IDEAS home Printed from https://ideas.repec.org/a/cdh/commen/391.html
   My bibliography  Save this article

High Frequency Traders: Angels or Devils?

Author

Listed:
  • Jeffrey MacIntosh

    (University of Toronto)

Abstract

High frequency trading (HFT) is taking world capital markets by storm, notably in the United States and the United Kingdom, where it accounted for about 50 percent of equities trading in 2012, and to a growing extent in other parts of Europe and in Canada. Are high frequency traders angels or devils in terms of the impact on capital markets? Critics claim the latter and charge that they put retail and institutional investors at a disadvantage. Critics also blame high frequency trading for the “flash crash” on the Dow of May 6 2010 and say it has increased the likelihood of such events happening again. A closer examination of these views is in order. In this Commentary, I first look at what HF traders do and how HFT differs from traditional market making. I then explore the empirical evidence relating to the effect of HFT on capital markets, and canvass the policy issues that HFT raises. In the final section, I list some recommendations for policymakers with respect to HFT. After surveying empirical studies of HFT, I conclude that it enhances market quality. For example, it lowers bid/ask spreads, reduces volatility, improves short-term price discovery, and creates competitive pressures that reduce broker commissions. Despite being at a pronounced speed disadvantage, retail traders have realized a net gain from the presence of HF traders in the world’s capital markets. Maintain the Order Protection Rule and Contain the Spread of Dark Pools: To prevent abusive trading practices, protect client interests, and create a level playing field among different trading venues, policymakers should defend the consolidated order book by maintaining and policing the order protection rule and minimizing the leakage of trading from the “lit” markets to “dark pools.” Do Not Interfere with Maker/Taker Pricing Models: Some observers say maker/taker pricing raises higher trading costs for retail traders, because retail trade orders are typically on the active side of the market, and associated fees are passed on to customers. However, retail traders are about as likely to be on the active as the passive side of the market. Maker/taker pricing may raise costs on the margin, but also lowers bid/ask spreads. Focus on Circuit Breakers to Prevent “Flash Crashes”: HF traders did not cause the “flash crash,” and instead supply liquidity when markets become volatile. Canadian regulators concerned with preventing similar events should focus on circuit breakers to stop market anomalies before they turn into “flash crashes.”

Suggested Citation

  • Jeffrey MacIntosh, 2013. "High Frequency Traders: Angels or Devils?," C.D. Howe Institute Commentary, C.D. Howe Institute, issue 391, October.
  • Handle: RePEc:cdh:commen:391
    as

    Download full text from publisher

    File URL: https://www.cdhowe.org/public-policy-research/high-frequency-traders-angels-or-devils
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2015. "High frequency trading and end-of-day price dislocation," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 330-349.
    2. 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.
    3. Stoll, Hans R, 1978. "The Supply of Dealer Services in Securities Markets," Journal of Finance, American Finance Association, vol. 33(4), pages 1133-1151, September.
    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. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    2. repec:hal:spmain:info:hdl:2441/f6h8764enu2lskk9p4oq9ig8k is not listed on IDEAS
    3. Aitken, Michael & Cumming, Douglas & Zhan, Feng, 2015. "High frequency trading and end-of-day price dislocation," Journal of Banking & Finance, Elsevier, vol. 59(C), pages 330-349.
    4. Torben G. Andersen & Oleg Bondarenko, 2013. "Assessing Measures of Order Flow Toxicity via Perfect Trade Classification," CREATES Research Papers 2013-43, Department of Economics and Business Economics, Aarhus University.
    5. Lucio Maria Calcagnile & Giacomo Bormetti & Michele Treccani & Stefano Marmi & Fabrizio Lillo, 2015. "Collective synchronization and high frequency systemic instabilities in financial markets," Papers 1505.00704, arXiv.org.

    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. Steven L. Heston & Robert A. Korajczyk & Ronnie Sadka, 2010. "Intraday Patterns in the Cross‐section of Stock Returns," Journal of Finance, American Finance Association, vol. 65(4), pages 1369-1407, August.
    2. Hendershott, Terrence & Menkveld, Albert J., 2014. "Price pressures," Journal of Financial Economics, Elsevier, vol. 114(3), pages 405-423.
    3. 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.
    4. Ranaldo, Angelo & Somogyi, Fabricius, 2021. "Asymmetric information risk in FX markets," Journal of Financial Economics, Elsevier, vol. 140(2), pages 391-411.
    5. Clapham, Benjamin & Gomber, Peter & Lausen, Jens & Panz, Sven, 2018. "Liquidity provider incentives in fragmented securities markets," SAFE Working Paper Series 231, Leibniz Institute for Financial Research SAFE.
    6. 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).
    7. Khomyn, Marta & Putniņš, Tālis J., 2021. "Algos gone wild: What drives the extreme order cancellation rates in modern markets?," Journal of Banking & Finance, Elsevier, vol. 129(C).
    8. 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).
    9. Lepone, Andrew & Wong, Jin Boon, 2017. "Pseudo market-makers, market quality and the minimum tick size," International Review of Economics & Finance, Elsevier, vol. 47(C), pages 88-100.
    10. Shang, Chenguang, 2020. "Trade credit and stock liquidity," Journal of Corporate Finance, Elsevier, vol. 62(C).
    11. Ersan, Oguz & Simsir, Serif Aziz & Simsek, Koray D. & Hasan, Afan, 2021. "The speed of stock price adjustment to corporate announcements: Insights from Turkey," Emerging Markets Review, Elsevier, vol. 47(C).
    12. 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.
    13. Fricke, Daniel & Gerig, Austin, 2014. "Liquidity Risk, Speculative Trade, and the Optimal Latency of Financial Markets," VfS Annual Conference 2014 (Hamburg): Evidence-based Economic Policy 100402, Verein für Socialpolitik / German Economic Association.
    14. 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).
    15. Mila Getmansky & Ravi Jagannathan & Loriana Pelizzon & Ernst Schaumburg & Darya Yuferova, 2017. "Stock Price Crashes: Role of Slow-Moving Capital," NBER Working Papers 24098, National Bureau of Economic Research, Inc.
    16. 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.
    17. Chelley-Steeley, Patricia L. & Lambertides, Neophytos & Steeley, James M., 2016. "Explaining turn of the year order flow imbalance," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 76-95.
    18. Zhou, Hao & Kalev, Petko S. & Frino, Alex, 2020. "Algorithmic trading in turbulent markets," Pacific-Basin Finance Journal, Elsevier, vol. 62(C).
    19. Joel Peress & Daniel Schmidt, 2020. "Glued to the TV: Distracted Noise Traders and Stock Market Liquidity," Journal of Finance, American Finance Association, vol. 75(2), pages 1083-1133, April.
    20. Benos, Evangelos & Sagade, Satchit, 2012. "High-frequency trading behaviour and its impact on market quality: evidence from the UK equity market," Bank of England working papers 469, Bank of England.

    More about this item

    Keywords

    Economic Growth and Innovation; Financial Services;

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G18 - Financial Economics - - General Financial Markets - - - 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:cdh:commen:391. 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: Kristine Gray (email available below). General contact details of provider: https://edirc.repec.org/data/cdhowca.html .

    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.