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2006

A study of Taiwan's issuer credit rating systems using support vector machines

9 years 2 days ago
A study of Taiwan's issuer credit rating systems using support vector machines
By providing credit risk information, credit rating systems benefit most participants in financial markets, including issuers, investors, market regulators and intermediaries. In this paper, we propose an automatic classification model for issuer credit ratings, a type of fundamental credit rating information, by applying the support vector machine (SVM) method. This is a novel classification algorithm that is famous for dealing with high dimension classifications. We also use three new variables: stock market information, financial support by the government, and financial support by major shareholders to enhance the effectiveness of the classification. Previous research has seldom considered these variables. The data period of the input variables used in this study covers three years, while most previous research has only considered one year. We compare our SVM model with the back propagation neural network (BP), a well-known credit rating classification method. Our experiment result...
Wun-Hwa Chen, Jen-Ying Shih
Added 12 Dec 2010
Updated 12 Dec 2010
Type Journal
Year 2006
Where ESWA
Authors Wun-Hwa Chen, Jen-Ying Shih
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