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Does high-frequency trading increase systemic risk?

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  • Jain, Pankaj K.
  • Jain, Pawan
  • McInish, Thomas H.

Abstract

In 2010, the Tokyo Stock Exchange, the largest stock exchange headquartered outside of the United States, introduced a new trading platform, Arrowhead. This platform reduced latency and increased co-located, high-frequency quoting and trading (HFQ) from zero to 36% of trading volume. During tail events representing extreme market conditions, low-latency correlated HFQ may lead to systemic risks such as flash crashes, which has not been sufficiently addressed in the literature. In this paper, our study provides a framework to assess whether HFQ increases systemic risks and points to the need for incorporating correlations and CoVaR methods in regulating these risks through circuit breakers and other regulations.

Suggested Citation

  • Jain, Pankaj K. & Jain, Pawan & McInish, Thomas H., 2016. "Does high-frequency trading increase systemic risk?," Journal of Financial Markets, Elsevier, vol. 31(C), pages 1-24.
  • Handle: RePEc:eee:finmar:v:31:y:2016:i:c:p:1-24
    DOI: 10.1016/j.finmar.2016.09.004
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    2. Turiel, Jeremy D. & Aste, Tomaso, 2022. "Heterogeneous criticality in high frequency finance: a phase transition in flash crashes," LSE Research Online Documents on Economics 113892, London School of Economics and Political Science, LSE Library.
    3. Arumugam, Devika & Prasanna, P. Krishna & Marathe, Rahul R., 2023. "Do algorithmic traders exploit volatility?," Journal of Behavioral and Experimental Finance, Elsevier, vol. 37(C).
    4. Murinde, Victor & Rizopoulos, Efthymios & Zachariadis, Markos, 2022. "The impact of the FinTech revolution on the future of banking: Opportunities and risks," International Review of Financial Analysis, Elsevier, vol. 81(C).
    5. Li, Mingyi & Yin, Xiangkang & Zhao, Jing, 2020. "Does program trading contribute to excess comovement of stock returns?," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 257-277.
    6. Marcus Buckmann & Andy Haldane & Anne-Caroline Hüser, 2021. "Comparing minds and machines: implications for financial stability," Oxford Review of Economic Policy, Oxford University Press and Oxford Review of Economic Policy Limited, vol. 37(3), pages 479-508.
    7. Andrea Roncella & Ignacio Ferrero, 2022. "The Ethics of Financial Market Making and Its Implications for High-Frequency Trading," Journal of Business Ethics, Springer, vol. 181(1), pages 139-151, November.
    8. Fabrice Rousseau & Herve Boco & Laurent Germain, 2020. "High Frequency Trading: Strategic Competition Between Slow and Fast Traders," Economics Department Working Paper Series n296-20.pdf, Department of Economics, National University of Ireland - Maynooth.
    9. Hyun Jin Jang & Kiseop Lee & Kyungsub Lee, 2020. "Systemic risk in market microstructure of crude oil and gasoline futures prices: A Hawkes flocking model approach," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(2), pages 247-275, February.
    10. Yang, Haijun & Ge, Hengshun & Luo, Ying, 2020. "The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity," Research in International Business and Finance, Elsevier, vol. 53(C).
    11. Tian, Xiao & Duong, Huu Nhan & Kalev, Petko S., 2019. "Information content of the limit order book for crude oil futures price volatility," Energy Economics, Elsevier, vol. 81(C), pages 584-597.
    12. 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).
    13. Cox, Justin S., 2022. "The impact of reporting changes on hidden liquidity: Evidence from the Chicago stock exchange," Global Finance Journal, Elsevier, vol. 53(C).
    14. Kemme, David M. & McInish, Thomas H. & Zhang, Jiang, 2022. "Market fairness and efficiency: Evidence from the Tokyo Stock Exchange," Journal of Banking & Finance, Elsevier, vol. 134(C).
    15. Richard Mawulawoe Ahadzie & Nagaratnam Jeyasreedharan, 2024. "Higher‐order moments and asset pricing in the Australian stock market," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 75-128, March.
    16. Dungey, Mardi & Matei, Marius & Treepongkaruna, Sirimon, 2020. "Examining stress in Asian currencies: A perspective offered by high frequency financial market data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 67(C).
    17. 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).
    18. Tobias Braun & Jonas A Fiegen & Daniel C Wagner & Sebastian M Krause & Thomas Guhr, 2018. "Impact and recovery process of mini flash crashes: An empirical study," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-11, May.
    19. 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.
    20. Кравчук, Ігор Святославович, 2018. "Сучасні тенденції електронної торгівлі обіговими фінансовими інструментами // Modern trends of electronic trading by negotiable financial instruments," Вісник Житомирського державного технологічного університету. Серія: Економічні науки // THE JOURNAL OF ZHYTOMYR STATE TECHNOLOGICAL UNIVERSITY. SERIES: ECONOMICS, Житомирський державний технологічний університет // ZHYTOMYR STATE TECHNOLOGICAL UNIVERSITY, vol. 83(1).
    21. 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).
    22. Sánchez Serrano Antonio, 2020. "High-Frequency Trading and Systemic Risk: A Structured Review of Findings and Policies," Review of Economics, De Gruyter, vol. 71(3), pages 169-195, December.
    23. Zhao, Shangmei & Chen, Xinyi & Zhang, Junhuan, 2019. "The systemic risk of China’s stock market during the crashes in 2008 and 2015," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 520(C), pages 161-177.
    24. Arumugam, Devika & Krishna Prasanna, P., 2021. "Commonality and contrarian trading among algorithmic traders," Journal of Behavioral and Experimental Finance, Elsevier, vol. 30(C).

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    More about this item

    Keywords

    High-frequency trading; Liquidity; Correlation; Systemic risk; Arrowhead; CoVaR;
    All these keywords.

    JEL classification:

    • 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
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets

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