Evolving Market Index Trading Rules using Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4524

  author =       "Michael O'Neill and Anthony Brabazon and 
                 Conor Ryan and J. J. Collins",
  title =        "Evolving Market Index Trading Rules using Grammatical
  booktitle =    "Applications of Evolutionary Computing",
  editor =       "Egbert J. W. Boers and Stefano Cagnoni and 
                 Jens Gottlieb and Emma Hart and Pier Luca Lanzi and 
                 Gunther R. Raidl and Robert E. Smith and Harald Tijink",
  year =         "2001",
  volume =       "2037",
  series =       "LNCS",
  pages =        "343--352",
  address =      "Lake Como, Italy",
  publisher_address = "Berlin",
  month =        "18-19 " # apr,
  organisation = "EvoNET",
  publisher =    "Springer-Verlag",
  keywords =     "genetic algorithms, genetic programming, grammatical
  ISBN =         "3-540-41920-9",
  URL =          "http://ncra.ucd.ie/papers/evoiasp2001.ps.gz",
  DOI =          "doi:10.1007/3-540-45365-2_36",
  size =         "10 pages",
  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
  notes =        "EvoWorkshops2001. One of the better GA for stock
                 market prediction papers",

Genetic Programming entries for Michael O'Neill Anthony Brabazon Conor Ryan John James Collins