會社債等級 豫測模型

A Predicting Model of Industrial Bond Ratings

The Purpose of this study was to develop and test a model for predicting industrial bond ratings. The joint application of factor analysis and multiple discriminant analysis (MDA) , in a financial context, was found to be both viable and essential in developing and understanding the model for predicting industrial bond ratings. The final MDA model incorporating six variables correctly predicted 100 percent of the actual ratings in the estimation sample, and predicted approximately 93 percent of the ratings for a validation sample. The best replications of KIS(Korea Investors Service)'s ratings were obtained when variables relating to return on investment, financial leverage, total assets turnover, size, risk, and growth were considered. The model performed very poorly for rating Group 3 bonds. An analysis of the multiple range tests indicated that the inability of the MDA model to accurately predict rating Group 3 bonds appears to be due to a lack of statistically significant differences in the quantifiable variables considered for inclusion in the model. Such a model may be useful to the rating agencies themselves if it helps them to reduce inconsistencies among individual ratings, to form a preliminary rating of a bond, or to capture and evaluate the judgments of their raters. The model may also be useful to investors when industial bonds are not rated by KIS. Above all, the findigs should be useful to those who pay to have bonds rated. Hence, managers may form an opinion of the eventual rating and take sound actions to improve some of the financial dimensions outlined in this study in order to acheieve a better rating. These findings suggest that further research in this area could concentrate on two different aspects of the bond rating process. First further attempts could be made to replicate existing bond ratings by focusing on other quantifiable variables not include in this study. The second possible area of future research is to develop new bond rating systems which more effectively reflect the probability of financial impairment for individual bond issues.