IDEAS home Printed from https://ideas.repec.org/a/kap/jbuset/v147y2018i1d10.1007_s10551-015-2964-y.html
   My bibliography  Save this article

Market Fairness: The Poor Country Cousin of Market Efficiency

Author

Listed:
  • Michael J. Aitken

    () (Macquarie University)

  • Angelo Aspris

    () (University of Sydney)

  • Sean Foley

    () (University of Sydney)

  • Frederick H. de B. Harris

    () (Wake Forest University)

Abstract

Both fairness and efficiency are important considerations in market design and regulation, yet many regulators have neither defined nor measured these concepts. We develop an evidencebased policy framework in which these are both defined and measured using a series of empirical proxies. We then build a systems estimation model to examine the 2003–2011 explosive growth in algorithmic trading (AT) on the London Stock Exchange and NYSE Euronext Paris. Our results show that greater AT is associated with increased transactional efficiency and reduced information leakage in top quintile stocks. For less liquid stocks, manipulation at the close declines. We also document the tradeoff between reduced spreads and increased manipulation or information leakage following the introduction of MiFID1.

Suggested Citation

  • Michael J. Aitken & Angelo Aspris & Sean Foley & Frederick H. de B. Harris, 2018. "Market Fairness: The Poor Country Cousin of Market Efficiency," Journal of Business Ethics, Springer, vol. 147(1), pages 5-23, January.
    • Handle: RePEc:kap:jbuset:v:147:y:2018:i:1:d:10.1007_s10551-015-2964-y
    DOI: 10.1007/s10551-015-2964-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10551-015-2964-y
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    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. J. Dugast & T. Foucault, 2014. "False News, Informational Efficiency, and Price Reversals," Working papers 513, Banque de France.
    2. 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.
    3. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    4. Thomas H. McInish & James Upson, 2013. "The Quote Exception Rule: Giving High Frequency Traders an Unintended Advantage," Financial Management, Financial Management Association International, vol. 42(3), pages 481-501, September.
    5. 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.
    6. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    7. 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.
    8. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    9. Yan, Bingcheng & Zivot, Eric, 2010. "A structural analysis of price discovery measures," Journal of Financial Markets, Elsevier, vol. 13(1), pages 1-19, February.
    10. Albert S. Kyle & S. Viswanathan, 2008. "How to Define Illegal Price Manipulation," American Economic Review, American Economic Association, vol. 98(2), pages 274-279, May.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Agapova, Anna & Madura, Jeff & Volkov, Nikanor, 2020. "Information leakage of ADRs Prior to company issued guidance," Research in International Business and Finance, Elsevier, vol. 54(C).
    2. Zhang, Jun & Fu, Xiaoming & Morris, Harry, 2019. "Construction of indicator system of regional economic system impact factors based on fractional differential equations," Chaos, Solitons & Fractals, Elsevier, vol. 128(C), pages 25-33.

    More about this item

    Keywords

    Market quality; Market fairness; Manipulation; Information leakage; Algorithmic trading;

    JEL classification:

    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation

    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:kap:jbuset:v:147:y:2018:i:1:d:10.1007_s10551-015-2964-y. 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: (Sonal Shukla) or (Springer Nature Abstracting and Indexing). General contact details of provider: http://www.springer.com .

    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 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.

    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.