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Evolving Market Index Trading Rules Using Grammatical Evolution

  • Michael O’Neill
  • Anthony Brabazon
  • Conor Ryan
  • J. J. Collins
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 2037)

Abstract

This study examines the potential of an evolutionary automatic programming methodology to uncover a series of useful technical trading rules for the UK FTSE 100 stock index. Index values for the period 26/4/1984 to 4/12/1997 are used to train and test the model. The preliminary findings indicate that the methodology has much potential, outperforming the benchmark strategy adopted.

Keywords

Trading System Stock Index Trading Rule Technical Indicator Average Indicator 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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Copyright information

© Springer-Verlag Berlin Heidelberg 2001

Authors and Affiliations

  • Michael O’Neill
    • 2
  • Anthony Brabazon
    • 1
  • Conor Ryan
    • 2
  • J. J. Collins
    • 2
  1. 1.Dept. Of AccountancyUniversity College DublinIreland
  2. 2.Dept. Of Computer Science And Information SystemsUniversity of LimerickIreland

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