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Order Protection Through Delayed Messaging

Author

Listed:
  • Eric M. Aldrich

    (Amazon, New York, New York 10018)

  • Daniel Friedman

    (Department of Economics, University of Essex, Colchester CO4 3SQ, United Kingdom; Department of Economics, University of California Santa Cruz, Santa Cruz, California 95064)

Abstract
Several financial exchanges (e.g., IEX and NYSE American) recently introduced messaging delays to protect ordinary investors from high-frequency traders who exploit stale orders. To capture the impact of such delays, we propose a simple parametric model of the continuous double auction market format. The model examines the dynamics of midpoint pegged order queues and finds their steady states. It shows how messaging delays can protect pegged orders and improve investor welfare, but typically increase queuing costs. Recently available field data show that the empirical distribution of queued pegged orders is highly leptokurtotic and resembles the discrete Laplace distribution predicted by the model.

Suggested Citation

  • Eric M. Aldrich & Daniel Friedman, 2023. "Order Protection Through Delayed Messaging," Management Science, INFORMS, vol. 69(2), pages 774-790, February.
    • Handle: RePEc:inm:ormnsc:v:69:y:2023:i:2:p:774-790
    DOI: 10.1287/mnsc.2022.4370
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    References listed on IDEAS

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    Full references (including those not matched with items on IDEAS)

    Citations

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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. 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.
    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. Mariana Khapko & Marius Zoican, 2019. "Do speed bumps curb low-latency trading? Evidence from a laboratory market," Papers 1910.03068, arXiv.org.
    5. 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.

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    More about this item

    Keywords

    high-frequency trading; continuous double auction; pegged orders; IEX;
    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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