Adaptive Trading with Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{dempsey:2006:CEC,
  author =       "Ian Dempsey and Michael O'Neill and Anthony Brabazon",
  title =        "Adaptive Trading with Grammatical Evolution",
  booktitle =    "Proceedings of the 2006 IEEE Congress on Evolutionary
                 Computation",
  year =         "2006",
  pages =        "9137--9142",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  ISBN =         "0-7803-9487-9",
  DOI =          "doi:10.1109/CEC.2006.1688631",
  size =         "6 pages",
  abstract =     "This study reports on the performance of an on-line
                 evolutionary automatic programming methodology for
                 uncovering technical trading rules for the S&P 500 and
                 Nikkei 225 indices. The system adopts a variable sized
                 investment strategy based on the strength of the
                 signals produced by the trading rules. Two approaches
                 are explored, one using a single population of rules
                 which is adapted over the lifetime of the data and
                 another whereby a new population is created for each
                 step across the time series. The results show
                 profitable performance for the trading periods explored
                 with clear advantages for an adaptive population of
                 rules.",
  notes =        "WCCI 2006 - A joint meeting of the IEEE, the EPS, and
                 the IEE.",
}

Genetic Programming entries for Ian Dempsey Michael O'Neill Anthony Brabazon

Citations