IDEAS home Printed from https://ideas.repec.org/p/arx/papers/2211.06046.html
   My bibliography  Save this paper

Are Large Traders Harmed by Front-running HFTs?

Author

Listed:
  • Ziyi Xu
  • Xue Cheng

Abstract

This paper studies the influences of a high-frequency trader (HFT) on a large trader whose future trading is predicted by the former. We conclude that HFT always front-runs and the large trader is benefited when: (1) there is sufficient high-speed noise trading; (2) HFT's prediction is vague enough. Besides, we find surprisingly that (1) making HFT's prediction less accurate might decrease large trader's profit; (2) when there is little high-speed noise trading, although HFT nearly does nothing, the large trader is still hurt.

Suggested Citation

  • Ziyi Xu & Xue Cheng, 2022. "Are Large Traders Harmed by Front-running HFTs?," Papers 2211.06046, arXiv.org, revised Jul 2023.
  • Handle: RePEc:arx:papers:2211.06046
    as

    Download full text from publisher

    File URL: http://arxiv.org/pdf/2211.06046
    File Function: Latest version
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows," Review of Finance, European Finance Association, vol. 33(4), pages 1484-1533.
    2. Bernhardt, Dan & Taub, Bart, 2008. "Front-running dynamics," Journal of Economic Theory, Elsevier, vol. 138(1), pages 288-296, January.
    3. Michael Goldstein & Jonathan Brogaard & Terrence Hendershott & Stefan Hunt & Carla Ysusi, 2014. "High-Frequency Trading and the Execution Costs of Institutional Investors," The Financial Review, Eastern Finance Association, vol. 49(2), pages 345-369, May.
    4. Thorsten Hens & Terje Lensberg & Klaus Reiner Schenk‐Hoppé, 2018. "Front‐Running and Market Quality: An Evolutionary Perspective on High Frequency Trading," International Review of Finance, International Review of Finance Ltd., vol. 18(4), pages 727-741, December.
    5. Viktor Manahov, 2016. "Front-Running Scalping Strategies and Market Manipulation: Why Does High-Frequency Trading Need Stricter Regulation?," The Financial Review, Eastern Finance Association, vol. 51(3), pages 363-402, August.
    6. Albert J. Menkveld, 2016. "The Economics of High-Frequency Trading: Taking Stock," Annual Review of Financial Economics, Annual Reviews, vol. 8(1), pages 1-24, October.
    7. Bessembinder, Hendrik & Carrion, Allen & Tuttle, Laura & Venkataraman, Kumar, 2016. "Liquidity, resiliency and market quality around predictable trades: Theory and evidence," Journal of Financial Economics, Elsevier, vol. 121(1), pages 142-166.
    8. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    9. Liyan Yang & Haoxiang Zhu, 2020. "Back-Running: Seeking and Hiding Fundamental Information in Order Flows," The Review of Financial Studies, Society for Financial Studies, vol. 33(4), pages 1484-1533.
    10. Markus Baldauf & Joshua Mollner, 2020. "High‐Frequency Trading and Market Performance," Journal of Finance, American Finance Association, vol. 75(3), pages 1495-1526, June.
    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. Ziyi Xu & Xue Cheng, 2023. "The Effects of High-frequency Anticipatory Trading: Small Informed Trader vs. Round-Tripper," Papers 2304.13985, arXiv.org, revised Feb 2024.
    2. Sagade, Satchit & Scharnowski, Stefan & Westheide, Christian, 2022. "Broker colocation and the execution costs of customer and proprietary orders," SAFE Working Paper Series 366, Leibniz Institute for Financial Research SAFE.
    3. Ziyi Xu & Xue Cheng, 2024. "Trading Large Orders in the Presence of Multiple High-Frequency Anticipatory Traders," Papers 2403.08202, arXiv.org.
    4. Xu, Ke, 2023. "High frequency market making during stressed periods," International Review of Economics & Finance, Elsevier, vol. 87(C), pages 379-397.
    5. Li, Sida & Ye, Mao & Zheng, Miles, 2023. "Refusing the best price?," Journal of Financial Economics, Elsevier, vol. 147(2), pages 317-337.
    6. Ye, Mao & Zheng, Miles Y. & Zhu, Wei, 2023. "The effect of tick size on managerial learning from stock prices," Journal of Accounting and Economics, Elsevier, vol. 75(1).
    7. Bongaerts, Dion & Achter, Mark Van, 2021. "Competition among liquidity providers with access to high-frequency trading technology," Journal of Financial Economics, Elsevier, vol. 140(1), pages 220-249.
    8. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    9. Corey Garriot & Ryan Riordan, 2020. "Trading on Long-term Information," Staff Working Papers 20-20, Bank of Canada.
    10. Han, Jinhui & Li, Xiaolong & Ma, Guiyuan & Kennedy, Adrian Patrick, 2023. "Strategic trading with information acquisition and long-memory stochastic liquidity," European Journal of Operational Research, Elsevier, vol. 308(1), pages 480-495.
    11. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    12. Mark Marner-Hausen, 2022. "Developing a Framework for Real-Time Trading in a Laboratory Financial Market," ECONtribute Discussion Papers Series 172, University of Bonn and University of Cologne, Germany.
    13. Gider, Jasmin & Schmickler, Simon & Westheide, Christian, 2019. "High-frequency trading and price informativeness," SAFE Working Paper Series 248, Leibniz Institute for Financial Research SAFE, revised 2019.
    14. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    15. Aliyev, Nihad & Huseynov, Fariz & Rzayev, Khaladdin, 2022. "Algorithmic trading and investment-to-price sensitivity," LSE Research Online Documents on Economics 118844, London School of Economics and Political Science, LSE Library.
    16. Huang, Shao’an & Qiu, Zhigang & Wang, Gaowang & Wang, Xiaodan, 2022. "Government intervention through informed trading in financial markets," Journal of Economic Dynamics and Control, Elsevier, vol. 141(C).
    17. Zheng, Jiayi & Zhu, Yushu, 2023. "Algorithmic trading and block ownership initiation: An information perspective," The British Accounting Review, Elsevier, vol. 55(4).
    18. Gong, Aibo & Ke, Shaowei & Qiu, Yawen & Shen, Rui, 2022. "Robust pricing under strategic trading," Journal of Economic Theory, Elsevier, vol. 199(C).
    19. Guo, Qi & Huang, Shao'an & Wang, Gaowang, 2022. "Stabilizing the Financial Markets through Informed Trading," MPRA Paper 115470, University Library of Munich, Germany.
    20. Gu, Dingwei & Liu, Xin & Sun, Hanwen & Zhao, Huainan, 2021. "Strategic insider trading: Disguising order flows to escape trading competition," Journal of Corporate Finance, Elsevier, vol. 67(C).

    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:2211.06046. 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.