Evolutionary Induction of Trading Models

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  author =       "Siddhartha Bhattacharyya and Kumar Mehta",
  title =        "Evolutionary Induction of Trading Models",
  booktitle =    "Evolutionary Computation in Economics and Finance",
  publisher =    "Physica Verlag",
  year =         "2002",
  editor =       "Shu-Heng Chen",
  volume =       "100",
  series =       "Studies in Fuzziness and Soft Computing",
  chapter =      "17",
  pages =        "311--332",
  month =        "2002",
  keywords =     "genetic algorithms, genetic programming",
  ISBN =         "3-7908-1476-8",
  URL =          "http://tigger.uic.edu/~sidb/papers/EvolInductionOfTradingModels.pdf",
  DOI =          "doi:10.1007/978-3-7908-1784-3_17",
  abstract =     "Financial markets data present a challenging
                 opportunity for the learning of complex patterns not
                 readily discernable. This paper investigates the use of
                 genetic algorithms for the mining of financial
                 time-series for patterns aimed at the provision of
                 trading decision models. A simple yet flexible
                 representation for trading rules is proposed, and
                 issues pertaining to fitness evaluation examined. Two
                 key issues in fitness evaluation, the design of a
                 suitable fitness function reflecting desired trading
                 characteristics and choice of appropriate training
                 duration, are discussed and empirically examined. Two
                 basic measures are also proposed for characterising
                 rules obtained with alternate fitness criteria.",
  size =         "22 pages",

Genetic Programming entries for Siddhartha Bhattacharyya Kumar Mehta