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Who provides liquidity, and when?

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  • Li, Sida
  • Wang, Xin
  • Ye, Mao

Abstract

We model competition for liquidity provision between high-frequency traders (HFTs) and slower execution algorithms (EAs) designed to minimize investors’ transaction costs. Under continuous pricing, EAs dominate liquidity provision by using aggressive limit orders to stimulate HFTs’ market orders. Under discrete pricing, HFTs dominate liquidity provision if the bid-ask spread is binding at one tick. If the tick size (minimum price variation) is not binding, EAs choose between stimulating HFTs and providing liquidity to non-HFTs. Transaction costs increase with the tick size but can be negatively correlated with the bid-ask spread when all traders can provide liquidity.

Suggested Citation

  • Li, Sida & Wang, Xin & Ye, Mao, 2021. "Who provides liquidity, and when?," Journal of Financial Economics, Elsevier, vol. 141(3), pages 968-980.
    • Handle: RePEc:eee:jfinec:v:141:y:2021:i:3:p:968-980
    DOI: 10.1016/j.jfineco.2021.04.020
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    References listed on IDEAS

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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. Li, Sida & Ye, Mao & Zheng, Miles, 2023. "Refusing the best price?," Journal of Financial Economics, Elsevier, vol. 147(2), pages 317-337.
    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. Petter Dahlström & Björn Hagströmer & Lars L. Nordén, 2024. "The determinants of limit order cancellations," The Financial Review, Eastern Finance Association, vol. 59(1), pages 181-201, February.
    5. Jose S. Penalva & Mikel Tapia, 2021. "Heterogeneity and Competition in Fragmented Markets: Fees Vs Speed," Applied Mathematical Finance, Taylor & Francis Journals, vol. 28(2), pages 143-177, March.
    6. Matteo Aquilina & Eric Budish & Peter O’Neill, 2022. "Quantifying the High-Frequency Trading “Arms Race”," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 137(1), pages 493-564.
    7. 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).
    8. Eric Budish & Peter Cramton & Albert S. Kyle & Jeongmin Lee & David Malec, 2022. "Flow Trading," ECONtribute Discussion Papers Series 146, University of Bonn and University of Cologne, Germany.
    9. Dang, Man & Puwanenthiren, Premkanth & Nguyen, Manh Toan & Hoang, Viet Anh & Mazur, Mieszko & Henry, Darren, 2022. "Does managerial tone matter for stock liquidity? Evidence from textual disclosures," Finance Research Letters, Elsevier, vol. 48(C).
    10. Giuliano Graziani & Barbara Rindi, 2023. "Optimal Tick Size," Working Papers 688, IGIER (Innocenzo Gasparini Institute for Economic Research), Bocconi University.

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    More about this item

    Keywords

    High-frequency trading; Algorithmic trading; Tick size; Liquidity; Bid-ask spread;
    All these keywords.

    JEL classification:

    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G18 - Financial Economics - - General Financial Markets - - - Government Policy and Regulation

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