IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1304.6819.html
   My bibliography  Save this paper

A Fokker-Planck description for the queue dynamics of large tick stocks

Author

Listed:
  • A. Gareche
  • G. Disdier
  • J. Kockelkoren
  • J. -P. Bouchaud

Abstract

Motivated by empirical data, we develop a statistical description of the queue dynamics for large tick assets based on a two-dimensional Fokker-Planck (diffusion) equation, that explicitly includes state dependence, i.e. the fact that the drift and diffusion depends on the volume present on both sides of the spread. "Jump" events, corresponding to sudden changes of the best limit price, must also be included as birth-death terms in the Fokker-Planck equation. All quantities involved in the equation can be calibrated using high-frequency data on best quotes. One of our central finding is the the dynamical process is approximately scale invariant, i.e., the only relevant variable is the ratio of the current volume in the queue to its average value. While the latter shows intraday seasonalities and strong variability across stocks and time periods, the dynamics of the rescaled volumes is universal. In terms of rescaled volumes, we found that the drift has a complex two-dimensional structure, which is a sum of a gradient contribution and a rotational contribution, both stable across stocks and time. This drift term is entirely responsible for the dynamical correlations between the ask queue and the bid queue.

Suggested Citation

  • A. Gareche & G. Disdier & J. Kockelkoren & J. -P. Bouchaud, 2013. "A Fokker-Planck description for the queue dynamics of large tick stocks," Papers 1304.6819, arXiv.org.
  • Handle: RePEc:arx:papers:1304.6819
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1304.6819
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. P. Weber & B. Rosenow, 2005. "Order book approach to price impact," Quantitative Finance, Taylor & Francis Journals, vol. 5(4), pages 357-364.
    2. Avellaneda, Marco & Reed, Josh & Stoikov, Sasha, 2011. "Forecasting prices from level-I quotes in the presence of hidden liquidity," Algorithmic Finance, IOS Press, vol. 1(1), pages 35-43.
    3. Zoltan Eisler & Jean-Philippe Bouchaud & Julien Kockelkoren, 2011. "Models for the impact of all order book events," Papers 1107.3364, arXiv.org.
    4. B. Tóth & Z. Eisler & F. Lillo & J. Kockelkoren & J.-P. Bouchaud & J.D. Farmer, 2012. "How does the market react to your order flow?," Quantitative Finance, Taylor & Francis Journals, vol. 12(7), pages 1015-1024, May.
    5. Ioanid Rosu, 2009. "A Dynamic Model of the Limit Order Book," Post-Print hal-00515873, HAL.
    6. Zoltán Eisler & Jean-Philippe Bouchaud & Julien Kockelkoren, 2012. "The price impact of order book events: market orders, limit orders and cancellations," Quantitative Finance, Taylor & Francis Journals, vol. 12(9), pages 1395-1419, September.
    7. Ioanid Rosu, 2009. "A Dynamic Model of the Limit Order Book," The Review of Financial Studies, Society for Financial Studies, vol. 22(11), pages 4601-4641, November.
    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. Emmanuel Bacry & Thibault Jaisson & Jean-Francois Muzy, 2014. "Estimation of slowly decreasing Hawkes kernels: Application to high frequency order book modelling," Papers 1412.7096, arXiv.org.
    2. Martin D. Gould & Julius Bonart, 2015. "Queue Imbalance as a One-Tick-Ahead Price Predictor in a Limit Order Book," Papers 1512.03492, arXiv.org.
    3. Julius Bonart & Martin Gould, 2015. "Latency and liquidity provision in a limit order book," Papers 1511.04116, arXiv.org, revised Jun 2016.
    4. Dupret, Jean-Loup & Hainaut, Donatien, 2023. "Optimal liquidation under indirect price impact with propagator," LIDAM Discussion Papers ISBA 2023012, Université catholique de Louvain, Institute of Statistics, Biostatistics and Actuarial Sciences (ISBA).
    5. Aim'e Lachapelle & Jean-Michel Lasry & Charles-Albert Lehalle & Pierre-Louis Lions, 2013. "Efficiency of the Price Formation Process in Presence of High Frequency Participants: a Mean Field Game analysis," Papers 1305.6323, arXiv.org, revised Aug 2015.
    6. Aurélien Alfonsi & Pierre Blanc, 2016. "Dynamic optimal execution in a mixed-market-impact Hawkes price model," Finance and Stochastics, Springer, vol. 20(1), pages 183-218, January.
    7. Iacopo Mastromatteo, 2014. "Apparent impact: the hidden cost of one-shot trades," Papers 1409.8497, arXiv.org, revised Jun 2015.
    8. Julius Bonart & Martin D. Gould, 2017. "Latency and liquidity provision in a limit order book," Quantitative Finance, Taylor & Francis Journals, vol. 17(10), pages 1601-1616, October.
    9. Aur'elien Alfonsi & Pierre Blanc, 2014. "Dynamic optimal execution in a mixed-market-impact Hawkes price model," Papers 1404.0648, arXiv.org, revised Jun 2015.
    10. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    11. Weibing Huang & Charles-Albert Lehalle & Mathieu Rosenbaum, 2015. "Simulating and Analyzing Order Book Data: The Queue-Reactive Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 107-122, March.
    12. Marc Hoffmann & Mauricio Labadie & Charles-Albert Lehalle & Gilles Pagès & Huyên Pham & Mathieu Rosenbaum, 2013. "Optimization And Statistical Methods For High Frequency Finance," Post-Print hal-01102785, HAL.
    13. Tzu-Wei Yang & Lingjiong Zhu, 2015. "A reduced-form model for level-1 limit order books," Papers 1508.07891, arXiv.org, revised Nov 2016.
    14. Aurélien Alfonsi & Pierre Blanc, 2016. "Dynamic optimal execution in a mixed-market-impact Hawkes price model," Post-Print hal-00971369, HAL.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Weibing Huang & Charles-Albert Lehalle & Mathieu Rosenbaum, 2015. "Simulating and Analyzing Order Book Data: The Queue-Reactive Model," Journal of the American Statistical Association, Taylor & Francis Journals, vol. 110(509), pages 107-122, March.
    2. 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.
    3. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.
    4. Havran, Dániel & Váradi, Kata, 2016. "A limitáras ajánlatok szerkezete és dinamikája a Budapesti Értéktőzsdén. Az OTP- és a Mol-részvények esete [The structure and dynamics of limit orders on the Budapest stock exchange: The cases of O," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(9), pages 966-992.
    5. Nikolsko-Rzhevska, Olena & Nikolsko-Rzhevskyy, Alex & Black, Jeffrey R., 2020. "The life of U’s: Order revisions on NASDAQ," Journal of Banking & Finance, Elsevier, vol. 111(C).
    6. Daniel Havran & Kata Varadi, 2015. "Price Impact and the Recovery of the Limit Order Book: Why Should We Care About Informed Liquidity Providers?," CERS-IE WORKING PAPERS 1540, Institute of Economics, Centre for Economic and Regional Studies.
    7. Withanawasam, R.M. & Whigham, P.A. & Crack, Timothy Falcon, 2013. "Characterizing limit order prices," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 392(21), pages 5346-5355.
    8. 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.
    9. Duong, Huu Nhan & Kalev, Petko S., 2013. "Anonymity and order submissions," Pacific-Basin Finance Journal, Elsevier, vol. 25(C), pages 101-118.
    10. Guillaume Rocheteau & Pierre‐Olivier Weill, 2011. "Liquidity in Frictional Asset Markets," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 43(s2), pages 261-282, October.
    11. Marcello Rambaldi & Emmanuel Bacry & Jean-Franc{c}ois Muzy, 2018. "Disentangling and quantifying market participant volatility contributions," Papers 1807.07036, arXiv.org.
    12. Peter Malec, 2016. "A Semiparametric Intraday GARCH Model," Cambridge Working Papers in Economics 1633, Faculty of Economics, University of Cambridge.
    13. Ulrich Horst & Michael Paulsen, 2017. "A Law of Large Numbers for Limit Order Books," Mathematics of Operations Research, INFORMS, vol. 42(4), pages 1280-1312, November.
    14. Dionne, Georges & Pacurar, Maria & Zhou, Xiaozhou, 2015. "Liquidity-adjusted Intraday Value at Risk modeling and risk management: An application to data from Deutsche Börse," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 202-219.
    15. Filip Stanek & Jiri Kukacka, 2018. "The Impact of the Tobin Tax in a Heterogeneous Agent Model of the Foreign Exchange Market," Computational Economics, Springer;Society for Computational Economics, vol. 51(4), pages 865-892, April.
    16. Menkhoff, Lukas & Osler, Carol L. & Schmeling, Maik, 2010. "Limit-order submission strategies under asymmetric information," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2665-2677, November.
    17. Alexis Stenfors & Masayuki Susai, 2021. "Stealth Trading in FX Markets," Working Papers in Economics & Finance 2021-02, University of Portsmouth, Portsmouth Business School, Economics and Finance Subject Group.
    18. Haoxiang Zhu, 2014. "Do Dark Pools Harm Price Discovery?," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 747-789.
    19. A. Lykov & S. Muzychka & K. Vaninsky, 2012. "Investor's sentiment in multi-agent model of the continuous double auction," Papers 1208.3083, arXiv.org, revised Feb 2016.
    20. Gerry Tsoukalas & Jiang Wang & Kay Giesecke, 2019. "Dynamic Portfolio Execution," Management Science, INFORMS, vol. 67(5), pages 2015-2040, May.

    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:1304.6819. See general information about how to correct material in RePEc.

    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 bibliographic 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.

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

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

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.