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How rigged are stock markets? Evidence from microsecond timestamps

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  • Bartlett, Robert P.
  • McCrary, Justin

Abstract

Using new data from the two U.S. securities information processors (SIPs) between August 6, 2015 and June 30, 2016, we examine claims that high-frequency trading (HFT) firms use direct feeds to exploit traders who rely on SIP prices. Across $3.7 trillion of trades in the Dow Jones 30, the SIPs report quote updates from exchanges 1,128 μs after they occur. However, the SIP-reported National Best Bid and Offer (NBBO) matches the NBBO calculated without reporting latencies in 97% of all SIP-priced trades. Liquidity-taking orders gain on average $0.0002/share when priced at the SIP-reported NBBO rather than the instantaneous NBBO, but aggregate gross profits are just $14.4 million. These findings indicate that direct feed arbitrage is not a meaningful source of HFT profits, nor can it explain the arms race for trading speed.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:finmar:v:45:y:2019:i:c:p:37-60
    DOI: 10.1016/j.finmar.2019.06.003
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    2. Joel Hasbrouck, 2021. "Price Discovery in High Resolution," Journal of Financial Econometrics, Oxford University Press, vol. 19(3), pages 395-430.
    3. Brian F Tivnan & David Rushing Dewhurst & Colin M Van Oort & John H Ring IV & Tyler J Gray & Brendan F Tivnan & Matthew T K Koehler & Matthew T McMahon & David M Slater & Jason G Veneman & Christopher, 2020. "Fragmentation and inefficiencies in US equity markets: Evidence from the Dow 30," PLOS ONE, Public Library of Science, vol. 15(1), pages 1-24, January.
    4. 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.
    5. Peter B. Lerner, 2022. "Fourier Integral Operator Model of Market Liquidity: The Chinese Experience 2009–2010," Mathematics, MDPI, vol. 10(14), pages 1-25, July.
    6. Allen Carrion & Madhuparna Kolay, 2020. "Trade signing in fast markets," The Financial Review, Eastern Finance Association, vol. 55(3), pages 385-404, August.
    7. Peter Lerner, 2022. "The market drives ETFs or ETFs the market: causality without Granger," Papers 2204.03760, arXiv.org.
    8. P. B. Lerner, 2020. "Dual State-Space Model of Market Liquidity: The Chinese Experience 2009-2010," Papers 2004.06200, arXiv.org, revised May 2020.
    9. 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.
    10. Peter B. Lerner, 2021. "Transmission of Trading Orders through Communication Line with Relativistic Delay," IJFS, MDPI, vol. 9(1), pages 1-11, February.
    11. Bidisha Chakrabarty & Pankaj K. Jain & Andriy Shkilko & Konstantin Sokolov, 2021. "Unfiltered Market Access and Liquidity: Evidence from the SEC Rule 15c3-5," Management Science, INFORMS, vol. 67(2), pages 1183-1198, February.

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    More about this item

    Keywords

    Latency arbitrage; High-frequency trading; SIP; Market structure;
    All these keywords.

    JEL classification:

    • G10 - Financial Economics - - General Financial Markets - - - General (includes Measurement and Data)
    • G15 - Financial Economics - - General Financial Markets - - - International Financial Markets
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation
    • G23 - Financial Economics - - Financial Institutions and Services - - - Non-bank Financial Institutions; Financial Instruments; Institutional Investors
    • G28 - Financial Economics - - Financial Institutions and Services - - - Government Policy and Regulation
    • K22 - Law and Economics - - Regulation and Business Law - - - Business and Securities Law

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