Adaptive Trading with Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.4020

  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
  year =         "2006",
  pages =        "9137--9142",
  address =      "Vancouver",
  month =        "6-21 " # jul,
  publisher =    "IEEE Press",
  keywords =     "genetic algorithms, genetic programming, grammatical
  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
  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