IDEAS home Printed from https://ideas.repec.org/a/eee/dyncon/v134y2022ics0165188921002220.html
   My bibliography  Save this article

Order scoring, bandit learning and order cancellations

Author

Listed:
  • Gao, Xuefeng
  • Xu, Tianrun

Abstract

This paper develops an order scoring model that quantifies the performance of a limit order before execution. Our dynamic stochastic model takes into account of the bid-ask queue imbalance, the queue position of an order and price dynamics. We calibrate and validate the model using the historical order book data and backtesting simulations, and show that our model can perform well empirically. We also combine our model with multi-armed bandit learning to guide order cancellation decisions. We illustrate the empirical performances of various bandit algorithms and show that the Upper Confidence Bound algorithm generally performs the best.

Suggested Citation

  • Gao, Xuefeng & Xu, Tianrun, 2022. "Order scoring, bandit learning and order cancellations," Journal of Economic Dynamics and Control, Elsevier, vol. 134(C).
    • Handle: RePEc:eee:dyncon:v:134:y:2022:i:c:s0165188921002220
    DOI: 10.1016/j.jedc.2021.104287
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0165188921002220
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.jedc.2021.104287?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. Rama Cont & Sasha Stoikov & Rishi Talreja, 2010. "A Stochastic Model for Order Book Dynamics," Operations Research, INFORMS, vol. 58(3), pages 549-563, June.
    2. Sasha Stoikov, 2018. "The micro-price: a high-frequency estimator of future prices," Quantitative Finance, Taylor & Francis Journals, vol. 18(12), pages 1959-1966, December.
    3. Lo, Andrew W. & MacKinlay, A. Craig & Zhang, June, 2002. "Econometric models of limit-order executions," Journal of Financial Economics, Elsevier, vol. 65(1), pages 31-71, July.
    4. Nicholas T. Chan and Christian Shelton, 2001. "An Adaptive Electronic Market-Maker," Computing in Economics and Finance 2001 146, Society for Computational Economics.
    5. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    6. Ryan Donnelly & Luhui Gan, 2018. "Optimal Decisions in a Time Priority Queue," Applied Mathematical Finance, Taylor & Francis Journals, vol. 25(2), pages 107-147, March.
    7. Rama Cont & Adrien de Larrard, 2013. "Price Dynamics in a Markovian Limit Order Market," Post-Print hal-00552252, HAL.
    8. Cebiroğlu, Gökhan & Horst, Ulrich, 2015. "Optimal order display in limit order markets with liquidity competition," Journal of Economic Dynamics and Control, Elsevier, vol. 58(C), pages 81-100.
    9. Álvaro Cartea & Ryan Donnelly & Sebastian Jaimungal, 2018. "Enhancing trading strategies with order book signals," Applied Mathematical Finance, Taylor & Francis Journals, vol. 25(1), pages 1-35, January.
    10. Jim Gatheral & Roel Oomen, 2010. "Zero-intelligence realized variance estimation," Finance and Stochastics, Springer, vol. 14(2), pages 249-283, April.
    11. Justin A. Sirignano, 2019. "Deep learning for limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 19(4), pages 549-570, April.
    12. Avanidhar Subrahmanyam & Hui Zheng, 2016. "Limit order placement by high-frequency traders," Borsa Istanbul Review, Research and Business Development Department, Borsa Istanbul, vol. 16(4), pages 185-209, December.
    13. Chen Yao & Mao Ye, 2018. "Why Trading Speed Matters: A Tale of Queue Rationing under Price Controls," The Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2157-2183.
    14. 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.
    15. Xuefeng Gao & Yunhan Wang, 2020. "Optimal market making in the presence of latency," Quantitative Finance, Taylor & Francis Journals, vol. 20(9), pages 1495-1512, September.
    16. �lvaro Cartea & Sebastian Jaimungal, 2013. "Modelling Asset Prices for Algorithmic and High-Frequency Trading," Applied Mathematical Finance, Taylor & Francis Journals, vol. 20(6), pages 512-547, December.
    17. Xuefeng Gao & Yunhan Wang, 2018. "Optimal Market Making in the Presence of Latency," Papers 1806.05849, arXiv.org, revised Mar 2020.
    18. Thomas Spooner & John Fearnley & Rahul Savani & Andreas Koukorinis, 2018. "Market Making via Reinforcement Learning," Papers 1804.04216, arXiv.org.
    19. 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.
    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. Long, Yunshen & Yan, Jingzhou & Wu, Liang & Long, Xingchen, 2024. "Market price determination: Interpreting quote order imbalance under zero-profit equilibrium," Economic Modelling, Elsevier, vol. 134(C).

    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. Joseph Jerome & Leandro Sanchez-Betancourt & Rahul Savani & Martin Herdegen, 2022. "Model-based gym environments for limit order book trading," Papers 2209.07823, arXiv.org.
    2. 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.
    3. Antonio Briola & Silvia Bartolucci & Tomaso Aste, 2024. "Deep Limit Order Book Forecasting," Papers 2403.09267, arXiv.org, revised Jun 2024.
    4. 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.
    5. Federico Gonzalez & Mark Schervish, 2017. "Instantaneous order impact and high-frequency strategy optimization in limit order books," Papers 1707.01167, arXiv.org, revised Oct 2017.
    6. Jiafa He & Cong Zheng & Can Yang, 2023. "Integrating Tick-level Data and Periodical Signal for High-frequency Market Making," Papers 2306.17179, arXiv.org.
    7. 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.
    8. Philippe Bergault & Olivier Gu'eant, 2023. "Liquidity Dynamics in RFQ Markets and Impact on Pricing," Papers 2309.04216, arXiv.org, revised Jun 2024.
    9. Zijian Shi & John Cartlidge, 2024. "Neural stochastic agent‐based limit order book simulation with neural point process and diffusion probabilistic model," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 31(2), June.
    10. Jonathan A. Chávez Casillas, 2024. "A Time-Dependent Markovian Model of a Limit Order Book," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 679-709, February.
    11. Lee, Kyungsub & Seo, Byoung Ki, 2017. "Marked Hawkes process modeling of price dynamics and volatility estimation," Journal of Empirical Finance, Elsevier, vol. 40(C), pages 174-200.
    12. Hong Guo & Jianwu Lin & Fanlin Huang, 2023. "Market Making with Deep Reinforcement Learning from Limit Order Books," Papers 2305.15821, arXiv.org.
    13. Johannes Bleher & Michael Bleher & Thomas Dimpfl, 2020. "From orders to prices: A stochastic description of the limit order book to forecast intraday returns," Papers 2004.11953, arXiv.org, revised May 2021.
    14. Hagströmer, Björn, 2021. "Bias in the effective bid-ask spread," Journal of Financial Economics, Elsevier, vol. 142(1), pages 314-337.
    15. 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.
    16. Frédéric Abergel & Aymen Jedidi, 2015. "Long-Time Behavior of a Hawkes Process--Based Limit Order Book," Post-Print hal-01121711, HAL.
    17. Zoltan Eisler & Janos Kertesz & Fabrizio Lillo & Rosario Mantegna, 2009. "Diffusive behavior and the modeling of characteristic times in limit order executions," Quantitative Finance, Taylor & Francis Journals, vol. 9(5), pages 547-563.
    18. Alvaro Arroyo & Alvaro Cartea & Fernando Moreno-Pino & Stefan Zohren, 2023. "Deep Attentive Survival Analysis in Limit Order Books: Estimating Fill Probabilities with Convolutional-Transformers," Papers 2306.05479, arXiv.org.
    19. Rama Cont & Marvin S. Mueller, 2019. "A stochastic partial differential equation model for limit order book dynamics," Papers 1904.03058, arXiv.org, revised May 2021.
    20. Kyungsub Lee & Byoung Ki Seo, 2021. "Analytic formula for option margin with liquidity costs under dynamic delta hedging," Papers 2103.15302, arXiv.org.

    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:eee:dyncon:v:134:y:2022:i:c:s0165188921002220. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jedc .

    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.