Evolving Trading Rule-Based Policies

Created by W.Langdon from gp-bibliography.bib Revision:1.2031

@InProceedings{bradley:2010:evofin,
  author =       "Robert Gregory Bradley and Anthony Brabazon and 
                 Michael O'Neill",
  title =        "Evolving Trading Rule-Based Policies",
  booktitle =    "EvoFIN",
  year =         "2010",
  editor =       "Cecilia {Di Chio} and Anthony Brabazon and 
                 Gianni A. {Di Caro} and Marc Ebner and Muddassar Farooq and 
                 Andreas Fink and Jorn Grahl and Gary Greenfield and 
                 Penousal Machado and Michael O'Neill and 
                 Ernesto Tarantino and Neil Urquhart",
  volume =       "6025",
  series =       "LNCS",
  pages =        "251--260",
  address =      "Istanbul",
  month =        "7-9 " # apr,
  organisation = "EvoStar",
  publisher =    "Springer",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  isbn13 =       "978-3-642-12241-5",
  doi =          "doi:10.1007/978-3-642-12242-2_26",
  abstract =     "Trading-rule representation is an important factor to
                 consider when designing a quantitative trading system.
                 This study implements a trading strategy as a
                 rule-based policy. The result is an intuitive
                 human-readable format which allows for seamless
                 integration of domain knowledge. The components of a
                 policy are specified and represented as a set of
                 rewrite rules in a context-free grammar. These rewrite
                 rules define how the components can be legally
                 assembled. Thus, strategies derived from the grammar
                 are well-formed, domain-specific, solutions. A
                 grammar-based Evolutionary Algorithm, Grammatical
                 Evolution (GE), is then employed to automatically
                 evolve intra-day trading strategies for the U.S. Stock
                 Market. The GE methodology managed to discover
                 profitable rules with realistic transaction costs
                 included. The paper concludes with a number of
                 suggestions for future work.",
  notes =        "EvoFIN'2010 held in conjunction with EuroGP'2010
                 EvoCOP2010 EvoBIO2010",
}

Genetic Programming entries for Robert Gregory Bradley Anthony Brabazon Michael O'Neill