IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v229y2015i1p521-54010.1007-s10479-015-1815-7.html
   My bibliography  Save this article

Optimal trading of algorithmic orders in a liquidity fragmented market place

Author

Listed:
  • Miles Kumaresan
  • Nataša Krejić

Abstract

An optimization model for the execution of algorithmic orders at multiple trading venues is herein proposed and analyzed. The optimal trajectory consists of both market and limit orders, and takes advantage of any price or liquidity improvement in a particular market. The complexity of a multi-market environment poses a bi-level nonlinear optimization problem. The lower-level problem admits a unique solution thus enabling the second order conditions to be satisfied under a set of reasonable assumptions. The model is computationally affordable and solvable using standard software packages. The simulation results presented in the paper show the model’s effectiveness using real trade data. From the outset, great effort was made to ensure that this was a challenging practical problem which also had a direct real world application. To be able to estimate in realtime the probability of fill for tens of thousands of orders at multiple price levels in a liquidity fragmented market place and finally carry out an optimization procedure to find the most optimal order placement solution is a significant computational breakthrough. Copyright Springer Science+Business Media New York 2015

Suggested Citation

  • Miles Kumaresan & Nataša Krejić, 2015. "Optimal trading of algorithmic orders in a liquidity fragmented market place," Annals of Operations Research, Springer, vol. 229(1), pages 521-540, June.
  • Handle: RePEc:spr:annopr:v:229:y:2015:i:1:p:521-540:10.1007/s10479-015-1815-7
    DOI: 10.1007/s10479-015-1815-7
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1007/s10479-015-1815-7
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1007/s10479-015-1815-7?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Jean-Philippe Bouchaud & Yuval Gefen & Marc Potters & Matthieu Wyart, 2004. "Fluctuations and response in financial markets: the subtle nature of 'random' price changes," Quantitative Finance, Taylor & Francis Journals, vol. 4(2), pages 176-190.
    2. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, vol. 2(2), pages 99-134, May.
    3. Marco Avellaneda & Sasha Stoikov, 2008. "High-frequency trading in a limit order book," Quantitative Finance, Taylor & Francis Journals, vol. 8(3), pages 217-224.
    4. Edward Sun & Timm Kruse & Min-Teh Yu, 2014. "High frequency trading, liquidity, and execution cost," Annals of Operations Research, Springer, vol. 223(1), pages 403-432, December.
    5. Miles Kumaresan & Nataša Krejić, 2010. "A model for optimal execution of atomic orders," Computational Optimization and Applications, Springer, vol. 46(2), pages 369-389, June.
    6. 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.
    7. 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.
    8. Fabrizio Lillo & J. Doyne Farmer & Rosario N. Mantegna, 2003. "Master curve for price-impact function," Nature, Nature, vol. 421(6919), pages 129-130, January.
    9. Seppi, Duane J, 1997. "Liquidity Provision with Limit Orders and a Strategic Specialist," The Review of Financial Studies, Society for Financial Studies, vol. 10(1), pages 103-150.
    10. 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.
    11. Thangaraj Draviam & Thomas Coleman & Yuying Li, 2011. "Dynamic liquidation under market impact," Quantitative Finance, Taylor & Francis Journals, vol. 11(1), pages 69-80.
    12. Robert Almgren, 2003. "Optimal execution with nonlinear impact functions and trading-enhanced risk," Applied Mathematical Finance, Taylor & Francis Journals, vol. 10(1), pages 1-18.
    13. Gençay, Ramazan & Dacorogna, Michel & Muller, Ulrich A. & Pictet, Olivier & Olsen, Richard, 2001. "An Introduction to High-Frequency Finance," Elsevier Monographs, Elsevier, edition 1, number 9780122796715.
    14. repec:bla:jfinan:v:43:y:1988:i:1:p:97-112 is not listed on IDEAS
    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. Viktor Manahov, 2018. "The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming," Annals of Operations Research, Springer, vol. 260(1), pages 321-352, January.

    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. 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.
    2. Olivier Guéant, 2016. "The Financial Mathematics of Market Liquidity: From Optimal Execution to Market Making," Post-Print hal-01393136, HAL.
    3. 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.
    4. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    5. Kashyap, Ravi, 2020. "David vs Goliath (You against the Markets), A dynamic programming approach to separate the impact and timing of trading costs," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 545(C).
    6. Frank McGroarty & Ash Booth & Enrico Gerding & V. L. Raju Chinthalapati, 2019. "High frequency trading strategies, market fragility and price spikes: an agent based model perspective," Annals of Operations Research, Springer, vol. 282(1), pages 217-244, November.
    7. Cebiroglu, Gökhan & Hautsch, Nikolaus & Walsh, Christopher, 2019. "Revisiting the stealth trading hypothesis: Does time-varying liquidity explain the size-effect?," CFS Working Paper Series 625, Center for Financial Studies (CFS).
    8. Aurélien Alfonsi & Pierre Blanc, 2016. "Dynamic optimal execution in a mixed-market-impact Hawkes price model," Post-Print hal-00971369, HAL.
    9. Cebiroğlu, Gökhan & Horst, Ulrich, 2011. "Optimal display of Iceberg orders," SFB 649 Discussion Papers 2011-057, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    10. Qinghua Li, 2014. "Facilitation and Internalization Optimal Strategy in a Multilateral Trading Context," Papers 1404.7320, arXiv.org, revised Jan 2015.
    11. Nico Achtsis & Dirk Nuyens, 2013. "A Monte Carlo method for optimal portfolio executions," Papers 1312.5919, arXiv.org.
    12. 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.
    13. Edward W. Sun & Timm Kruse & Yi-Ting Chen, 2019. "Stylized algorithmic trading: satisfying the predictive near-term demand of liquidity," Annals of Operations Research, Springer, vol. 281(1), pages 315-347, October.
    14. 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.
    15. S. C. P. Yam & W. Zhou, 2017. "Optimal Liquidation of Child Limit Orders," Mathematics of Operations Research, INFORMS, vol. 42(2), pages 517-545, May.
    16. Miles Kumaresan & Nataša Krejić, 2010. "A model for optimal execution of atomic orders," Computational Optimization and Applications, Springer, vol. 46(2), pages 369-389, June.
    17. repec:dau:papers:123456789/7391 is not listed on IDEAS
    18. Cattivelli, Luca & Pirino, Davide, 2019. "A SHARP model of bid–ask spread forecasts," International Journal of Forecasting, Elsevier, vol. 35(4), pages 1211-1225.
    19. 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).
    20. 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.

    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:spr:annopr:v:229:y:2015:i:1:p:521-540:10.1007/s10479-015-1815-7. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.