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Market Quality Breakdowns in Equities

Author

Listed:
  • Cheng Gao

    (Rutgers University)

  • Bruce Mizrach

    (Rutgers University)

Abstract

A breakdown in market quality occurs when an order book thins to the point where extreme price movements are observed. These are frequently reversed as the market learns that nothing fundamental has occurred. The daily average breakdown frequency from 1993-2011 is 0.64%, with averages in 2010-11 below this amount. Controlling for microstructure effects, breakdowns have fallen significantly since Reg NMS. Spikes in market correlation and high frequency trading surges make breakdowns more likely. ETFs break down more often than non-ETFs. Both ETFs and high frequency trading Granger cause market correlation. Breakdowns are predictable for up to two days.

Suggested Citation

  • Cheng Gao & Bruce Mizrach, 2013. "Market Quality Breakdowns in Equities," Departmental Working Papers 201318, Rutgers University, Department of Economics.
    • Handle: RePEc:rut:rutres:201318
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    Cited by:

    1. Elias Strehle, 2016. "Optimal Execution in a Multiplayer Model of Transient Price Impact," Papers 1609.00599, arXiv.org, revised Mar 2019.
    2. Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2025. "Do designated market makers provide liquidity during downward extreme price movements?," Journal of Financial Markets, Elsevier, vol. 76(C).
    3. Flora, Maria & Renò, Roberto, 2025. "V-shapes," Journal of Banking & Finance, Elsevier, vol. 179(C).
    4. 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.
    5. Saketh Aleti & Bruce Mizrach, 2021. "Bitcoin spot and futures market microstructure," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 41(2), pages 194-225, February.
    6. Aghanya, Daniel & Agarwal, Vineet & Poshakwale, Sunil, 2020. "Market in Financial Instruments Directive (MiFID), stock price informativeness and liquidity," Journal of Banking & Finance, Elsevier, vol. 113(C).
    7. 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.
    8. Mestel, Roland & Steffen, Viktoria & Theissen, Erik, 2024. "Algorithmic trading and mini flash crashes: Evidence from Austria," Economics Letters, Elsevier, vol. 244(C).
    9. Geir-Are Karvik & Joseph Noss & Jack Worlidge & Daniel Beale, 2018. "The deeds of speed: an agent-based model of market liquidity and flash episodes," Bank of England working papers 743, Bank of England.
    10. Thomas H. McInish & Olena Nikolsko‐Rzhevska & Alex Nikolsko‐Rzhevskyy & Irina Panovska, 2020. "Fast and slow cancellations and trader behavior," Financial Management, Financial Management Association International, vol. 49(4), pages 973-996, December.
    11. 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.
    12. Steffen, Viktoria, 2023. "A literature review on extreme price movements with reversal," Journal of Behavioral and Experimental Finance, Elsevier, vol. 38(C).
    13. Rif, Alexandru & Utz, Sebastian, 2021. "Short-term stock price reversals after extreme downward price movements," The Quarterly Review of Economics and Finance, Elsevier, vol. 81(C), pages 123-133.
    14. Zhou, Hao & Kalev, Petko S. & Frino, Alex, 2020. "Algorithmic trading in turbulent markets," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    15. 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).
    16. Schlepper, Kathi, 2016. "High-frequency trading in the Bund futures market," Discussion Papers 15/2016, Deutsche Bundesbank.

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    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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