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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.

Suggested Citation

  • Terrence Hendershott & Ryan Riordan, 2009. "Algorithmic Trading and Information," Working Papers 09-08, NET Institute, revised Aug 2009.
    • Handle: RePEc:net:wpaper:0908
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    References listed on IDEAS

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    1. Hasbrouck, Joel, 1991. "Measuring the Information Content of Stock Trades," Journal of Finance, American Finance Association, vol. 46(1), pages 179-207, March.
    2. repec:bla:jfinan:v:58:y:2003:i:6:p:2637-2666 is not listed on IDEAS
    3. 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 1655-1689, December.
    4. Bessembinder, Hendrik, 2003. "Issues in assessing trade execution costs," Journal of Financial Markets, Elsevier, vol. 6(3), pages 233-257, May.
    5. 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.
    6. Parlour, Christine A, 1998. "Price Dynamics in Limit Order Markets," The Review of Financial Studies, Society for Financial Studies, vol. 11(4), pages 789-816.
    7. Mitchell A. Petersen, 2009. "Estimating Standard Errors in Finance Panel Data Sets: Comparing Approaches," The Review of Financial Studies, Society for Financial Studies, vol. 22(1), pages 435-480, January.
    8. Lo, Andrew W. & MacKinlay, A. Craig & Zhang, June, 2002. "Econometric models of limit-order executions," Journal of Financial Economics, Elsevier, vol. 65(1), pages 31-71, July.
    9. Copeland, Thomas E & Galai, Dan, 1983. "Information Effects on the Bid-Ask Spread," Journal of Finance, American Finance Association, vol. 38(5), pages 1457-1469, December.
    10. Kumar Venkataraman, 2001. "Automated Versus Floor Trading: An Analysis of Execution Costs on the Paris and New York Exchanges," Journal of Finance, American Finance Association, vol. 56(4), pages 1445-1485, August.
    11. Harald Hau, 2001. "Location Matters: An Examination of Trading Profits," Journal of Finance, American Finance Association, vol. 56(5), pages 1959-1983, October.
    12. Lee, Charles M C & Ready, Mark J, 1991. "Inferring Trade Direction from Intraday Data," Journal of Finance, American Finance Association, vol. 46(2), pages 733-746, June.
    13. 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.
    14. Ranaldo, Angelo, 2004. "Order aggressiveness in limit order book markets," Journal of Financial Markets, Elsevier, vol. 7(1), pages 53-74, January.
    15. Michael J. Barclay & Terrence Hendershott & D. Timothy McCormick, 2003. "Competition among Trading Venues: Information and Trading on Electronic Communications Networks," Journal of Finance, American Finance Association, vol. 58(6), pages 2637-2665, December.
    16. 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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    More about this item

    Keywords

    Algorithmic trading; information technology; price discovery; market microstructure; price efficiency;
    All these keywords.

    JEL classification:

    • D4 - Microeconomics - - Market Structure, Pricing, and Design
    • D8 - Microeconomics - - Information, Knowledge, and Uncertainty
    • G1 - Financial Economics - - General Financial Markets

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    This paper has been announced in the following NEP Reports:

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