Forecasting credit ratings Using ANN and statistical techniques

Kuldeep Kumar, John D Haynes

Research output: Contribution to journalArticleResearchpeer-review

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Abstract

In a liberal environment the conceptual importance of credit rating has increased significantly. The objective of this study is to explore and find out the effect of the financial performance data of a firm relative to the credit rating of a debt issue of that firm. The study also proposes to capture the relationship, if any, between financial performance data and credit rating given by experts in an appropriate model. Financial data relevant to debt issue ratings are obtained from the publications of a premier credit rating agency in India. Data analysis involved the building of a model using conventional multiple linear discriminant analysis and Artificial Neural Network Systems. Artificial Neural Networks (ANN) model was found to be superior to the discriminant analysis model. The ANN model can be used to increase speed and efficiency of the rating process in practical applications. In addition, if experts provide better-input data, it can be relied upon to provide an automatic rating to a significant extent.
Original languageEnglish
Pages (from-to)91-108
Number of pages18
JournalInternational Journal of Business Studies
Volume11
Issue number1
Publication statusPublished - 1 Jun 2003

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Rating
Artificial neural network
Credit rating
Discriminant analysis
Network model
Debt
Financial performance
Credit rating agencies
Financial data
India

Cite this

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Forecasting credit ratings Using ANN and statistical techniques. / Kumar, Kuldeep; Haynes, John D.

In: International Journal of Business Studies, Vol. 11, No. 1, 01.06.2003, p. 91-108.

Research output: Contribution to journalArticleResearchpeer-review

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