IDEAS home Printed from https://ideas.repec.org/p/zbw/cfswop/200841.html
   My bibliography  Save this paper

Does algorithmic trading improve liquidity?

Author

Listed:
  • Hendershott, Terrence
  • Jones, Charles M.
  • Menkveld, Albert J.

Abstract

Algorithmic trading has sharply increased over the past decade. Equity market liquidity has improved as well. Are the two trends related? For a recent five-year panel of New York Stock Exchange (NYSE) stocks, we use a normalized measure of electronic message traffic (order submissions, cancellations, and executions) as a proxy for algorithmic trading, and we trace the associations between liquidity and message traffic. Based on within-stock variation, we find that algorithmic trading and liquidity are positively related. To sort out causality, we use the start of autoquoting on the NYSE as an exogenous instrument for algorithmic trading. Previously, specialists were responsible for manually disseminating the inside quote. As stocks were phased in gradually during early 2003, the manual quote was replaced by a new automated quote whenever there was a change to the NYSE limit order book. This market structure change provides quicker feedback to traders and algorithms and results in more message traffic. For large-cap stocks in particular, quoted and effective spreads narrow under autoquote and adverse selection declines, indicating that algorithmic trading does causally improve liquidity.

Suggested Citation

  • Hendershott, Terrence & Jones, Charles M. & Menkveld, Albert J., 2008. "Does algorithmic trading improve liquidity?," CFS Working Paper Series 2008/41, Center for Financial Studies (CFS).
  • Handle: RePEc:zbw:cfswop:200841
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/43255/1/599235055.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Keim, Donald B. & Madhavan, Ananth, 1995. "Anatomy of the trading process Empirical evidence on the behavior of institutional traders," Journal of Financial Economics, Elsevier, vol. 37(3), pages 371-398, March.
    2. Thierry Foucault & Ailsa Röell & Patrik Sandås, 2003. "Market Making with Costly Monitoring: An Analysis of the SOES Controversy," Review of Financial Studies, Society for Financial Studies, vol. 16(2), pages 345-384.
    3. Glosten, Lawrence R, 1994. "Is the Electronic Open Limit Order Book Inevitable?," Journal of Finance, American Finance Association, vol. 49(4), pages 1127-1161, September.
    4. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    5. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
    6. Obizhaeva, Anna A. & Wang, Jiang, 2013. "Optimal trading strategy and supply/demand dynamics," Journal of Financial Markets, Elsevier, vol. 16(1), pages 1-32.
    7. Bessembinder, Hendrik, 2003. "Issues in assessing trade execution costs," Journal of Financial Markets, Elsevier, vol. 6(3), pages 233-257, May.
    8. Hasbrouck, Joel & Ho, Thomas S Y, 1987. "Order Arrival, Quote Behavior, and the Return-Generating Process," Journal of Finance, American Finance Association, vol. 42(4), pages 1035-1048, September.
    9. Lo, Andrew W. & MacKinlay, A. Craig & Zhang, June, 2002. "Econometric models of limit-order executions," Journal of Financial Economics, Elsevier, vol. 65(1), pages 31-71, July.
    10. 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.
    11. Pankaj K. Jain, 2005. "Financial Market Design and the Equity Premium: Electronic versus Floor Trading," Journal of Finance, American Finance Association, vol. 60(6), pages 2955-2985, December.
    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. Terrence Hendershott & Ryan Riordan, 2009. "Algorithmic Trading and Information," Working Papers 09-08, NET Institute, revised Aug 2009.
    2. Fong, Kingsley Y.L. & Liu, Wai-Man, 2010. "Limit order revisions," Journal of Banking & Finance, Elsevier, vol. 34(8), pages 1873-1885, August.
    3. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4-2015, August.
    4. G. Wuyts, 2007. "Stock Market Liquidity.Determinants and Implications," Review of Business and Economic Literature, KU Leuven, Faculty of Economics and Business (FEB), Review of Business and Economic Literature, vol. 0(2), pages 279-316.
    5. Stenfors, Alexis & Susai, Masayuki, 2019. "Liquidity withdrawal in the FX spot market: A cross-country study using high-frequency data," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 59(C), pages 36-57.
    6. Arie E. Gozluklu & Pietro Perotti & Barbara Rindi & Roberta Fredella, 2015. "Lot Size Constraints and Market Quality: Evidence from the Borsa Italiana," Financial Management, Financial Management Association International, vol. 44(4), pages 905-945, October.
    7. Danny Lo, 2015. "Essays in Market Microstructure and Investor Trading," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 22, July-Dece.
    8. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 4, July-Dece.
    9. Craig W. Holden & Stacey Jacobsen & Avanidhar Subrahmanyam, 2014. "The Empirical Analysis of Liquidity," Foundations and Trends(R) in Finance, now publishers, vol. 8(4), pages 263-365, December.
    10. Biais, Bruno & Glosten, Larry & Spatt, Chester, 2005. "Market microstructure: A survey of microfoundations, empirical results, and policy implications," Journal of Financial Markets, Elsevier, vol. 8(2), pages 217-264, May.
    11. Abad, David & Pascual, Roberto, 2015. "The friction-free weighted price contribution," International Review of Economics & Finance, Elsevier, vol. 37(C), pages 226-239.
    12. Murphy Jun Jie Lee, 2013. "The Microstructure of Trading Processes on the Singapore Exchange," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 2-2013, August.
    13. Hendershott, Terrence & Moulton, Pamela C., 2011. "Automation, speed, and stock market quality: The NYSE's Hybrid," Journal of Financial Markets, Elsevier, vol. 14(4), pages 568-604, November.
    14. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    15. Martin D. Gould & Mason A. Porter & Stacy Williams & Mark McDonald & Daniel J. Fenn & Sam D. Howison, 2013. "Limit order books," Quantitative Finance, Taylor & Francis Journals, vol. 13(11), pages 1709-1742, November.
    16. Rose, Annica, 2014. "The informational effect and market quality impact of upstairs trading and fleeting orders on the Australian Securities Exchange," Journal of Empirical Finance, Elsevier, vol. 28(C), pages 171-184.
    17. Chang, Sanders S. & Wang, F. Albert, 2015. "Adverse selection and the presence of informed trading," Journal of Empirical Finance, Elsevier, vol. 33(C), pages 19-33.
    18. Menkhoff, Lukas & Osler, Carol L. & Schmeling, Maik, 2010. "Limit-order submission strategies under asymmetric information," Journal of Banking & Finance, Elsevier, vol. 34(11), pages 2665-2677, November.
    19. Thierry Foucault & Sophie Moinas & Erik Theissen, 2007. "Does Anonymity Matter in Electronic Limit Order Markets?," Review of Financial Studies, Society for Financial Studies, vol. 20(5), pages 1707-1747, 2007 28.
    20. Comerton-Forde, Carole & Tang, Kar Mei, 2009. "Anonymity, liquidity and fragmentation," Journal of Financial Markets, Elsevier, vol. 12(3), pages 337-367, August.

    More about this item

    Keywords

    Liquidity; Algorithmic Trading; Microstructure;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)

    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:zbw:cfswop:200841. See general information about how to correct material in RePEc.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: . General contact details of provider: https://edirc.repec.org/data/ifkcfde.html .

    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: ZBW - Leibniz Information Centre for Economics (email available below). General contact details of provider: https://edirc.repec.org/data/ifkcfde.html .

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

    IDEAS is a RePEc service hosted by the Research Division of the Federal Reserve Bank of St. Louis . RePEc uses bibliographic data supplied by the respective publishers.