Combining Market and Accounting-Based Models for Credit Scoring Using a Classification Scheme Based on Support Vector Machines

Abstract

Credit risk rating is a very important issue for both banks and companies, especially in periods of economic recession. There are many different approaches and methods which have been developed over the years. The aim of this paper is to create a credit risk rating model combining the option-based approach of Black, Scholes, and Merton with an accounting based approach which uses financial ratios. While the market model is well-suited for listed firms, the proposed approach illustrates that it can also be useful for non-listed ones. In particular, the option-based model is implemented to a group of listed firms and its results are applied in order to develop a model for credit risk evaluation of non-listed firms, using financial ratios. This approach is tested on a sample of Greek firms and the results are compared to other already established models.

Keywords: Credit risk, Black-Scholes-Merton model, Credit rating, Support vector machines

JEL Classification: G13, G33, C45, C52