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A dynamic limit order market with fast and slow traders

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  • Hoffmann, Peter
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    Abstract

    We study a dynamic limit order market where agents may invest into a trading technology that grants them a speed advantage over others. Being fast is valuable because it allows limit orders to be revised quickly in the light of new information and therefore reduces the risk of being picked off. Even though this can generate more trading, the equilibrium level of investment is excessive and always generates a welfare loss because fast traders exert negative externalities on slow agents and are able to extract any surplus. If the diffusion of trading technology additionally leads to a more efficient trading process, this result may reverse completely. For sufficiently large efficiency gains, fast traders exert positive externalities on slow market participants and their presence leads to an increase in social welfare, albeit the equilibrium level of investment is below the social optimum. Our results imply that the marginal impact of investments related to algorithmic and high-frequency trading on social welfare crucially depends on the pre-investment level of market efficiency.

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    File URL: http://mpra.ub.uni-muenchen.de/52570/
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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 39855.

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    Date of creation: Jul 2012
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    Handle: RePEc:pra:mprapa:39855

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    Keywords: Algorithmic Trading; Limit Order Market; Welfare; Investment;

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    1. Alain Chaboud & Benjamin Chiquoine & Erik Hjalmarsson & Clara Vega, 2009. "Rise of the machines: algorithmic trading in the foreign exchange market," International Finance Discussion Papers, Board of Governors of the Federal Reserve System (U.S.) 980, Board of Governors of the Federal Reserve System (U.S.).
    2. FOUCAULT, Thierry & RÖELL, Ailsa & SANDAS, Patrik, 2000. "Market Making with Costly Monitoring : An Analysis of the SOES Controversy," Les Cahiers de Recherche 702, HEC Paris.
    3. Johannes A. Skjeltorp & Elvira Sojli & Wing Wah Tham, 2012. "Sunshine Trading: Flashes of Trading Intent at the NASDAQ," Tinbergen Institute Discussion Papers 12-141/IV/DSF47, Tinbergen Institute.
    4. Jean-Edouard Colliard & Thierry Foucault, 2012. "Trading Fees and Efficiency in Limit Order Markets," Review of Financial Studies, Society for Financial Studies, Society for Financial Studies, vol. 25(11), pages 3389-3421.
    5. Foucault, Thierry, 1999. "Order flow composition and trading costs in a dynamic limit order market1," Journal of Financial Markets, Elsevier, Elsevier, vol. 2(2), pages 99-134, May.
    6. Terrence Hendershott & Charles M. Jones & Albert J. Menkveld, 2011. "Does Algorithmic Trading Improve Liquidity?," Journal of Finance, American Finance Association, American Finance Association, vol. 66(1), pages 1-33, 02.
    7. Liu, Wai-Man, 2009. "Monitoring and limit order submission risks," Journal of Financial Markets, Elsevier, Elsevier, vol. 12(1), pages 107-141, February.
    8. Álvaro Cartea & José Penalva, 2011. "Where is the value in high frequency trading?," Banco de Espa�a Working Papers 1111, Banco de Espa�a.
    9. Goettler, Ronald L. & Parlour, Christine A. & Rajan, Uday, 2009. "Informed traders and limit order markets," Journal of Financial Economics, Elsevier, Elsevier, vol. 93(1), pages 67-87, July.
    10. Garvey, Ryan & Wu, Fei, 2010. "Speed, distance, and electronic trading: New evidence on why location matters," Journal of Financial Markets, Elsevier, Elsevier, vol. 13(4), pages 367-396, November.
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    Cited by:
    1. Menkveld, Albert J., 2013. "High frequency trading and the new market makers," Journal of Financial Markets, Elsevier, Elsevier, vol. 16(4), pages 712-740.

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