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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 the role of high-frequency trading in a dynamic limit order market. Being fast is valuable because it enables traders to revise outstanding limit orders upon news arrivals when interacting with slow market participants. On the one hand, the existence of fast traders can help to reduce the inefficiency that is rooted in the risk of being "picked off" after unfavourable price movements and therefore allows more gains from trade to be realized. On the other hand, slow traders face a relative loss in bargaining power which leads them to strategically submit limit orders with a lower execution probability, thereby reducing trade. Due to this negative externality, the equilibrium level of investment is always welfare-reducing. The model generates additional testable implications regarding the effects of high-frequency trading on order flow statistics.

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    File URL: http://mpra.ub.uni-muenchen.de/44621/
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    File URL: http://mpra.ub.uni-muenchen.de/52569/
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    Bibliographic Info

    Paper provided by University Library of Munich, Germany in its series MPRA Paper with number 44621.

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    Date of creation: Jul 2012
    Date of revision: Jan 2013
    Handle: RePEc:pra:mprapa:44621

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    Related research

    Keywords: High-frequency trading; Limit Order Market;

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    References

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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 980, Board of Governors of the Federal Reserve System (U.S.).
    2. 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.
    3. Liu, Wai-Man, 2009. "Monitoring and limit order submission risks," Journal of Financial Markets, Elsevier, vol. 12(1), pages 107-141, February.
    4. 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, 02.
    5. Garvey, Ryan & Wu, Fei, 2010. "Speed, distance, and electronic trading: New evidence on why location matters," Journal of Financial Markets, Elsevier, vol. 13(4), pages 367-396, November.
    6. Jean-Edouard Colliard & Thierry Foucault, 2012. "Trading Fees and Efficiency in Limit Order Markets," Review of Financial Studies, Society for Financial Studies, vol. 25(11), pages 3389-3421.
    7. 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.
    8. 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.
    9. 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.
    10. Álvaro Cartea & José Penalva, 2011. "Where is the value in high frequency trading?," Banco de Espa�a Working Papers 1111, Banco de Espa�a.
    11. Copeland, Thomas E & Galai, Dan, 1983. " Information Effects on the Bid-Ask Spread," Journal of Finance, American Finance Association, vol. 38(5), pages 1457-69, December.
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    Cited by:
    1. Kervel, V.L. van, 2013. "Competition between stock exchanges and optimal trading," Open Access publications from Tilburg University urn:nbn:nl:ui:12-5663709, Tilburg University.
    2. Jonathan Brogaard & Corey Garriott & Anna Pomeranets, 2014. "High-Frequency Trading Competition," Working Papers 14-19, Bank of Canada.

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