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Order Protection through Delayed Messaging

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  • Aldrich, Eric M
  • Friedman, Daniel

Abstract

Several financial exchanges have recently introduced messaging delays (e.g., a 350 microsecond delay at IEX and NYSE American) intended to protect ordinary investors from high-frequency traders who exploit stale orders. We propose an equilibrium model of this exchange design as a modification of the standard continuous double auction market format. The model predicts that a messaging delay will generally improve price efficiency and lower transactions cost but will increase queuing costs. Some of the predictions are testable in the field or in a laboratory environment.
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Suggested Citation

  • Aldrich, Eric M & Friedman, Daniel, 2019. "Order Protection through Delayed Messaging," Santa Cruz Department of Economics, Working Paper Series qt4938f518, Department of Economics, UC Santa Cruz.
    • Handle: RePEc:cdl:ucscec:qt4938f518
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    References listed on IDEAS

    as
    1. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, vol. 2(2), pages 99-134, May.
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    6. Copeland, Thomas E & Galai, Dan, 1983. "Information Effects on the Bid-Ask Spread," Journal of Finance, American Finance Association, vol. 38(5), pages 1457-1469, December.
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    12. 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, Oxford University Press, vol. 130(4), pages 1547-1621.
    13. Brolley, Michael & Cimon, David A., 2020. "Order-Flow Segmentation, Liquidity, and Price Discovery: The Role of Latency Delays," Journal of Financial and Quantitative Analysis, Cambridge University Press, vol. 55(8), pages 2555-2587, December.
    14. Albert S Kyle & Jeongmin Lee, 2017. "Toward a fully continuous exchange," Oxford Review of Economic Policy, Oxford University Press, vol. 33(4), pages 650-675.
    15. David Easley & Marcos M. López de Prado & Maureen O'Hara, 2012. "Flow Toxicity and Liquidity in a High-frequency World," Review of Financial Studies, Society for Financial Studies, vol. 25(5), pages 1457-1493.
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    Cited by:

    1. Collins, Sean M. & James, Duncan & Servátka, Maroš & Vadovič, Radovan, 2021. "Attainment of equilibrium via Marshallian path adjustment: Queueing and buyer determinism," Games and Economic Behavior, Elsevier, vol. 125(C), pages 94-106.
    2. Eric M. Aldrich & Kristian López Vargas, 2020. "Experiments in high-frequency trading: comparing two market institutions," Experimental Economics, Springer;Economic Science Association, vol. 23(2), pages 322-352, June.
    3. 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.
    4. Kyungsub Lee & Byoung Ki Seo, 2022. "Modeling bid and ask price dynamics with an extended Hawkes process and its empirical applications for high-frequency stock market data," Papers 2201.10173, arXiv.org.
    5. Mariana Khapko & Marius Zoican, 2019. "Do speed bumps curb low-latency trading? Evidence from a laboratory market," Papers 1910.03068, arXiv.org.

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    More about this item

    Keywords

    Market design; high-frequency trading; continuous double auction; IEX; lab experiments;
    All these keywords.

    JEL classification:

    • C91 - Mathematical and Quantitative Methods - - Design of Experiments - - - Laboratory, Individual Behavior
    • D44 - Microeconomics - - Market Structure, Pricing, and Design - - - Auctions
    • D47 - Microeconomics - - Market Structure, Pricing, and Design - - - Market Design
    • D53 - Microeconomics - - General Equilibrium and Disequilibrium - - - Financial Markets
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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