEP Reports:

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:arx:papers:1502.00680. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (arXiv administrators). General contact details of provider: http://arxiv.org/ .

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.