IDEAS home Printed from
   My bibliography  Save this article

High-Frequency Trading and the Execution Costs of Institutional Investors


  • Michael Goldstein
  • Jonathan Brogaard
  • Terrence Hendershott
  • Stefan Hunt
  • Carla Ysusi


This paper studies whether high-frequency trading (HFT) increases the execution costs of institutional investors. We use technology upgrades that lower the latency of the London Stock Exchange to obtain variation in the level of HFT over time. Following upgrades, the level of HFT increases. Around these shocks to HFT institutional traders’ costs remain unchanged. We find no clear evidence that HFT impacts institutional execution costs.

Suggested Citation

  • 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.
  • Handle: RePEc:bla:finrev:v:49:y:2014:i:2:p:345-369

    Download full text from publisher

    File URL:
    Download Restriction: Access to full text is restricted to subscribers.

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


    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.

    Cited by:

    1. 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.
    2. Mestel, Roland & Murg, Michael & Theissen, Erik, 2018. "Algorithmic trading and liquidity: Long term evidence from Austria," Finance Research Letters, Elsevier, vol. 26(C), pages 198-203.
    3. Frino, Alex & Mollica, Vito & Webb, Robert I. & Zhang, Shunquan, 2017. "The impact of latency sensitive trading on high frequency arbitrage opportunities," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 91-102.
    4. Sağlam, Mehmet & Moallemi, Ciamac C. & Sotiropoulos, Michael G., 2019. "Short-term trading skill: An analysis of investor heterogeneity and execution quality," Journal of Financial Markets, Elsevier, vol. 42(C), pages 1-28.
    5. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    6. Benos, Evangelos & Sagade, Satchit, 2016. "Price discovery and the cross-section of high-frequency trading," Journal of Financial Markets, Elsevier, vol. 30(C), pages 54-77.
    7. Gider, Jasmin & Schmickler, Simon & Westheide, Christian, 2019. "High-frequency trading and price informativeness," SAFE Working Paper Series 248, Leibniz Institute for Financial Research SAFE.
    8. John Cotter & Niall McGeever, 2018. "Are equity market anomalies disappearing? Evidence from the U.K," Working Papers 201804, Geary Institute, University College Dublin.
    9. Upson, James & Van Ness, Robert A., 2017. "Multiple markets, algorithmic trading, and market liquidity," Journal of Financial Markets, Elsevier, vol. 32(C), pages 49-68.
    10. Guanqing Liu, 2019. "Technical Trading Behaviour: Evidence from Chinese Rebar Futures Market," Computational Economics, Springer;Society for Computational Economics, vol. 54(2), pages 669-704, August.
    11. Fabio S. Dias & Gareth W. Peters, 2020. "A Non-parametric Test and Predictive Model for Signed Path Dependence," Computational Economics, Springer;Society for Computational Economics, vol. 56(2), pages 461-498, August.
    12. Hu, Gang & Jo, Koren M. & Wang, Yi Alex & Xie, Jing, 2018. "Institutional trading and Abel Noser data," Journal of Corporate Finance, Elsevier, vol. 52(C), pages 143-167.
    13. Efstathios Panayi & Gareth Peters, 2015. "Stochastic simulation framework for the Limit Order Book using liquidity motivated agents," Papers 1501.02447,, revised Jan 2015.
    14. Efstathios Panayi & Gareth W. Peters, 2015. "Stochastic simulation framework for the limit order book using liquidity-motivated agents," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 2(02), pages 1-52.
    15. Sifat, Imtiaz Mohammad & Mohamad, Azhar, 2015. "Order imbalance and selling aggression under a shorting ban: Evidence from the UK," International Review of Financial Analysis, Elsevier, vol. 42(C), pages 368-379.
    16. Manahov, Viktor, 2016. "A note on the relationship between high-frequency trading and latency arbitrage," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 281-296.

    More about this item


    Access and download statistics


    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:bla:finrev:v:49:y:2014:i:2:p:345-369. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (Wiley Content Delivery). General contact details of provider: .

    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.

    We have no references for this item. You can help adding them by using 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.

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.