Credit Classification Using Grammatical Evolution

Grammatical Evolution (GE) is a novel data driven, model induction tool, inspired by the biological geneto-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 issuercredit 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 investmentgrade and junk bond ratings with an average accuracy of 87.59 (84.92)% across a five-fold cross validation.