Biologically Inspired Algorithms for Financial Modelling

  • Kaboudan M
  • 71

    Readers

    Mendeley users who have this article in their library.
  • N/A

    Citations

    Citations of this article.

Abstract

Grammatical Evolution (GE) is a novel data driven,
model induction tool, inspired by the biological
genetoprotein 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)percent across a five-fold cross validation.

Get free article suggestions today

Mendeley saves you time finding and organizing research

Sign up here
Already have an account ?Sign in

Find this document

Authors

  • Mak Kaboudan

Cite this document

Choose a citation style from the tabs below

Save time finding and organizing research with Mendeley

Sign up for free