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Who supplies liquidity, how and when?

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  • Bruno Biais
  • Fany Declerck
  • Sophie Moinas

Abstract

Who provides liquidity in modern, electronic limit order book, markets? While agency trading can be constrained by conflicts of interest and information asymmetry between customers and traders, prop traders are likely to be less constrained and thus better positioned to carry inventory risk. Moreover, while slow traders' limit orders may be exposed to severe adverse selection, fast trading technology can improve traders' ability to monitor the market and avoid being picked off. To shed light on these points, we rely on unique data from Euronext and the AMF, the French financial markets regulator, enabling us to observe the connectivity of traders to the market, and whether they are proprietary traders. We find that proprietary traders, be they fast or slow, provide liquidity with contrarian marketable orders, thus helping the market absorb shocks, even during a crisis, and they earn profits while doing so. Moreover, fast traders provide liquidity by leaving limit orders in the book. Yet, only prop traders can do so without making losses. This suggests that technology is not enough to overcome adverse selection; monitoring incentives are also needed.

Suggested Citation

  • Bruno Biais & Fany Declerck & Sophie Moinas, 2016. "Who supplies liquidity, how and when?," BIS Working Papers 563, Bank for International Settlements.
  • Handle: RePEc:bis:biswps:563
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    Cited by:

    1. Alderighi, Stefano & Cleary, Siobhan & Varanasi, Padmasai, 2018. "The determinants of cross-border portfolio equity flows: new evidence from emerging markets," Economics Discussion Papers 23310, University of Essex, Department of Economics.
    2. Giovanni Cespa & Xavier Vives, 2022. "Exchange Competition, Entry, and Welfare," The Review of Financial Studies, Society for Financial Studies, vol. 35(5), pages 2570-2624.
    3. Selma Boussetta, 2017. "The role of pre-opening mechanisms in fragmented markets," Post-Print hal-02156145, HAL.
    4. Foucault, Thierry & Moinas, Sophie, 2018. "Is Trading Fast Dangerous?," TSE Working Papers 18-881, Toulouse School of Economics (TSE).
    5. Xinyue He & Teresa Serra & Philip Garcia, 2021. "Resilience in “Flash Events” in the Corn and Lean Hog Futures Markets," American Journal of Agricultural Economics, John Wiley & Sons, vol. 103(2), pages 743-764, March.
    6. Hautsch, Nikolaus & Noé, Michael & Zhang, S. Sarah, 2017. "The ambivalent role of high-frequency trading in turbulent market periods," CFS Working Paper Series 580, Center for Financial Studies (CFS).
    7. Cespa, Giovanni & Vives, Xavier, 2017. "High frequency trading and fragility," Working Paper Series 2020, European Central Bank.
    8. Banerjee, Anirban & Nawn, Samarpan, 2024. "Proprietary algorithmic traders and liquidity supply during the pandemic," Finance Research Letters, Elsevier, vol. 61(C).
    9. Fany Declerck & Laurence Lescourret, 2015. "Dark pools et trading haute fréquence : une évolution utile ?," Revue d'économie financière, Association d'économie financière, vol. 0(4), pages 113-126.
    10. Coen, Jamie & Coen, Patrick, 2022. "A structural model of liquidity in over‑the‑counter markets," Bank of England working papers 979, Bank of England.
    11. Xin Guo & Charles-Albert Lehalle & Renyuan Xu, 2022. "Transaction cost analytics for corporate bonds," Quantitative Finance, Taylor & Francis Journals, vol. 22(7), pages 1295-1319, July.
    12. Giovanni Cespa & Xavier Vives, 2016. "Market Transparency and Fragility," CESifo Working Paper Series 6279, CESifo.
    13. Saæglam, Mehmet & Tuzun, Tugkan & Wermers, Russ, 2021. "Do ETFs increase liquidity?," CFR Working Papers 21-03, University of Cologne, Centre for Financial Research (CFR).
    14. Esen Onur & John S. Roberts & Tugkan Tuzun, 2017. "Trader Positions and Marketwide Liquidity Demand," Finance and Economics Discussion Series 2017-103, Board of Governors of the Federal Reserve System (U.S.).
    15. Jean-Edouard Colliard, 2017. "Catching Falling Knives: Speculating on Liquidity Shocks," Management Science, INFORMS, vol. 63(8), pages 2573-2591, August.
    16. Bellia, Mario & Pelizzon, Loriana & Subrahmanyam, Marti & Uno, Jun & Yuferova, Darya, 2017. "Coming early to the party," SAFE Working Paper Series 182, Leibniz Institute for Financial Research SAFE.
      • Mario Bellia & Loriana Pelizzon & Marti G. Subrahmanyam & Jun Uno & Darya Yuferova, 2020. "Coming early to the party," Working Papers 2020:11, Department of Economics, University of Venice "Ca' Foscari".
    17. Aït-Sahalia, Yacine & Brunetti, Celso, 2020. "High frequency traders and the price process," Journal of Econometrics, Elsevier, vol. 217(1), pages 20-45.
    18. Alderighi, Stefano & Cleary, Siobhan & Varanasi, Padmasai, 2019. "Do institutional factors influence cross-border portfolio equity flows? New evidence from emerging markets," Journal of International Money and Finance, Elsevier, vol. 99(C).
    19. 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.
    20. Charles-Albert Lehalle & Othmane Mounjid, 2016. "Limit Order Strategic Placement with Adverse Selection Risk and the Role of Latency," Papers 1610.00261, arXiv.org, revised Mar 2018.
    21. Declerck, F., 2016. "High-frequency trading, geographical concerns and the curvature of the Earth," Financial Stability Review, Banque de France, issue 20, pages 153-160, April.
    22. Gousgounis, Eleni & Onur, Esen, 2018. "The effect of pit closure on futures trading," Journal of Commodity Markets, Elsevier, vol. 10(C), pages 69-90.

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    More about this item

    Keywords

    Liquidity; high-frequency trading; proprietary trading; adverse selection; electronic limit order book; short-term momentum; contrarian;
    All these keywords.

    JEL classification:

    • D82 - Microeconomics - - Information, Knowledge, and Uncertainty - - - Asymmetric and Private Information; Mechanism Design
    • G1 - Financial Economics - - General Financial Markets

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