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Le trading algorithmique

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  • Victor Lebreton

    (CES - Centre d'économie de la Sorbonne - UP1 - Université Paris 1 Panthéon-Sorbonne - CNRS - Centre National de la Recherche Scientifique)

Abstract

The algorithmic trading comes from digitalisation of the processing of trading assets on financial markets. Since 1980 the computerization of the stock market offers real time processing of financial information. This technological revolution has offered processes and mathematic methods to identify best return on transactions. Current research relates to autonomous transaction systems programmed in certain periods and some algorithms. This offers return opportunities where traders can not intervene. There are about thirty algorithms to assist the traders, the best known are the VWAP, the TWAP, TVOL. The algorithms offer the latest strategies and decision-making are the subject of much research. These advances in modeling decision-making autonomous agent can envisage a rich future for these technologies, the players already in use for more than 30% of their trading.

Suggested Citation

  • Victor Lebreton, 2007. "Le trading algorithmique," Post-Print hal-00332823, HAL.
  • Handle: RePEc:hal:journl:hal-00332823
    Note: View the original document on HAL open archive server: https://hal.science/hal-00332823v3
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    References listed on IDEAS

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    1. Brailsford, Timothy J. & Frino, Alex & Hodgson, Allan & West, Andrew, 1999. "Stock market automation and the transmission of information between spot and futures markets," Journal of Multinational Financial Management, Elsevier, vol. 9(3-4), pages 247-264, November.
    2. Bollerslev, Tim & Domowitz, Ian & Wang, Jianxin, 1997. "Order flow and the bid-ask spread: An empirical probability model of screen-based trading," Journal of Economic Dynamics and Control, Elsevier, vol. 21(8-9), pages 1471-1491, June.
    3. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. "Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, vol. 47(5), pages 1731-1764, December.
    4. Jean-Philippe Bouchaud & Marc Mezard & Marc Potters, 2002. "Statistical properties of stock order books: empirical results and models," Science & Finance (CFM) working paper archive 0203511, Science & Finance, Capital Fund Management.
    5. Mark Austin & Graham Bates & Michael Dempster & Vasco Leemans & Stacy Williams, 2004. "Adaptive systems for foreign exchange trading," Quantitative Finance, Taylor & Francis Journals, vol. 4(4), pages 37-45.
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