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Make-take decisions under high-frequency trading competition

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  • Bernales, Alejandro

Abstract

The make-take preferences of investors depend on high-frequency trading (HFT) competition, under which HFT firms endogenously acquire speed and informational advantages. In the case where there are many HFT firms in the market, they compete more through limit orders; meanwhile, in the case with few HFT firms, they compete more through market orders that “pick-off" limit orders coming from the big crowd of slow traders. In the former (latter) case, additional HFT competition improves (damage) liquidity. In both cases, HFT competition improves informational efficiency and reduces microstructure noise. Finally, I use the model to analyze potential regulations under HFT competition.

Suggested Citation

  • Bernales, Alejandro, 2019. "Make-take decisions under high-frequency trading competition," Journal of Financial Markets, Elsevier, vol. 45(C), pages 1-18.
  • Handle: RePEc:eee:finmar:v:45:y:2019:i:c:p:1-18
    DOI: 10.1016/j.finmar.2019.05.001
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    References listed on IDEAS

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    1. Foucault, Thierry, 1998. "Order Flow Composition and Trading Costs in Dynamic Limit Order Markets," CEPR Discussion Papers 1817, C.E.P.R. Discussion Papers.
    2. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2005. "Limit Order Book as a Market for Liquidity," Review of Financial Studies, Society for Financial Studies, vol. 18(4), pages 1171-1217.
    3. Burton Hollifield & Robert A. Miller & Patrik Sandås & Joshua Slive, 2006. "Estimating the Gains from Trade in Limit‐Order Markets," Journal of Finance, American Finance Association, vol. 61(6), pages 2753-2804, December.
    4. Thierry Foucault & Johan Hombert & Ioanid Roşu, 2016. "News Trading and Speed," Journal of Finance, American Finance Association, vol. 71(1), pages 335-382, February.
    5. Grossman, Sanford J & Stiglitz, Joseph E, 1980. "On the Impossibility of Informationally Efficient Markets," American Economic Review, American Economic Association, vol. 70(3), pages 393-408, June.
    6. Pakes, Ariel & McGuire, Paul, 2001. "Stochastic Algorithms, Symmetric Markov Perfect Equilibrium, and the 'Curse' of Dimensionality," Econometrica, Econometric Society, vol. 69(5), pages 1261-1281, September.
    7. Parlour, Christine A, 1998. "Price Dynamics in Limit Order Markets," Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 789-816.
    8. Albert J. Menkveld & Marius A. Zoican, 2017. "Need for Speed? Exchange Latency and Liquidity," Review of Financial Studies, Society for Financial Studies, vol. 30(4), pages 1188-1228.
    9. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    10. Goettler, Ronald L. & Parlour, Christine A. & Rajan, Uday, 2009. "Informed traders and limit order markets," Journal of Financial Economics, Elsevier, vol. 93(1), pages 67-87, July.
    11. Andrei Kirilenko & Albert S. Kyle & Mehrdad Samadi & Tugkan Tuzun, 2017. "The Flash Crash: High-Frequency Trading in an Electronic Market," Journal of Finance, American Finance Association, vol. 72(3), pages 967-998, June.
    12. Maskin, Eric & Tirole, Jean, 2001. "Markov Perfect Equilibrium: I. Observable Actions," Journal of Economic Theory, Elsevier, vol. 100(2), pages 191-219, October.
    13. Jean†Edouard Colliard & Peter Hoffmann, 2017. "Financial Transaction Taxes, Market Composition, and Liquidity," Journal of Finance, American Finance Association, vol. 72(6), pages 2685-2716, December.
    14. Jonathan Brogaard & Terrence Hendershott & Ryan Riordan, 2014. "High-Frequency Trading and Price Discovery," Review of Financial Studies, Society for Financial Studies, vol. 27(8), pages 2267-2306.
    15. Ekkehart Boehmer & Dan Li & Gideon Saar, 2018. "The Competitive Landscape of High-Frequency Trading Firms," Review of Financial Studies, Society for Financial Studies, vol. 31(6), pages 2227-2276.
    16. Breckenfelder, Johannes, 2013. "Competition between high-frequency traders, and market quality," MPRA Paper 66715, University Library of Munich, Germany, revised Dec 2013.
    17. Ronald L. Goettler & Christine A. Parlour & Uday Rajan, 2005. "Equilibrium in a Dynamic Limit Order Market," Journal of Finance, American Finance Association, vol. 60(5), pages 2149-2192, October.
    18. Hagströmer, Björn & Nordén, Lars, 2013. "The diversity of high-frequency traders," Journal of Financial Markets, Elsevier, vol. 16(4), pages 741-770.
    19. Alain P. Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2014. "Rise of the Machines: Algorithmic Trading in the Foreign Exchange Market," Journal of Finance, American Finance Association, vol. 69(5), pages 2045-2084, October.
    20. 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.
    21. Hoffmann, Peter, 2014. "A dynamic limit order market with fast and slow traders," Journal of Financial Economics, Elsevier, vol. 113(1), pages 156-169.
    22. Pankaj K. Jain, 2005. "Financial Market Design and the Equity Premium: Electronic versus Floor Trading," Journal of Finance, American Finance Association, vol. 60(6), pages 2955-2985, December.
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    Cited by:

    1. Ladley, Daniel, 2020. "The high frequency trade off between speed and sophistication," Journal of Economic Dynamics and Control, Elsevier, vol. 116(C).

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    More about this item

    Keywords

    Make-take decisions; High-frequency trading competition; Limit order market; Market quality; Welfare;
    All these keywords.

    JEL classification:

    • C63 - Mathematical and Quantitative Methods - - Mathematical Methods; Programming Models; Mathematical and Simulation Modeling - - - Computational Techniques
    • C73 - Mathematical and Quantitative Methods - - Game Theory and Bargaining Theory - - - Stochastic and Dynamic Games; Evolutionary Games
    • G11 - Financial Economics - - General Financial Markets - - - Portfolio Choice; Investment Decisions
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading

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