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  • 标题:Credit Classification Using Grammatical Evolution
  • 本地全文:下载
  • 作者:A. Brabazon ; M. O'Neill
  • 期刊名称:Informatica
  • 印刷版ISSN:1514-8327
  • 电子版ISSN:1854-3871
  • 出版年度:2006
  • 卷号:30
  • 期号:3
  • 出版社:The Slovene Society Informatika, Ljubljana
  • 摘要:Grammatical Evolution (GE) is a novel data driven, model induction tool, inspired by the biological gene- to-protein mapping process. This study provides an introduction to GE, and demonstrates the methodology by applying it to model the corporate bond-issuer credit rating process, using information drawn from the financial statements of bond-issuing firms. Financial data and the associated Standard & 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 87.59 (84.92)% across a five-fold cross validation. Povzetek: Metoda gramatiˇ cne evolucije je uporabljena za klasificiranje kreditov.
  • 关键词:grammatical evolution; credit rating; bond rating
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