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High Frequency Traders: Taking Advantage of Speed

Author

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  • Yacine Aït-Sahalia
  • Mehmet Saglam

Abstract

We propose a model of dynamic trading where a strategic high frequency trader receives an imperfect signal about future order flows, and exploits his speed advantage to optimize his quoting policy. We determine the provision of liquidity, order cancellations, and impact on low frequency traders as a function of both the high frequency trader's latency, and the market volatility. The model predicts that volatility leads high frequency traders to reduce their provision of liquidity. Finally, we analyze the impact of various policies designed to potentially regulate high frequency trading.

Suggested Citation

  • Yacine Aït-Sahalia & Mehmet Saglam, 2013. "High Frequency Traders: Taking Advantage of Speed," NBER Working Papers 19531, National Bureau of Economic Research, Inc.
  • Handle: RePEc:nbr:nberwo:19531
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    File URL: http://www.nber.org/papers/w19531.pdf
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    References listed on IDEAS

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    1. Emiliano Pagnotta & Thomas Philippon, 2011. "Competing on Speed," NBER Working Papers 17652, National Bureau of Economic Research, Inc.
    2. Cespa, Giovanni & Foucault, Thierry, 2008. "Insiders-outsiders, transparency and the value of the ticker," CFS Working Paper Series 2008/39, Center for Financial Studies (CFS).
    3. Thierry Foucault & Ohad Kadan & Eugene Kandel, 2013. "Liquidity Cycles and Make/Take Fees in Electronic Markets," Journal of Finance, American Finance Association, vol. 68(1), pages 299-341, February.
    4. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, vol. 16(4), pages 712-740.
    5. Hasbrouck, Joel & Saar, Gideon, 2009. "Technology and liquidity provision: The blurring of traditional definitions," Journal of Financial Markets, Elsevier, vol. 12(2), pages 143-172, May.
    6. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, vol. 66(1), pages 1-33, February.
    Full references (including those not matched with items on IDEAS)

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    Cited by:

    1. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    2. Sandrine Jacob Leal & Mauro Napoletano & Andrea Roventini & Giorgio Fagiolo, 2016. "Rock around the clock: An agent-based model of low- and high-frequency trading," Journal of Evolutionary Economics, Springer, vol. 26(1), pages 49-76, March.
    3. Giovanni Ferri & Matteo Ploner & Matteo Rizzolli, 2016. "Trading Fast and Slow: The Role Of Deliberation In Experimental Financial Markets," CERBE Working Papers wpC07, CERBE Center for Relationship Banking and Economics.
    4. Linton, O. & Mahmoodzadeh, S., 2018. "Implications of High-Frequency Trading for Security Markets," Cambridge Working Papers in Economics 1802, Faculty of Economics, University of Cambridge.
    5. Seddon, Jonathan J.J.M. & Currie, Wendy L., 2017. "A model for unpacking big data analytics in high-frequency trading," Journal of Business Research, Elsevier, vol. 70(C), pages 300-307.
    6. repec:wsi:ijfexx:v:02:y:2015:i:02:n:s2424786315500139 is not listed on IDEAS
    7. repec:scn:000ven:127602 is not listed on IDEAS

    More about this item

    JEL classification:

    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates

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