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Algorithmic Trading and Information

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    Abstract

    We examine algorithmic trades (AT) and their role in the price discovery process in the 30 DAX stocks on the Deutsche Boerse. AT liquidity demand represents 52% of volume and AT supplies liquidity on 50% of volume. AT act strategically by monitoring the market for liquidity and deviations of price from fundamental value. AT consume liquidity when it is cheap and supply liquidity when it is expensive. AT contribute more to the efficient price by placing more efficient quotes and AT demanding liquidity to move the prices towards the efficient price.

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    File URL: http://www.netinst.org/Hendershott_Riordan_09-08.pdf
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    Bibliographic Info

    Paper provided by NET Institute in its series Working Papers with number 09-08.

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    Length: 40 pages
    Date of creation: Mar 2009
    Date of revision: Aug 2009
    Handle: RePEc:net:wpaper:0908

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    Related research

    Keywords: Algorithmic trading; information technology; price discovery; market microstructure; price efficiency;

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    1. Keim, Donald B. & Madhavan, Ananth, 1995. "Anatomy of the trading process Empirical evidence on the behavior of institutional traders," Journal of Financial Economics, Elsevier, vol. 37(3), pages 371-398, March.
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    8. Biais, Bruno & Hillion, Pierre & Spatt, Chester, 1995. " An Empirical Analysis of the Limit Order Book and the Order Flow in the Paris Bourse," Journal of Finance, American Finance Association, vol. 50(5), pages 1655-89, December.
    9. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
    10. 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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