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Comparisons of the corporate credit rating model power under various conditions
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 Title & Authors
Comparisons of the corporate credit rating model power under various conditions
Ha, Jeongcheol; Kim, Soojin;
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This study aims to compare the model power in developing corporate credit rating models and to suggest a good way to build models based on the characteristic of data. Among many measurement methods, AR is used to measure the model power under various conditions. SAS/MACRO is in use for similar repetitions to reduce time to build models under several combination of conditions. A corporate credit rating model is composed of two sub-models; a credit scoring model and a default prediction model. We verify that the latter performs better than the former under various conditions. From the result of size comparisons, models of large size corporate are more powerful and more meaningful in financial viewpoint than those of small size corporate. As a corporate size gets smaller, the gap between sub-models becomes huge and the effect of outliers becomes serious.
AR;corporate credit rating model;financial model;SAS/MACRO;
 Cited by
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