IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1205.3051.html
   My bibliography  Save this paper

Optimal High Frequency Trading in a Pro-Rata Microstructure with Predictive Information

Author

Listed:
  • Fabien Guilbaud

    (LPMA)

  • Huy^en Pham

    (LPMA, CREST)

Abstract

We propose a framework to study optimal trading policies in a one-tick pro-rata limit order book, as typically arises in short-term interest rate futures contracts. The high-frequency trader has the choice to trade via market orders or limit orders, which are represented respectively by impulse controls and regular controls. We model and discuss the consequences of the two main features of this particular microstructure: first, the limit orders sent by the high frequency trader are only partially executed, and therefore she has no control on the executed quantity. For this purpose, cumulative executed volumes are modelled by compound Poisson processes. Second, the high frequency trader faces the overtrading risk, which is the risk of brutal variations in her inventory. The consequences of this risk are investigated in the context of optimal liquidation. The optimal trading problem is studied by stochastic control and dynamic programming methods, which lead to a characterization of the value function in terms of an integro quasi-variational inequality. We then provide the associated numerical resolution procedure, and convergence of this computational scheme is proved. Next, we examine several situations where we can on one hand simplify the numerical procedure by reducing the number of state variables, and on the other hand focus on specific cases of practical interest. We examine both a market making problem and a best execution problem in the case where the mid-price process is a martingale. We also detail a high frequency trading strategy in the case where a (predictive) directional information on the mid-price is available. Each of the resulting strategies are illustrated by numerical tests.

Suggested Citation

  • Fabien Guilbaud & Huy^en Pham, 2012. "Optimal High Frequency Trading in a Pro-Rata Microstructure with Predictive Information," Papers 1205.3051, arXiv.org.
  • Handle: RePEc:arx:papers:1205.3051
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1205.3051
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Field, Jonathan & Large, Jeremy, 2008. "Pro-rata matching and one-tick futures markets," CFS Working Paper Series 2008/40, Center for Financial Studies (CFS).
    2. repec:dau:papers:123456789/7390 is not listed on IDEAS
    3. Fabien Guilbaud & Huyen Pham, 2011. "Optimal High Frequency Trading with limit and market orders," Papers 1106.5040, arXiv.org.
    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. Kaj Nyström & Sidi Mohamed Ould Aly & Changyong Zhang, 2014. "Market Making And Portfolio Liquidation Under Uncertainty," International Journal of Theoretical and Applied Finance (IJTAF), World Scientific Publishing Co. Pte. Ltd., vol. 17(05), pages 1-33.
    2. Filippo Passerini & Samuel E. Vazquez, 2015. "Optimal Trading with Alpha Predictors," Papers 1501.03756, arXiv.org, revised Jan 2015.
    3. Jack Sarkissian, 2013. "Coupled mode theory of stock price formation," Papers 1312.4622, arXiv.org.
    4. Rama Cont & Arseniy Kukanov, 2012. "Optimal order placement in limit order markets," Working Papers hal-00737491, HAL.
    5. Rama Cont & Arseniy Kukanov, 2012. "Optimal order placement in limit order markets," Papers 1210.1625, arXiv.org, revised Nov 2014.

    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. Fabien Guilbaud & Huyên Pham, 2012. "Optimal High Frequency Trading in a Pro-Rata Microstructure with Predictive Information," Working Papers hal-00697125, HAL.
    2. Sophie Laruelle & Charles-Albert Lehalle & Gilles Pag`es, 2011. "Optimal posting price of limit orders: learning by trading," Papers 1112.2397, arXiv.org, revised Sep 2012.
    3. 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.
    4. Pietro Fodra & Mauricio Labadie, 2012. "High-frequency market-making with inventory constraints and directional bets," Papers 1206.4810, arXiv.org.
    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. Pierre Cardaliaguet & Charles-Albert Lehalle, 2016. "Mean Field Game of Controls and An Application To Trade Crowding," Papers 1610.09904, arXiv.org, revised Sep 2017.
    7. Haynes, Richard & Onur, Esen, 2020. "Precedence rules in matching algorithms," Journal of Commodity Markets, Elsevier, vol. 19(C).
    8. Qing-Qing Yang & Jia-Wen Gu & Wai-Ki Ching & Tak-Kuen Siu, 2019. "On Optimal Pricing Model for Multiple Dealers in a Competitive Market," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 397-431, January.
    9. van Kervel, V.L., 2013. "Competition between stock exchanges and optimal trading," Other publications TiSEM 5c608a0f-527d-441d-a910-e, Tilburg University, School of Economics and Management.
    10. Joseph Jerome & Gregory Palmer & Rahul Savani, 2022. "Market Making with Scaled Beta Policies," Papers 2207.03352, arXiv.org, revised Sep 2022.
    11. Thomas Spooner & John Fearnley & Rahul Savani & Andreas Koukorinis, 2018. "Market Making via Reinforcement Learning," Papers 1804.04216, arXiv.org.
    12. Pietro Fodra & Mauricio Labadie, 2013. "High-frequency market-making for multi-dimensional Markov processes," Papers 1303.7177, arXiv.org, revised Apr 2013.
    13. Gianbiagio Curato & Fabrizio Lillo, 2013. "Modeling the coupled return-spread high frequency dynamics of large tick assets," Papers 1310.4539, arXiv.org.
    14. 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.
    15. Peter Belcak & Jan-Peter Calliess & Stefan Zohren, 2020. "Fast Agent-Based Simulation Framework with Applications to Reinforcement Learning and the Study of Trading Latency Effects," Papers 2008.07871, arXiv.org, revised Sep 2022.
    16. Hugh L. Christensen & Richard E. Turner & Simon I. Hill & Simon J. Godsill, 2013. "Rebuilding the limit order book: sequential Bayesian inference on hidden states," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1779-1799, November.

    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:1205.3051. 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.