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Price discovery and the cross-section of high-frequency trading

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  • Benos, Evangelos
  • Sagade, Satchit

Abstract

We quantify the price discovery contributions of high-frequency traders (HFTs) in the United Kingdom equity market and examine how it varies in their cross-section. For this, we group individual HFTs according to their liquidity taking/making activity. HFTs contribute about 14% of all trade-induced information, with aggressive HFTs accounting for two-thirds of this contribution. This suggests that HFTs who pursue strategies that require the use of aggressive trades are most informed, as opposed to passive HFTs who more likely act as market-makers. However, information shares decline with the amount of aggressive volume, suggesting that these trading strategies are not scalable.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:finmar:v:30:y:2016:i:c:p:54-77
    DOI: 10.1016/j.finmar.2016.03.004
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    References listed on IDEAS

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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. Gianluca Piero Maria Virgilio, 2019. "High-frequency trading: a literature review," Financial Markets and Portfolio Management, Springer;Swiss Society for Financial Market Research, vol. 33(2), pages 183-208, June.
    3. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti & Uno, Jun & Yuferova, Darya, 2017. "Coming early to the party," SAFE Working Paper Series 182, Leibniz Institute for Financial Research SAFE.
      • Mario Bellia & Loriana Pelizzon & Marti G. Subrahmanyam & Jun Uno & Darya Yuferova, 2020. "Coming early to the party," Working Papers 2020:11, Department of Economics, University of Venice "Ca' Foscari".
    4. 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).
    5. Zhou, Hao & Elliott, Robert J. & Kalev, Petko S., 2019. "Information or noise: What does algorithmic trading incorporate into the stock prices?," International Review of Financial Analysis, Elsevier, vol. 63(C), pages 27-39.
    6. Roşu, Ioanid, 2019. "Fast and slow informed trading," Journal of Financial Markets, Elsevier, vol. 43(C), pages 1-30.
    7. Zura Kakushadze & Juan Andrés Serur, 2018. "151 Trading Strategies," Springer Books, Springer, number 978-3-030-02792-6, January.
    8. Yan Chen & Peter Cramton & John List & Axel Ockenfels, 2020. "Market Design, Human Behavior and Management," Artefactual Field Experiments 00685, The Field Experiments Website.
    9. Donald B. Keim & Massimo Massa & Bastian von Beschwitz, 2018. "First to \"Read\" the News: New Analytics and Algorithmic Trading," International Finance Discussion Papers 1233, Board of Governors of the Federal Reserve System (U.S.).
    10. Bizzozero, Paolo & Flepp, Raphael & Franck, Egon, 2018. "The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 126-143.
    11. Alexander, Carol & Heck, Daniel F., 2020. "Price discovery in Bitcoin: The impact of unregulated markets," Journal of Financial Stability, Elsevier, vol. 50(C).
    12. Benos, Evangelos & Brugler, James & Hjalmarsson, Erik & Zikes, Filip, 2017. "Interactions among High-Frequency Traders," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1375-1402, August.
    13. 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.
    14. Tobias Adrian & Agostino Capponi & Michael J. Fleming & Erik Vogt & Hongzhong Zhang, 2016. "Intraday market making with overnight inventory costs," Staff Reports 799, Federal Reserve Bank of New York.
    15. 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.
    16. Ramos, Henrique Pinto & Perlin, Marcelo Scherer, 2020. "Does algorithmic trading harm liquidity? Evidence from Brazil," The North American Journal of Economics and Finance, Elsevier, vol. 54(C).

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    More about this item

    Keywords

    High-frequency trading; Price discovery;

    JEL classification:

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

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