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Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures

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  • Karkowska, Renata
  • Palczewski, Andrzej

Abstract

The increasing volume of messages sent to the exchange by algorithmic traders stimulates a fierce debate among academics and practitioners on the impacts of high-frequency trading (HFT) on capital markets. By comparing a variety of regression models that associate various measures of market liquidity with measures of high-frequency activity on the same dataset, we find that for some models the increase in high-frequency activity improves market liquidity, but for others, we get the opposite effect. We indicate that this ambiguity does not depend only on the stock market or the data period, but also on the used HFT measure: the increase of high-frequency orders leads to lower market liquidity whereas the increase in high-frequency trades improves liquidity. We hypothesize that the observed decrease in market liquidity associated with an increasing level of high-frequency orders is caused by a rise in quote volatility.

Suggested Citation

  • Karkowska, Renata & Palczewski, Andrzej, 2023. "Does high-frequency trading actually improve market liquidity? A comparative study for selected models and measures," Research in International Business and Finance, Elsevier, vol. 64(C).
    • Handle: RePEc:eee:riibaf:v:64:y:2023:i:c:s0275531922002586
    DOI: 10.1016/j.ribaf.2022.101872
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    References listed on IDEAS

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    1. Panagiotis Anagnostidis & Patrice Fontaine, 2020. "Liquidity commonality and high frequency trading: Evidence from the French stock market," Post-Print hal-03061863, HAL.
    2. Ladley, Daniel, 2020. "The high frequency trade off between speed and sophistication," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).
    3. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti G. & Uno, Jun & Yuferova, Darya, 2017. "Low-latency trading and price discovery: Evidence from the Tokyo Stock Exchange in the pre-opening and opening periods," SAFE Working Paper Series 144, Leibniz Institute for Financial Research SAFE, revised 2017.
    4. Michael J. Aitken & Angelo Aspris & Sean Foley & Frederick H. de B. Harris, 2018. "Market Fairness: The Poor Country Cousin of Market Efficiency," Journal of Business Ethics, Springer, vol. 147(1), pages 5-23, January.
    5. Anagnostidis, Panagiotis & Fontaine, Patrice, 2020. "Liquidity commonality and high frequency trading: Evidence from the French stock market," International Review of Financial Analysis, Elsevier, vol. 69(C).
    6. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    7. Christophe Desagre & Catherine D’Hondt & Mikael Petitjean, 2022. "The rise of fast trading: Curse or blessing for liquidity?," Finance, Presses universitaires de Grenoble, vol. 43(3), pages 119-158.
    8. Biais, Bruno & Foucault, Thierry & Moinas, Sophie, 2015. "Equilibrium fast trading," Journal of Financial Economics, Elsevier, vol. 116(2), pages 292-313.
    9. Hendershott, Terrence & Riordan, Ryan, 2013. "Algorithmic Trading and the Market for Liquidity," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 48(4), pages 1001-1024, August.
    10. Blundell, Richard & Bond, Stephen, 1998. "Initial conditions and moment restrictions in dynamic panel data models," Journal of Econometrics, Elsevier, vol. 87(1), pages 115-143, August.
    11. Panagiotis Anagnostidis & Patrice Fontaine, 2020. "Liquidity commonality and high frequency trading: Evidence from the French stock market," Post-Print hal-03062612, HAL.
    12. Hasbrouck, Joel, 2018. "High-Frequency Quoting: Short-Term Volatility in Bids and Offers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 613-641, April.
    13. Ben Ammar, Imen & Hellara, Slaheddine & Ghadhab, Imen, 2020. "High-frequency trading and stock liquidity: An intraday analysis," Research in International Business and Finance, Elsevier, vol. 53(C).
    14. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    15. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," The Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    16. Álvaro Cartea & José Penalva, 2012. "Where is the Value in High Frequency Trading?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 2(03), pages 1-46.
    17. Michael Goldstein & Elvis Jarnecic & Mark Snape, 2014. "The Provision of Liquidity by High-Frequency Participants," The Financial Review, Eastern Finance Association, vol. 49(2), pages 371-394, May.
    18. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    19. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    20. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    21. Conrad, Jennifer & Wahal, Sunil & Xiang, Jin, 2015. "High-frequency quoting, trading, and the efficiency of prices," Journal of Financial Economics, Elsevier, vol. 116(2), pages 271-291.
    22. Dubey, Ritesh Kumar & Chauhan, Yogesh & Syamala, Sudhakara Reddy, 2017. "Evidence of algorithmic trading from Indian equity market: Interpreting the transaction velocity element of financialization," Research in International Business and Finance, Elsevier, vol. 42(C), pages 31-38.
    23. Ekinci, Cumhur & Ersan, Oğuz, 2022. "High-frequency trading and market quality: The case of a “slightly exposed” market," International Review of Financial Analysis, Elsevier, vol. 79(C).
    24. Alex Frino & Vito Mollica & Robert I. Webb, 2014. "The Impact of Co‐Location of Securities Exchanges' and Traders' Computer Servers on Market Liquidity," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 34(1), pages 20-33, January.
    25. Ekinci, Cumhur & Ersan, Oguz, 2018. "A new approach for detecting high-frequency trading from order and trade data," Finance Research Letters, Elsevier, vol. 24(C), pages 313-320.
    26. Archana Jain & Chinmay Jain & Revansiddha Basavaraj Khanapure, 2021. "Do Algorithmic Traders Improve Liquidity When Information Asymmetry is High?," Quarterly Journal of Finance (QJF), World Scientific Publishing Co. Pte. Ltd., vol. 11(01), pages 1-32, March.
    27. Bonnie F. Van Ness & Robert A. Van Ness & Ethan D. Watson, 2015. "Canceling Liquidity," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 38(1), pages 3-33, March.
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    More about this item

    Keywords

    High-frequency trading; Liquidity; Algorithmic trading; Market microstructure;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors

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