Evolutionary Learning of Technical Trading Rules without Data-mining Bias

Created by W.Langdon from gp-bibliography.bib Revision:1.4549

  author =       "Alexandros Agapitos and Michael O'Neill and 
                 Anthony Brabazon",
  title =        "Evolutionary Learning of Technical Trading Rules
                 without Data-mining Bias",
  booktitle =    "PPSN 2010 11th International Conference on Parallel
                 Problem Solving From Nature",
  pages =        "294--303",
  year =         "2010",
  volume =       "6238",
  editor =       "Robert Schaefer and Carlos Cotta and 
                 Joanna Kolodziej and Guenter Rudolph",
  publisher =    "Springer",
  series =       "Lecture Notes in Computer Science",
  isbn13 =       "978-3-642-15843-8",
  address =      "Krakow, Poland",
  month =        "11-15 " # sep,
  keywords =     "genetic algorithms, genetic programming",
  DOI =          "doi:10.1007/978-3-642-15844-5_30",
  abstract =     "In this paper we investigate the profitability of
                 evolved technical trading rules when controlling for
                 data-mining bias. For the first time in the
                 evolutionary computation literature, a comprehensive
                 test for a rule's statistical significance using
                 Hansen's Superior Predictive Ability is explicitly
                 taken into account in the fitness function, and
                 multi-objective evolutionary optimisation is employed
                 to drive the search towards individual rules with
                 better generalisation abilities. Empirical results on a
                 spot foreign-exchange market index suggest that
                 increased out-of-sample performance can be obtained
                 after accounting for data-mining bias effects in a
                 multi-objective fitness function, as compared to a
                 single-criterion fitness measure that considers solely
                 the average return.",

Genetic Programming entries for Alexandros Agapitos Michael O'Neill Anthony Brabazon