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Rent Seeking by Low-Latency Traders: Evidence from Trading on Macroeconomic Announcements

Author

Listed:
  • Tarun Chordia
  • T Clifton Green
  • Badrinath Kottimukkalur

Abstract

Prices of the highly liquid S&P 500 exchange-traded fund (SPY) and the E-mini future (ES) respond to macroeconomic announcement surprises within five milliseconds, with trading intensity increasing over 100-fold following the news release. However, profits from trading quickly are relatively small, roughly $\$$19,000 ($\$$50,000) per event for SPY (ES). Although the speed of information incorporation has increased in recent years, profits have not. Order flow has become less informative, consistent with prices responding directly to news rather than indirectly through trading. Our evidence indicates that low-latency liquidity demanders do not benefit materially from short-term monopolistic access to information. Received April 18, 2017; editorial decision November 4, 2017 by Editor Andrew Karolyi. Authors have furnished an Internet Appendix, which is available on the Oxford University Press Web site next to the link to the final published paper online.

Suggested Citation

  • Tarun Chordia & T Clifton Green & Badrinath Kottimukkalur, 2018. "Rent Seeking by Low-Latency Traders: Evidence from Trading on Macroeconomic Announcements," The Review of Financial Studies, Society for Financial Studies, vol. 31(12), pages 4650-4687.
    • Handle: RePEc:oup:rfinst:v:31:y:2018:i:12:p:4650-4687.
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    File URL: http://hdl.handle.net/10.1093/rfs/hhy025
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    Cited by:

    1. Kang, Jongho & Kang, Jangkoo & Kwon, Kyung Yoon, 2022. "Market versus limit orders of speculative high-frequency traders and price discovery," Research in International Business and Finance, Elsevier, vol. 63(C).
    2. Masahiro Yamada & Takatoshi Ito, 2020. "Price Discovery and Liquidity Recovery: Forex Market Reactions to Macro Announcements," NBER Working Papers 27036, National Bureau of Economic Research, Inc.
    3. 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.
    4. 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).
    5. Seok, Sangik & Cho, Hoon & Ryu, Doojin, 2022. "Scheduled macroeconomic news announcements and intraday market sentiment," The North American Journal of Economics and Finance, Elsevier, vol. 62(C).
    6. 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.
    7. Karolis Liaudinskas, 2022. "Human vs. Machine: Disposition Effect among Algorithmic and Human Day Traders," Working Paper 2022/6, Norges Bank.
    8. Gabriele D'Acunto & Paolo Bajardi & Francesco Bonchi & Gianmarco De Francisci Morales, 2021. "The Evolving Causal Structure of Equity Risk Factors," Papers 2111.05072, arXiv.org.
    9. Chen, Jian & Haboub, Ahmad & Khan, Ali, 2024. "Limits of arbitrage and their impact on market efficiency: Evidence from China," Global Finance Journal, Elsevier, vol. 59(C).
    10. Aziz Simsir, Serif & Simsek, Koray D., 2022. "The market impact of private information before corporate Announcements: Evidence from Turkey," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 80(C).
    11. Maryam Farboodi & Adrien Matray & Laura Veldkamp & Venky Venkateswaran, 2022. "Where Has All the Data Gone?," The Review of Financial Studies, Society for Financial Studies, vol. 35(7), pages 3101-3138.
    12. Yamada, Masahiro & Ito, Takatoshi, 2022. "Price discovery and liquidity recovery: Forex market reactions to macro announcements," Journal of International Money and Finance, Elsevier, vol. 120(C).
    13. Nicholas Hirschey, 2021. "Do High-Frequency Traders Anticipate Buying and Selling Pressure?," Management Science, INFORMS, vol. 67(6), pages 3321-3345, June.
    14. 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.
    15. Jie Cao & Tarun Chordia & Xintong Zhan, 2021. "The Calendar Effects of the Idiosyncratic Volatility Puzzle: A Tale of Two Days?," Management Science, INFORMS, vol. 67(12), pages 7866-7887, December.
    16. 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).
    17. 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.
    18. Armstrong, Will J. & Cardella, Laura & Sabah, Nasim, 2021. "Information shocks, disagreement, and drift," Journal of Financial Economics, Elsevier, vol. 140(3), pages 916-940.

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