IDEAS home Printed from https://ideas.repec.org/p/zbw/cfswop/580.html
   My bibliography  Save this paper

The ambivalent role of high-frequency trading in turbulent market periods

Author

Listed:
  • Hautsch, Nikolaus
  • Noé, Michael
  • Zhang, S. Sarah

Abstract

We show an ambivalent role of high-frequency traders (HFTs) in the Eurex Bund Futures market around high-impact macroeconomic announcements and extreme events. Around macroeconomic announcements, HFTs serve as market makers, post competitive spreads, and earn most of their profits through liquidity supply. Right before the announcement, however, HFTs significantly widen spreads and cause a rapid but short-lived drying-out of liquidity. In turbulent periods, such as after the U.K. Brexit announcement, HFTs shift their focus from market making activities to aggressive (but not necessarily profitable) directional strategies. Then, HFT activity becomes dominant and market quality can degrade.

Suggested Citation

  • Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    • Handle: RePEc:zbw:cfswop:580
    as

    Download full text from publisher

    File URL: https://www.econstor.eu/bitstream/10419/172247/1/1006705589.pdf
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Scholtus, Martin & van Dijk, Dick & Frijns, Bart, 2014. "Speed, algorithmic trading, and market quality around macroeconomic news announcements," Journal of Banking & Finance, Elsevier, vol. 38(C), pages 89-105.
    2. Bruno Biais & Fany Declerck & Sophie Moinas, 2016. "Who supplies liquidity, how and when?," BIS Working Papers 563, Bank for International Settlements.
    3. Hautsch, Nikolaus & Hess, Dieter & Veredas, David, 2011. "The impact of macroeconomic news on quote adjustments, noise, and informational volatility," Journal of Banking & Finance, Elsevier, vol. 35(10), pages 2733-2746, October.
    4. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    5. 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.
    6. Torben G. Andersen & Tim Bollerslev & Francis X. Diebold & Clara Vega, 2003. "Micro Effects of Macro Announcements: Real-Time Price Discovery in Foreign Exchange," American Economic Review, American Economic Association, vol. 93(1), pages 38-62, March.
    7. Hasbrouck, Joel & Saar, Gideon, 2013. "Low-latency trading," Journal of Financial Markets, Elsevier, vol. 16(4), pages 646-679.
    8. 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.
    9. Brogaard, Jonathan & Hendershott, Terrence & Riordan, Ryan, 2017. "High frequency trading and the 2008 short-sale ban," Journal of Financial Economics, Elsevier, vol. 124(1), pages 22-42.
    10. 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.
    11. Jiang, George J. & Konstantinidi, Eirini & Skiadopoulos, George, 2012. "Volatility spillovers and the effect of news announcements," Journal of Banking & Finance, Elsevier, vol. 36(8), pages 2260-2273.
    12. Hautsch, Nikolaus & Horvath, Akos, 2019. "How effective are trading pauses?," Journal of Financial Economics, Elsevier, vol. 131(2), pages 378-403.
    13. Hasabrouck, Joel & Sofianos, George, 1993. "The Trades of Market Makers: An Empirical Analysis of NYSE Specialists," Journal of Finance, American Finance Association, vol. 48(5), pages 1565-1593, December.
    14. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    15. Eric Budish & Peter Cramton & John Shim, 2015. "Editor's Choice The High-Frequency Trading Arms Race: Frequent Batch Auctions as a Market Design Response," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 130(4), pages 1547-1621.
    16. repec:bla:jfinan:v:59:y:2004:i:3:p:1201-1234 is not listed on IDEAS
    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. Vincent van Kervel, 2015. "Competition for Order Flow with Fast and Slow Traders," The Review of Financial Studies, Society for Financial Studies, vol. 28(7), pages 2094-2127.
    19. Venkataraman, Kumar & Waisburd, Andrew C., 2007. "The Value of the Designated Market Maker," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 42(3), pages 735-758, September.
    20. 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.
    21. Schlepper, Kathi, 2016. "High-frequency trading in the Bund futures market," Discussion Papers 15/2016, Deutsche Bundesbank.
    22. Michael J. Fleming & Eli M. Remolona, 1999. "Price Formation and Liquidity in the U.S. Treasury Market: The Response to Public Information," Journal of Finance, American Finance Association, vol. 54(5), pages 1901-1915, October.
    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. Bellia, Mario & Christensen, Kim & Kolokolov, Aleksey & Pelizzon, Loriana & Renò, Roberto, 2022. "Do designated market makers provide liquidity during a flash crash?," SAFE Working Paper Series 270, Leibniz Institute for Financial Research SAFE, revised 2022.
    2. Brice Corgnet & Mark DeSantis & Christoph Siemroth, 2023. "Algorithmic Trading, Price Efficiency and Welfare: An Experimental Approach," Working Papers 2313, Groupe d'Analyse et de Théorie Economique Lyon St-Étienne (GATE Lyon St-Étienne), Université de Lyon.
    3. Yamada, Masahiro, 2022. "Profitability and liquidity provision of HFTs during large price shocks: Does relative tick size matter?," Finance Research Letters, Elsevier, vol. 46(PA).
    4. 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).
    5. Park, Seongkyu Gilbert & Ryu, Doojin, 2019. "Speed and trading behavior in an order-driven market," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 145-164.
    6. Banerjee, Anirban & Nawn, Samarpan, 2024. "Proprietary algorithmic traders and liquidity supply during the pandemic," Finance Research Letters, Elsevier, vol. 61(C).
    7. 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).

    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. 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.
    3. 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).
    4. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    5. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    6. Foucault, Thierry & Moinas, Sophie, 2018. "Is Trading Fast Dangerous?," TSE Working Papers 18-881, Toulouse School of Economics (TSE).
    7. 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).
    8. 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).
    9. Roşu, Ioanid, 2019. "Fast and slow informed trading," Journal of Financial Markets, Elsevier, vol. 43(C), pages 1-30.
    10. 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.
    11. Yang, Haijun & Ge, Hengshun & Luo, Ying, 2020. "The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity," Research in International Business and Finance, Elsevier, vol. 53(C).
    12. Keiichi Goshima & Yusuke Kumano, 2018. "Monetary Policy Announcement and Algorithmic News Trading in the Foreign Exchange Market," IMES Discussion Paper Series 18-E-13, Institute for Monetary and Economic Studies, Bank of Japan.
    13. Syamala, Sudhakara Reddy & Wadhwa, Kavita, 2020. "Trading performance and market efficiency: Evidence from algorithmic trading," Research in International Business and Finance, Elsevier, vol. 54(C).
    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. Gerig, Austin & Michayluk, David, 2017. "Automated liquidity provision," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 1-13.
    16. 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).
    17. 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.
    18. 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).
    19. 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).
    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

    High Frequency Trading; Market Making; News Releases; Futures Market; Brexit;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

    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:zbw:cfswop:580. 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: 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. RePEc uses bibliographic data supplied by the respective publishers.