IDEAS home Printed from https://ideas.repec.org/a/eee/jbfina/v147y2023ics0378426621003137.html
   My bibliography  Save this article

COVID-19 and market structure dynamics

Author

Listed:
  • Cox, Justin
  • Woods, Donovan

Abstract

We examine the impact of COVID-19 on market structure in the U.S. Specifically, we analyze the impact of both the COVID-19-induced market uncertainty period as well as the suspension of the NYSE floor on trading dynamics such as market fragmentation, algorithmic trading, and hidden liquidity in the market. During both the heightened market uncertainty and NYSE floor suspension periods, we find a significant increase in hidden liquidity yet significant decreases in both algorithmic trading and market fragmentation. However, despite withdrawing from the market during this period, remaining algorithmic traders appear to improve market quality. Our results indicate that COVID-19 had a significant impact on order routing, pre-trade transparency, and automated trading.

Suggested Citation

  • Cox, Justin & Woods, Donovan, 2023. "COVID-19 and market structure dynamics," Journal of Banking & Finance, Elsevier, vol. 147(C).
  • Handle: RePEc:eee:jbfina:v:147:y:2023:i:c:s0378426621003137
    DOI: 10.1016/j.jbankfin.2021.106362
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378426621003137
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.jbankfin.2021.106362?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Friederich, Sylvain & Payne, Richard, 2015. "Order-to-trade ratios and market liquidity," Journal of Banking & Finance, Elsevier, vol. 50(C), pages 214-223.
    2. Andriy Shkilko & Konstantin Sokolov, 2020. "Every Cloud Has a Silver Lining: Fast Trading, Microwave Connectivity, and Trading Costs," Journal of Finance, American Finance Association, vol. 75(6), pages 2899-2927, December.
    3. Upson, James & Van Ness, Robert A., 2017. "Multiple markets, algorithmic trading, and market liquidity," Journal of Financial Markets, Elsevier, vol. 32(C), pages 49-68.
    4. Terrence Hendershott & Haim Mendelson, 2000. "Crossing Networks and Dealer Markets: Competition and Performance," Journal of Finance, American Finance Association, vol. 55(5), pages 2071-2115, October.
    5. Coën, Alain & de La Bruslerie, Hubert, 2019. "The informational dimensions of the Amihud (2002) illiquidity measure: Evidence from the M&A market," Finance Research Letters, Elsevier, vol. 29(C), pages 23-29.
    6. O'Hara, Maureen & Ye, Mao, 2011. "Is market fragmentation harming market quality?," Journal of Financial Economics, Elsevier, vol. 100(3), pages 459-474, June.
    7. 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.
    8. Ekkehart Boehmer & Dan Li & Gideon Saar, 2018. "The Competitive Landscape of High-Frequency Trading Firms," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2227-2276.
    9. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    10. Yacine Aït-Sahalia & Mehmet Saglam, 2013. "High Frequency Traders: Taking Advantage of Speed," NBER Working Papers 19531, National Bureau of Economic Research, Inc.
    11. Amihud, Yakov, 2002. "Illiquidity and stock returns: cross-section and time-series effects," Journal of Financial Markets, Elsevier, vol. 5(1), pages 31-56, January.
    12. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    13. 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.
    14. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    15. Goldstein, Michael A. & A. Kavajecz, Kenneth, 2000. "Eighths, sixteenths, and market depth: changes in tick size and liquidity provision on the NYSE," Journal of Financial Economics, Elsevier, vol. 56(1), pages 125-149, April.
    16. Davies, Ryan J. & Kim, Sang Soo, 2009. "Using matched samples to test for differences in trade execution costs," Journal of Financial Markets, Elsevier, vol. 12(2), pages 173-202, May.
    17. Robert A Korajczyk & Dermot Murphy, 2019. "High-Frequency Market Making to Large Institutional Trades," Review of Financial Studies, Society for Financial Studies, vol. 32(3), pages 1034-1067.
    18. Anand, Amber & Venkataraman, Kumar, 2016. "Market conditions, fragility, and the economics of market making," Journal of Financial Economics, Elsevier, vol. 121(2), pages 327-349.
    19. Brogaard, Jonathan & Carrion, Allen & Moyaert, Thibaut & Riordan, Ryan & Shkilko, Andriy & Sokolov, Konstantin, 2018. "High frequency trading and extreme price movements," Journal of Financial Economics, Elsevier, vol. 128(2), pages 253-265.
    20. 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.
    21. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2019. "Price Discovery without Trading: Evidence from Limit Orders," Journal of Finance, American Finance Association, vol. 74(4), pages 1621-1658, August.
    22. Vincent Van Kervel & Albert J. Menkveld, 2019. "High‐Frequency Trading around Large Institutional Orders," Journal of Finance, American Finance Association, vol. 74(3), pages 1091-1137, June.
    23. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    24. Chung, Kee H. & Zhang, Hao, 2014. "A simple approximation of intraday spreads using daily data," Journal of Financial Markets, Elsevier, vol. 17(C), pages 94-120.
    25. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    26. Gresse, Carole, 2017. "Effects of lit and dark market fragmentation on liquidity," Journal of Financial Markets, Elsevier, vol. 35(C), pages 1-20.
    27. Malceniece, Laura & Malcenieks, Kārlis & Putniņš, Tālis J., 2019. "High frequency trading and comovement in financial markets," Journal of Financial Economics, Elsevier, vol. 134(2), pages 381-399.
    28. 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.
    29. Ekkehart Boehmer & Gideon Saar & Lei Yu, 2005. "Lifting the Veil: An Analysis of Pre‐trade Transparency at the NYSE," Journal of Finance, American Finance Association, vol. 60(2), pages 783-815, April.
    30. Menkveld, Albert J. & Yueshen, Bart Zhou & Zhu, Haoxiang, 2017. "Shades of darkness: A pecking order of trading venues," Journal of Financial Economics, Elsevier, vol. 124(3), pages 503-534.
    31. 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.
    32. Sassan Alizadeh & Michael W. Brandt & Francis X. Diebold, 2002. "Range‐Based Estimation of Stochastic Volatility Models," Journal of Finance, American Finance Association, vol. 57(3), pages 1047-1091, June.
    33. Carole Gresse, 2017. "Effects of Lit and Dark Market Fragmentation on Liquidity," Post-Print hal-01631771, HAL.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Dodd, Olga & Frijns, Bart & Indriawan, Ivan & Pascual, Roberto, 2023. "US cross-listing and domestic high-frequency trading: Evidence from Canadian stocks," Journal of Empirical Finance, Elsevier, vol. 72(C), pages 301-320.
    2. Breedon, Francis & Chen, Louisa & Ranaldo, Angelo & Vause, Nicholas, 2023. "Judgment day: Algorithmic trading around the Swiss franc cap removal," Journal of International Economics, Elsevier, vol. 140(C).
    3. Benjamin Clapham & Martin Haferkorn & Kai Zimmermann, 2023. "The Impact of High-Frequency Trading on Modern Securities Markets," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 65(1), pages 7-24, February.
    4. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    5. Karolis Liaudinskas, 2022. "Human vs. Machine: Disposition Effect among Algorithmic and Human Day Traders," Working Paper 2022/6, Norges Bank.
    6. 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).
    7. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    8. Ligot, Stephanie & Gillet, Roland & Veryzhenko, Iryna, 2021. "Intraday volatility smile: Effects of fragmentation and high frequency trading on price efficiency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
    9. 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).
    10. 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).
    11. Chordia, Tarun & Miao, Bin, 2020. "Market efficiency in real time: Evidence from low latency activity around earnings announcements," Journal of Accounting and Economics, Elsevier, vol. 70(2).
    12. Chen, Marie & Garriott, Corey, 2020. "High-frequency trading and institutional trading costs," Journal of Empirical Finance, Elsevier, vol. 56(C), pages 74-93.
    13. Oliver Linton & Soheil Mahmoodzadeh, 2018. "Implications of High-Frequency Trading for Security Markets," Annual Review of Economics, Annual Reviews, vol. 10(1), pages 237-259, August.
    14. 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.
    15. Michael Goldstein & Amy Kwan & Richard Philip, 2023. "High-Frequency Trading Strategies," Management Science, INFORMS, vol. 69(8), pages 4413-4434, August.
    16. Chakrabarty, Bidisha & Pascual, Roberto, 2023. "Stock liquidity and algorithmic market making during the COVID-19 crisis," Journal of Banking & Finance, Elsevier, vol. 147(C).
    17. Zhou, Hao & Kalev, Petko S. & Frino, Alex, 2020. "Algorithmic trading in turbulent markets," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    18. Zheng, Jiayi & Zhu, Yushu, 2023. "Algorithmic trading and block ownership initiation: An information perspective," The British Accounting Review, Elsevier, vol. 55(4).
    19. 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).
    20. 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.

    More about this item

    Keywords

    COVID-19 pandemic; NYSE floor close; Algorithmic trading; Hidden liquidity;
    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
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • L1 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:jbfina:v:147:y:2023:i:c:s0378426621003137. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/jbf .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.