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Can channel pattern trading be profitably automated?

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  • M. A. H. Dempster
  • C. M. Jones
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    Abstract

    Financial markets, such as the global foreign exchange (FX) market, often exhibit trending behaviour. Within such trends, the market level oscillates with changes in market consensus. Continued oscillations of this type result in the formation of wave patterns within the underlying trend known as channels, which are used by technical analysts as trade entry signals. A sample space of such channels has been constructed from a set of US dollar/British pound Spot FX tick data from 1989-1997 using pattern recognition algorithms and the profitability of trading using such patterns has been estimated. A number of attributes of the resulting collection of channels has been subjected to statistical analysis with the aim of classifying patterns that can be traded profitably using a number of simple trading rules. Results of this analysis show that there exist statistically significant links between the channels' attributes and profitability.

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    Bibliographic Info

    Article provided by Taylor & Francis Journals in its journal The European Journal of Finance.

    Volume (Year): 8 (2002)
    Issue (Month): 3 ()
    Pages: 275-301

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    Handle: RePEc:taf:eurjfi:v:8:y:2002:i:3:p:275-301

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    Related research

    Keywords: Technical Analysis; Technical Trading; Currency Trading; Intra; High Frequency Financial Data; Multivariate Discriminant Analysis; Pattern Recognition;

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    1. Neely, Christopher J. & Weller, Paul A., 2001. "Technical analysis and central bank intervention," Journal of International Money and Finance, Elsevier, Elsevier, vol. 20(7), pages 949-970, December.
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    6. Allan Timmermann & Halbert White & Ryan Sullivan, 1998. "Data-Snooping, Technical Trading, Rule Performance and the Bootstrap," FMG Discussion Papers, Financial Markets Group dp303, Financial Markets Group.
    7. Brock, William & Lakonishok, Josef & LeBaron, Blake, 1992. " Simple Technical Trading Rules and the Stochastic Properties of Stock Returns," Journal of Finance, American Finance Association, American Finance Association, vol. 47(5), pages 1731-64, December.
    8. Allen, Franklin & Karjalainen, Risto, 1999. "Using genetic algorithms to find technical trading rules," Journal of Financial Economics, Elsevier, Elsevier, vol. 51(2), pages 245-271, February.
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    Cited by:
    1. Stephan Schulmeister, 2005. "The Interaction between Technical Currency Trading and Exchange Rate Fluctuations," Finance, EconWPA 0512033, EconWPA.
    2. Manahov, Viktor & Hudson, Robert & Gebka, Bartosz, 2014. "Does high frequency trading affect technical analysis and market efficiency? And if so, how?," Journal of International Financial Markets, Institutions and Money, Elsevier, Elsevier, vol. 28(C), pages 131-157.

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