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The Provision of Liquidity by High-Frequency Participants

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  • Michael Goldstein
  • Elvis Jarnecic
  • Mark Snape

Abstract

This paper examines the order submission strategies and supply of liquidity by high-frequency participants versus the remainder of participants in the limit order book. The results show that high-frequency participants submit orders at multiple prices in the limit order book, concentrated at or within the quote. This activity translates into the provision of liquidity on an on-going basis, which is robust to fast versus slow and volatile markets, together suggesting that high-frequency participants resolve temporal liquidity imbalances in the limit order book. The evidence is consistent with high-frequency trading (HFT) improving market liquidity, but there remain issues surrounding high-frequency participants’ effect on market depth and the difficulty of trading of non-HFT participants.

Suggested Citation

  • Michael Goldstein & Elvis Jarnecic & Mark Snape, 2014. "The Provision of Liquidity by High-Frequency Participants," The Financial Review, Eastern Finance Association, vol. 49(2), pages 371-394, May.
    • Handle: RePEc:bla:finrev:v:49:y:2014:i:2:p:371-394
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    File URL: http://hdl.handle.net/10.1111/fire.12040
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    Citations

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    Cited by:

    1. Juraj Hruška, 2016. "Aggressive and Defensive High‑Frequency Trading and its Impact on Liquidity of German Stock Market," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 64(6), pages 1911-1918.
    2. Zhou, Hao & Kalev, Petko S., 2019. "Algorithmic and high frequency trading in Asia-Pacific, now and the future," Pacific-Basin Finance Journal, Elsevier, vol. 53(C), pages 186-207.
    3. Mestel, Roland & Murg, Michael & Theissen, Erik, 2018. "Algorithmic trading and liquidity: Long term evidence from Austria," Finance Research Letters, Elsevier, vol. 26(C), pages 198-203.
    4. Frino, Alex & Mollica, Vito & Webb, Robert I. & Zhang, Shunquan, 2017. "The impact of latency sensitive trading on high frequency arbitrage opportunities," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 91-102.
    5. Nidhi Aggarwal & Venkatesh Panchapagesan & Susan Thomas, 2019. "When do regulatory interventions work?," Indira Gandhi Institute of Development Research, Mumbai Working Papers 2019-011, Indira Gandhi Institute of Development Research, Mumbai, India.
    6. Breckenfelder, Johannes, 2019. "Competition among high-frequency traders, and market quality," Working Paper Series 2290, European Central Bank.
    7. Serbera, Jean-Philippe & Paumard, Pascal, 2016. "The fall of high-frequency trading: A survey of competition and profits," Research in International Business and Finance, Elsevier, vol. 36(C), pages 271-287.
    8. Viktor Manahov, 2018. "The rise of the machines in commodities markets: new evidence obtained using Strongly Typed Genetic Programming," Annals of Operations Research, Springer, vol. 260(1), pages 321-352, January.
    9. Upson, James & Van Ness, Robert A., 2017. "Multiple markets, algorithmic trading, and market liquidity," Journal of Financial Markets, Elsevier, vol. 32(C), pages 49-68.
    10. Lepone, Andrew & Wen, Jun & Yang, Jin Young, 2018. "Message traffic restrictions and relative pricing efficiency: Evidence from index futures contracts and exchange-traded funds," Pacific-Basin Finance Journal, Elsevier, vol. 51(C), pages 366-375.
    11. Yang, Haijun & Ge, Hengshun & Luo, Ying, 2020. "The optimal bid-ask price strategies of high-frequency trading and the effect on market liquidity," Research in International Business and Finance, Elsevier, vol. 53(C).
    12. OUATTARA, Aboudou, 2016. "Impact of the transition to continous trading on emerging financial market's liquidity : Case study of the West Africa Regional Exchange Market (BRVM)," MPRA Paper 75391, University Library of Munich, Germany.
    13. Manahov, Viktor, 2016. "A note on the relationship between high-frequency trading and latency arbitrage," International Review of Financial Analysis, Elsevier, vol. 47(C), pages 281-296.
    14. Tian, Xiao & Do, Binh & Duong, Huu Nhan & Kalev, Petko S., 2015. "Liquidity provision and informed trading by individual investors," Pacific-Basin Finance Journal, Elsevier, vol. 35(PA), pages 143-162.
    15. Frino, Alex & Mollica, Vito & Monaco, Eleonora & Palumbo, Riccardo, 2017. "The effect of algorithmic trading on market liquidity: Evidence around earnings announcements on Borsa Italiana," Pacific-Basin Finance Journal, Elsevier, vol. 45(C), pages 82-90.
    16. Wang, Qin & Zhang, Jun, 2015. "Does individual investor trading impact firm valuation?," Journal of Corporate Finance, Elsevier, vol. 35(C), pages 120-135.

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