Credit Rating with pi Grammatical Evolution

Created by W.Langdon from gp-bibliography.bib Revision:1.8120

@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

Citations