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Risk and Return in High-Frequency Trading

Author

Listed:
  • Matthew Baron

    () (University of Warwick)

  • Björn Hagströmer

    () (Stockholm University)

  • Andrei Kirilenko

    () (Imperial College London)

Abstract

We study performance and competition among high-frequency traders (HFTs). We construct measures of latency and find that differences in relative latency account for large differences in HFTs’ trading performance. HFTs that improve their latency rank due to colocation upgrades see improved trading performance. The stronger performance associated with speed comes through both the short-lived information channel and the risk management channel, and speed is useful for various strategies including market making and cross-market arbitrage. We find empirical support for many predictions regarding relative latency competition.

Suggested Citation

  • Matthew Baron & Björn Hagströmer & Andrei Kirilenko, 2017. "Risk and Return in High-Frequency Trading," GRU Working Paper Series GRU_2017_018, City University of Hong Kong, Department of Economics and Finance, Global Research Unit.
  • Handle: RePEc:cth:wpaper:gru_2017_018
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    File URL: https://www.cb.cityu.edu.hk/ef/doc/GRU/WPS/GRU%232017-018%20Baron%20et%20al.pdf
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    Citations

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    Cited by:

    1. Bastian von Beschwitz & Donald B Keim & Massimo Massa, 2020. "First to “Read” the News: News Analytics and Algorithmic Trading," Review of Asset Pricing Studies, Oxford University Press, vol. 10(1), pages 122-178.
    2. Chen, Marie & Garriott, Corey, 2020. "High-frequency trading and institutional trading costs," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 74-93.
    3. Roşu, Ioanid, 2019. "Fast and slow informed trading," Journal of Financial Markets, Elsevier, vol. 43(C), pages 1-30.
    4. Michael Brolley & Marius Zoican, 2019. "Liquid Speed: On-Demand Fast Trading at Distributed Exchanges," Papers 1907.10720, arXiv.org.
    5. Jurich, Stephen N. & Mishra, Ajay Kumar & Parikh, Bhavik, 2020. "Indecisive algos: Do limit order revisions increase market load?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 28(C).
    6. Rajiv Sethi & Julie Seager & Emily Cai & Daniel M. Benjamin & Fred Morstatter, 2021. "Models, Markets, and the Forecasting of Elections," Papers 2102.04936, arXiv.org, revised Mar 2021.
    7. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.

    More about this item

    Keywords

    high-frequency trading; low latency; market microstructure;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G19 - Financial Economics - - General Financial Markets - - - Other

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