Credit Rating with pi Grammatical Evolution

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

@InProceedings{brabazon:2005:CRWpiGE,
  author =       "Anthony Brabazon and Michael O'Neill",
  title =        "Credit Rating with pi Grammatical Evolution",
  booktitle =    "Proceedings of Computer Methods and Systems
                 Conference",
  year =         "2005",
  editor =       "R. Tadeusiewicz and A. Ligeza and M. Szymkat",
  volume =       "1",
  pages =        "253--260",
  address =      "Krakow, Poland",
  publisher_address = "Krakow",
  month =        "14-16 " # nov,
  publisher =    "Oprogramowanie Naukowo-Techniczne Tadeusiewicz",
  keywords =     "genetic algorithms, genetic programming, grammatical
                 evolution",
  ISBN =         "83-916420-3-8",
  abstract =     "This study examines the utility of pi Grammatical
                 Evolution in modelling the corporate bond-issuer credit
                 rating process, using information drawn from the
                 financial statements of bond-issuing firms. Financial
                 data, and the associated Standard and Poor's
                 issuer-credit ratings of 791 US firms, drawn from the
                 year 1999/2000 are used to train and test the model.
                 The best developed model was found to be able to
                 discriminate in-sample (out-of-sample) between
                 investment grade and junk bond ratings with an average
                 accuracy of 86 (87)percent across a five-fold cross
                 validation.",
}

Genetic Programming entries for Anthony Brabazon Michael O'Neill