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Algorithmic Trading and Market Quality: International Evidence

Author

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  • Boehmer, Ekkehart
  • Fong, Kingsley
  • Wu, Juan (Julie)

Abstract

We study the effect of algorithmic trading (AT) on market quality between 2001 and 2011 in 42 equity markets around the world. We use an exchange colocation service that increases AT as an exogenous instrument to draw causal inferences about AT on market quality. On average, AT improves liquidity and informational efficiency but increases short-term volatility. Importantly, AT also lowers execution shortfalls for buy-side institutional investors. Our results are surprisingly consistent across markets and thus across a wide range of AT environments. We further document that the beneficial effect of AT is stronger in large stocks than in small stocks.

Suggested Citation

  • Boehmer, Ekkehart & Fong, Kingsley & Wu, Juan (Julie), 2021. "Algorithmic Trading and Market Quality: International Evidence," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 56(8), pages 2659-2688, December.
    • Handle: RePEc:cup:jfinqa:v:56:y:2021:i:8:p:2659-2688_3
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    Citations

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    Cited by:

    1. Ben R. Marshall & Nhut H. Nguyen & Nuttawat Visaltanachoti & Jennifer Zhu, 2025. "Broker and institutional investor short selling," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 65(1), pages 621-645, March.
    2. Servanna Mianjun Fu & Christos Alexakis & Vasileios Pappas & Emmanouil Skarmeas & Thanos Verousis, 2026. "Does Algorithmic Trading Induce Herding?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 31(1), pages 1186-1202, January.
    3. Nag, Arindam, 2026. "Liquidity at the Speed of AI: Algorithmic Trading and Systemic Risk Amplification," MPRA Paper 128853, University Library of Munich, Germany.
    4. Brugler, James & Comerton-Forde, Carole, 2025. "Differential access to dark markets and execution outcomes," Journal of Financial Economics, Elsevier, vol. 171(C).
    5. Breckenfelder, Johannes, 2024. "Competition among high-frequency traders and market quality," Journal of Economic Dynamics and Control, Elsevier, vol. 166(C).
    6. John Paul Broussard & Andrei Nikiforov & Sergey Osmekhin, 2025. "The market ecosystem in the age of algorithms: An analysis of trading dynamics and market quality," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 49(2), pages 343-363, June.
    7. Nitika Sharma & Sridhar Manohar & Arjun J. Nair & A. B. Satish Rao, 2025. "Market microstructure to enhance sustainable investment decision and asset growth through financial literacy," Journal of Innovation and Entrepreneurship, Springer, vol. 14(1), pages 1-20, December.
    8. Christophe Desagre & Floris Laly & Mikael Petitjean, 2025. "Revisiting the trading activity of high-frequency trading firms around ultra-fast flash events," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-37, December.
    9. Zefeng Chen & Darcy Pu, 2026. "Autonomous Market Intelligence: Agentic AI Nowcasting Predicts Stock Returns," Papers 2601.11958, arXiv.org.
    10. Jacob-Leal, Sandrine & Hanaki, Nobuyuki, 2024. "Algorithmic trading, what if it is just an illusion? Evidence from experimental asset markets," Journal of Behavioral and Experimental Economics (formerly The Journal of Socio-Economics), Elsevier, vol. 112(C).
    11. Zhang, Jiang, 2025. "International information flow and market quality," Journal of Banking & Finance, Elsevier, vol. 173(C).

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