IDEAS home Printed from https://ideas.repec.org/p/bca/bocawp/18-8.html
   My bibliography  Save this paper

High-Frequency Trading and Institutional Trading Costs

Author

Listed:
  • Marie Chen
  • Corey Garriott

Abstract

Using data on Canadian bond futures, we examine how high-frequency traders (HFTs) interact with institutions building large positions. In contrast to recent findings, we find HFTs in the data act as small-sized liquidity suppliers, and we reject the hypothesis that they engage in back running, a predatory trading strategy. Using a quasi-experiment in November 2011, in which a number of HFTs started trading the bond future, we run a difference-in-differences event study and find more competition among HFTs improves implementation shortfall, effective spreads, and short-term price impacts for institutional trading in Canadian bond futures.

Suggested Citation

  • Marie Chen & Corey Garriott, 2018. "High-Frequency Trading and Institutional Trading Costs," Staff Working Papers 18-8, Bank of Canada.
  • Handle: RePEc:bca:bocawp:18-8
    as

    Download full text from publisher

    File URL: https://www.bankofcanada.ca/wp-content/uploads/2018/02/swp2018-8.pdf
    Download Restriction: no
    ---><---

    Other versions of this item:

    References listed on IDEAS

    as
    1. Griffiths, Mark D. & Smith, Brian F. & Turnbull, D. Alasdair S. & White, Robert W., 2000. "The costs and determinants of order aggressiveness," Journal of Financial Economics, Elsevier, vol. 56(1), pages 65-88, April.
    2. Baron, Matthew & Brogaard, Jonathan & Hagströmer, Björn & Kirilenko, Andrei, 2019. "Risk and Return in High-Frequency Trading," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(3), pages 993-1024, June.
    3. Fleming, Michael J. & Mizrach, Bruce & Nguyen, Giang, 2018. "The microstructure of a U.S. Treasury ECN: The BrokerTec platform," Journal of Financial Markets, Elsevier, vol. 40(C), pages 2-22.
    4. 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.
    5. Carrion, Allen, 2013. "Very fast money: High-frequency trading on the NASDAQ," Journal of Financial Markets, Elsevier, vol. 16(4), pages 680-711.
    6. Albert J. Menkveld, 2016. "The Economics of High-Frequency Trading: Taking Stock," Annual Review of Financial Economics, Annual Reviews, vol. 8(1), pages 1-24, October.
    7. Brogaard, Jonathan & Garriott, Corey, 2019. "High-Frequency Trading Competition," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 54(4), pages 1469-1497, August.
    8. 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.
    9. Callaway, Brantly & Sant’Anna, Pedro H.C., 2021. "Difference-in-Differences with multiple time periods," Journal of Econometrics, Elsevier, vol. 225(2), pages 200-230.
    10. Kyle, Albert S, 1985. "Continuous Auctions and Insider Trading," Econometrica, Econometric Society, vol. 53(6), pages 1315-1335, November.
    11. Justin Cox & Bonnie Van Ness & Robert Van Ness, 2019. "Increasing the Tick: Examining the Impact of the Tick Size Change on Maker‐Taker and Taker‐Maker Market Models," The Financial Review, Eastern Finance Association, vol. 54(3), pages 417-449, August.
    12. 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.
    13. 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.
    14. 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.
    15. Brian M. Weller, 2018. "Does Algorithmic Trading Reduce Information Acquisition?," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2184-2226.
    16. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    17. 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.
    18. 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.
    19. Léanne Berger-Soucy & Corey Garriott & André Usche, 2018. "Government of Canada Fixed-Income Market Ecology," Discussion Papers 18-10, Bank of Canada.
    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. Sagade, Satchit & Scharnowski, Stefan & Westheide, Christian, 2022. "Broker colocation and the execution costs of customer and proprietary orders," SAFE Working Paper Series 366, Leibniz Institute for Financial Research SAFE.
    2. Corey Garriot & Ryan Riordan, 2020. "Trading on Long-term Information," Staff Working Papers 20-20, Bank of Canada.
    3. Onur, Esen & Roberts, John S. & Tuzun, Tugkan, 2023. "Trader positions and aggregate portfolio demand," The Journal of Economic Asymmetries, Elsevier, vol. 27(C).
    4. Zheng, Jiayi & Zhu, Yushu, 2023. "Algorithmic trading and block ownership initiation: An information perspective," The British Accounting Review, Elsevier, vol. 55(4).

    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. Karolis Liaudinskas, 2022. "Human vs. Machine: Disposition Effect among Algorithmic and Human Day Traders," Working Paper 2022/6, Norges Bank.
    2. 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.
    3. Mark Marner-Hausen, 2022. "Developing a Framework for Real-Time Trading in a Laboratory Financial Market," ECONtribute Discussion Papers Series 172, University of Bonn and University of Cologne, Germany.
    4. 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).
    5. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    6. Cox, Justin & Woods, Donovan, 2023. "COVID-19 and market structure dynamics," Journal of Banking & Finance, Elsevier, vol. 147(C).
    7. 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.
    8. Bizzozero, Paolo & Flepp, Raphael & Franck, Egon, 2018. "The effect of fast trading on price discovery and efficiency: Evidence from a betting exchange," Journal of Economic Behavior & Organization, Elsevier, vol. 156(C), pages 126-143.
    9. 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.
    10. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti & Uno, Jun & Yuferova, Darya, 2017. "Coming early to the party," SAFE Working Paper Series 182, Leibniz Institute for Financial Research SAFE.
      • Mario Bellia & Loriana Pelizzon & Marti G. Subrahmanyam & Jun Uno & Darya Yuferova, 2020. "Coming early to the party," Working Papers 2020:11, Department of Economics, University of Venice "Ca' Foscari".
    11. Angerer, Martin & Neugebauer, Tibor & Shachat, Jason, 2023. "Arbitrage bots in experimental asset markets," Journal of Economic Behavior & Organization, Elsevier, vol. 206(C), pages 262-278.
    12. Adrian, Tobias & Capponi, Agostino & Fleming, Michael & Vogt, Erik & Zhang, Hongzhong, 2020. "Intraday market making with overnight inventory costs," Journal of Financial Markets, Elsevier, vol. 50(C).
    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. Benos, Evangelos & Brugler, James & Hjalmarsson, Erik & Zikes, Filip, 2017. "Interactions among High-Frequency Traders," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 52(4), pages 1375-1402, August.
    15. Roşu, Ioanid, 2019. "Fast and slow informed trading," Journal of Financial Markets, Elsevier, vol. 43(C), pages 1-30.
    16. S. Sarah Zhang, 2018. "Need for speed: Hard information processing in a high‐frequency world," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 38(1), pages 3-21, January.
    17. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    18. Gider, Jasmin & Schmickler, Simon & Westheide, Christian, 2019. "High-frequency trading and price informativeness," SAFE Working Paper Series 248, Leibniz Institute for Financial Research SAFE, revised 2019.
    19. Donald B. Keim & Massimo Massa & Bastian von Beschwitz, 2018. "First to \"Read\" the News: New Analytics and Algorithmic Trading," International Finance Discussion Papers 1233, Board of Governors of the Federal Reserve System (U.S.).
    20. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.

    More about this item

    Keywords

    Financial markets; Financial system regulation and policies; Market structure and pricing;
    All these keywords.

    JEL classification:

    • G20 - Financial Economics - - Financial Institutions and Services - - - General
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • L10 - Industrial Organization - - Market Structure, Firm Strategy, and Market Performance - - - General

    NEP fields

    This paper has been announced in the following NEP Reports:

    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:bca:bocawp:18-8. 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: the person in charge (email available below). General contact details of provider: https://edirc.repec.org/data/bocgvca.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.