IDEAS home Printed from https://ideas.repec.org/p/bis/biswps/1115.html
   My bibliography  Save this paper

Sharks in the dark: quantifying HFT dark pool latency arbitrage

Author

Listed:
  • Matteo Aquilina
  • Sean Foley
  • Peter O'Neill
  • Matteo Thomas Ruf

Abstract

We investigate stale reference pricing and liquidity provision in dark pools using proprietary, participant-level regulatory data. We show a substantial amount of stale trading occurs, imposing large costs on passive dark pool participants. Consistent with these costs, HFTs almost never provide liquidity in the dark, instead frequently consuming liquidity, in particular in order to take advantage of stale reference prices. Finally, we show that market design interventions randomizing dark execution times are successful at countering dark pool latency arbitrage, protecting passive providers of dark liquidity. Our results have substantial implications for practitioners and policymakers aiming to improve liquidity provision in dark pools.

Suggested Citation

  • Matteo Aquilina & Sean Foley & Peter O'Neill & Matteo Thomas Ruf, 2023. "Sharks in the dark: quantifying HFT dark pool latency arbitrage," BIS Working Papers 1115, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:1115
    as

    Download full text from publisher

    File URL: https://www.bis.org/publ/work1115.pdf
    File Function: Full PDF document
    Download Restriction: no

    File URL: https://www.bis.org/publ/work1115.htm
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Andriy Shkilko & Konstantin Sokolov, 2020. "Every Cloud Has a Silver Lining: Fast Trading, Microwave Connectivity, and Trading Costs," Journal of Finance, American Finance Association, vol. 75(6), pages 2899-2927, December.
    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. Glosten, Lawrence R. & Milgrom, Paul R., 1985. "Bid, ask and transaction prices in a specialist market with heterogeneously informed traders," Journal of Financial Economics, Elsevier, vol. 14(1), pages 71-100, March.
    4. Albert J. Menkveld & Marius A. Zoican, 2017. "Need for Speed? Exchange Latency and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1188-1228.
    5. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    6. 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.
    7. Conrad, Jennifer & Wahal, Sunil, 2020. "The term structure of liquidity provision," Journal of Financial Economics, Elsevier, vol. 136(1), pages 239-259.
    8. Angelo Aspris & Sean Foley & Peter O'Neill, 2020. "Benchmarks in the spotlight: The impact on exchange traded markets," Journal of Futures Markets, John Wiley & Sons, Ltd., vol. 40(11), pages 1691-1710, November.
    9. Albert J. Menkveld & Bart Zhou Yueshen, 2019. "The Flash Crash: A Cautionary Tale About Highly Fragmented Markets," Management Science, INFORMS, vol. 65(10), pages 4470-4488, October.
    10. 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.
    11. Haoxiang Zhu, 2014. "Do Dark Pools Harm Price Discovery?," The Review of Financial Studies, Society for Financial Studies, vol. 27(3), pages 747-789.
    12. Bartlett, Robert P. & McCrary, Justin, 2019. "How rigged are stock markets? Evidence from microsecond timestamps," Journal of Financial Markets, Elsevier, vol. 45(C), pages 37-60.
    13. Chau, Ching & Aspris, Angelo & Foley, Sean & Malloch, Hamish, 2021. "Quote-Based manipulation of illiquid securities," Finance Research Letters, Elsevier, vol. 39(C).
    14. Frino, Alex & Ibikunle, Gbenga & Mollica, Vito & Steffen, Tom, 2018. "The impact of commodity benchmarks on derivatives markets: The case of the dated Brent assessment and Brent futures," Journal of Banking & Finance, Elsevier, vol. 95(C), pages 27-43.
    15. Foley, Sean & Krekel, William & Mollica, Vito & Svec, Jiri, 2023. "Not so fast: Identifying and remediating slow and imprecise cryptocurrency exchange data," Finance Research Letters, Elsevier, vol. 51(C).
    16. Michael Goldstein & Shengwei Ding & John Hanna & Terrence Hendershott, 2014. "How Slow Is the NBBO? A Comparison with Direct Exchange Feeds," The Financial Review, Eastern Finance Association, vol. 49(2), pages 313-332, May.
    17. Markus Baldauf & Joshua Mollner, 2020. "High‐Frequency Trading and Market Performance," Journal of Finance, American Finance Association, vol. 75(3), pages 1495-1526, June.
    18. Foley, Sean & Putniņš, Tālis J., 2016. "Should we be afraid of the dark? Dark trading and market quality," Journal of Financial Economics, Elsevier, vol. 122(3), pages 456-481.
    19. Hasbrouck, Joel, 2018. "High-Frequency Quoting: Short-Term Volatility in Bids and Offers," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 53(2), pages 613-641, April.
    20. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.
    21. Jonathan Brogaard & Björn Hagströmer & Lars Nordén & Ryan Riordan, 2015. "Trading Fast and Slow: Colocation and Liquidity," The Review of Financial Studies, Society for Financial Studies, vol. 28(12), pages 3407-3443.
    22. Nimalendran, Mahendrarajah & Ray, Sugata, 2014. "Informational linkages between dark and lit trading venues," Journal of Financial Markets, Elsevier, vol. 17(C), pages 230-261.
    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. Rzayev, Khaladdin & Ibikunle, Gbenga & Steffen, Tom, 2023. "The market quality implications of speed in cross-platform trading: evidence from Frankfurt-London microwave," LSE Research Online Documents on Economics 119989, London School of Economics and Political Science, LSE Library.
    2. Baldauf, Markus & Mollner, Joshua, 2022. "Fast traders make a quick buck: The role of speed in liquidity provision," Journal of Financial Markets, Elsevier, vol. 58(C).
    3. 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".
    4. 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.
    5. 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.
    6. 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.
    7. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    8. Zhang, Zeyu & Ibikunle, Gbenga, 2023. "The market quality effects of sub-second frequent batch auctions: Evidence from dark trading restrictions," International Review of Financial Analysis, Elsevier, vol. 89(C).
    9. Breckenfelder, Johannes, 2019. "Competition among high-frequency traders, and market quality," Working Paper Series 2290, European Central Bank.
    10. Suchismita Mishra & Le Zhao, 2021. "Order Routing Decisions for a Fragmented Market: A Review," JRFM, MDPI, vol. 14(11), pages 1-32, November.
    11. 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.
    12. Eric M. Aldrich & Daniel Friedman, 2023. "Order Protection Through Delayed Messaging," Management Science, INFORMS, vol. 69(2), pages 774-790, February.
    13. Aggarwal, Nidhi & Panchapagesan, Venkatesh & Thomas, Susan, 2023. "When is the order-to-trade ratio fee effective?," Journal of Financial Markets, Elsevier, vol. 62(C).
    14. 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.
    15. 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.
    16. Peter Gomber & Satchit Sagade & Erik Theissen & Moritz Christian Weber & Christian Westheide, 2017. "Competition Between Equity Markets: A Review Of The Consolidation Versus Fragmentation Debate," Journal of Economic Surveys, Wiley Blackwell, vol. 31(3), pages 792-814, July.
    17. Brolley, Michael & Zoican, Marius, 2023. "Liquid speed: A micro-burst fee for low-latency exchanges," Journal of Financial Markets, Elsevier, vol. 64(C).
    18. Ibikunle, Gbenga & Rzayev, Khaladdin, 2023. "Volatility and dark trading: Evidence from the Covid-19 pandemic," The British Accounting Review, Elsevier, vol. 55(4).
    19. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    20. Sida Li & Xin Wang & Mao Ye, 2019. "Who Provides Liquidity, and When?," NBER Working Papers 25972, National Bureau of Economic Research, Inc.

    More about this item

    Keywords

    high-frequency trading; dark pools; latency arbitrage; stale quotes; reference prices;
    All these keywords.

    JEL classification:

    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • 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:bis:biswps:1115. 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: Christian Beslmeisl (email available below). General contact details of provider: https://edirc.repec.org/data/bisssch.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.