Abstract
Credit ratings issued by international agencies are extensively used in practice to support investment and financing decisions. Furthermore, a considerable portion of the financial research has been devoted to the analysis of credit ratings, in terms of their effectiveness, and practical implications. This paper explores the development of appropriate models to replicate the credit ratings issued by a rating agency. The analysis is based on a multicriteria classification method used in the development of the model. Special focus is laid on testing the out-of-time and out-of-sample effectiveness of the models and a comparison is performed with other parametric and non-parametric classification methods. The results indicate that using publicly available financial data, it is possible to replicate the credit ratings of the firms with a satisfactory accuracy.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
Belkaoui, A. (1983). Industrial Bonds and the Rating Process. Greenwood Press, Westport, CT.
Chandy, P.R. and Duett, E.H. (1990). Commercial paper rating models. Quarterly Journal of Business and Economics, 29(4) 79–101.
Dietterich, T.G. and Bakiri, G. (1995). Solving multiclass learning problems via error-correcting output codes. Journal of Artificial Intelligence Research 2, 263–286.
Doumpos, M. and Zopounidis, C. (2002). Multicriteria Decision Aid Classification Methods. Kluwer Academic Publishers, Dordrecht.
Doumpos, M., Kosmidou, K., Baourakis, G. and Zopounidis, C. (2002). Credit risk assessment using a multicriteria hierarchical discrimination approach: A comparative analysis. European Journal of Operational Research 138, 392–412.
Fayyad, U.M. and Irani, K.B. (1992). On the handling of continuous-valued attributes in decision tree generation. Machine Learning 8, 87–102.
Kaplan, R.S. and Urwitz, G. (1979). Statistical models of bond ratings: A methodological inquiry. Journal of Business 52, 231–261.
Kim, J.W. (1993). Expert systems for bond rating: A comparative analysis of statistical, rule-based and neural networks systems. Expert Systems 10, 167–171.
Laitinen, E.K. (1999). Predicting a corporate credit analyst’s risk estimate by logistic and linear models. International Review of Financial Analysis 8(2), 97–121.
Peavy, J.W. III. and Edgar, S.M. (1984). An expanded commercial paper rating scale: Classification of industrial issuers. Journal of Business Finance and Accounting 11(3), 397–407.
Sobehart, J.R., Keenan, S. and Stein, S. (2000). Benchmarking quantitative default risk models: A validation methodology. Moody’s Investors Service Global Credit Research, March.
Treacy, W.F. and Carey, M. (2000). Credit risk rating systems at large US banks. Journal of Banking and Finance 24, 167–201.
Zopounidis, C. and Doumpos, M. (1999). A multicriteria decision aid methodology for sorting decision problems: The case of financial distress. Computational Economics 14, 197–218.
Zopounidis, C. and Doumpos, M. (2002). Multicriteria classification and sorting methods: A literature review. European Journal of Operational Research 138(2), 229–246.
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Doumpos, M., Pasiouras, F. Developing and Testing Models for Replicating Credit Ratings: A Multicriteria Approach. Comput Econ 25, 327–341 (2005). https://doi.org/10.1007/s10614-005-6412-4
Accepted:
Issue Date:
DOI: https://doi.org/10.1007/s10614-005-6412-4