IDEAS home Printed from https://ideas.repec.org/p/arx/papers/1909.09495.html
   My bibliography  Save this paper

CME Iceberg Order Detection and Prediction

Author

Listed:
  • Dmitry Zotikov
  • Anton Antonov

Abstract

We propose a method for detection and prediction of native and synthetic iceberg orders on Chicago Mercantile Exchange. Native (managed by the exchange) icebergs are detected using discrepancies between the resting volume of an order and the actual trade size as indicated by trade summary messages, as well as by tracking order modifications that follow trade events. Synthetic (managed by market participants) icebergs are detected by observing limit orders arriving within a short time frame after a trade. The obtained icebergs are then used to train a model based on the Kaplan--Meier estimator, accounting for orders that were cancelled after a partial execution. The model is utilized to predict the total size of newly detected icebergs. Out of sample validation is performed on the full order depth data, performance metrics and quantitative estimates of hidden volume are presented.

Suggested Citation

  • Dmitry Zotikov & Anton Antonov, 2019. "CME Iceberg Order Detection and Prediction," Papers 1909.09495, arXiv.org.
    • Handle: RePEc:arx:papers:1909.09495
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/1909.09495
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Fleming, Michael J. & Mizrach, Bruce & Nguyen, Giang, 2018. "The microstructure of a U.S. Treasury ECN: The BrokerTec platform," Journal of Financial Markets, Elsevier, vol. 40(C), pages 2-22.
    2. Stefan Frey & Patrik Sandås, 2017. "The Impact of Iceberg Orders in Limit Order Books," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 7(03), pages 1-43, September.
    Full references (including those not matched with items on IDEAS)

    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. Moinas, Sophie, 2010. "Hidden Limit Orders and Liquidity in Order Driven Markets," TSE Working Papers 10-147, Toulouse School of Economics (TSE).
    2. Darrell Duffie & Michael Fleming & Frank Keane & Claire Nelson & Or Shachar & Peter Van Tassel, 2023. "Dealer capacity and US Treasury market functionality," BIS Working Papers 1138, Bank for International Settlements.
    3. Samuel N. Cohen & Lukasz Szpruch, 2011. "A limit order book model for latency arbitrage," Papers 1110.4811, arXiv.org.
    4. Comerton-Forde, Carole & Grégoire, Vincent & Zhong, Zhuo, 2019. "Inverted fee structures, tick size, and market quality," Journal of Financial Economics, Elsevier, vol. 134(1), pages 141-164.
    5. Gabor Pinter & Chaojun Wang & Junyuan Zou, 2024. "Size Discount and Size Penalty: Trading Costs in Bond Markets," The Review of Financial Studies, Society for Financial Studies, vol. 37(7), pages 2156-2190.
    6. Frey, Stefan & Sandås, Patrik, 2009. "The impact of iceberg orders in limit order books," CFR Working Papers 09-06, University of Cologne, Centre for Financial Research (CFR).
    7. Jacobs, Kris & Mai, Anh Thu, 2024. "The role of intermediaries in derivatives markets: Evidence from VIX options," Journal of Empirical Finance, Elsevier, vol. 77(C).
    8. Lin, Hai & Lo, Ingrid & Qiao, Rui, 2021. "Macroeconomic news announcements and market efficiency: Evidence from the U.S. Treasury market," Journal of Banking & Finance, Elsevier, vol. 133(C).
    9. Quanbiao Shang & Teresa Serra & Philip Garcia & Mindy Mallory, 2021. "Looking under the surface: An analysis of iceberg orders in the U.S. agricultural futures markets," Agricultural Economics, International Association of Agricultural Economists, vol. 52(4), pages 679-699, July.
    10. Onur, Esen & Roberts, John S. & Tuzun, Tugkan, 2023. "Trader positions and aggregate portfolio demand," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    11. Adrian, Tobias & Capponi, Agostino & Fleming, Michael & Vogt, Erik & Zhang, Hongzhong, 2020. "Intraday market making with overnight inventory costs," Journal of Financial Markets, Elsevier, vol. 50(C).
    12. Jens H. E. Christensen & James M. Gillan, 2011. "A model-independent maximum range for the liquidity correction of TIPS yields," Working Paper Series 2011-16, Federal Reserve Bank of San Francisco.
    13. Michael Fleming & Giang Nguyen & Francisco Ruela, 2024. "Tick Size, Competition for Liquidity Provision, and Price Discovery: Evidence from the U.S. Treasury Market," Management Science, INFORMS, vol. 70(1), pages 332-354, January.
    14. Alex Aronovich & Andrew C. Meldrum, 2021. "High-Frequency Estimates of the Natural Real Rate and Inflation Expectations," Finance and Economics Discussion Series 2021-034, Board of Governors of the Federal Reserve System (U.S.).
    15. Fabienne Schneider, 2024. "On-the-run Premia, Settlement Fails, and Central Bank Access," Working Papers 24.05, Swiss National Bank, Study Center Gerzensee.
    16. Lien, Donald & Hung, Pi-Hsia & Lin, Zong-Wei, 2020. "Whose trades move stock prices? Evidence from the Taiwan Stock Exchange," International Review of Economics & Finance, Elsevier, vol. 66(C), pages 25-50.
    17. Indriawan, Ivan & Jiao, Feng & Tse, Yiuman, 2021. "The FOMC announcement returns on long-term US and German bond futures," Journal of Banking & Finance, Elsevier, vol. 123(C).
    18. Joel Hasbrouck, 2021. "Rejoinder on: Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 465-471.
    19. William Dudley & Michelle Steinberg Ezer & Jennifer E. Roush, 2009. "The case for TIPS: an examination of the costs and benefits," Economic Policy Review, Federal Reserve Bank of New York, vol. 15(Jul), pages 1-17.
    20. Hautsch, Nikolaus & Huang, Ruihong, 2012. "On the dark side of the market: Identifying and analyzing hidden order placements," CFS Working Paper Series 2012/04, Center for Financial Studies (CFS).

    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:1909.09495. 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.