Investors, issuers, academicians, and capital market regulators alike, have been increasingly focusing their attention on rating consistency. The purpose of this study is to improve the credit rating system in Korea by empirically examining the useful...
Investors, issuers, academicians, and capital market regulators alike, have been increasingly focusing their attention on rating consistency. The purpose of this study is to improve the credit rating system in Korea by empirically examining the usefulness of financial information in forecasting of credit rating.
There is considerable variation as to which credit factors are most relevant to a given industry at a time. The sample consists of 596 rating disclosures by KMCC, KIS, and NICE over the 1998~2001 period. The sample contains both 415 investment-grade and 181 non-investment-grade disclosures. There are very important differences between investment-grade and non-investment-grade companies in terms of the relative weight issues. Investment-grade/non-investment-grade are assigned as the dependent variables, and financial variables including capital market are assigned as the independent variables. The Logit analysis technique is used in this research.
The results of the Logit analysis have the highest hit-ratio for several financial variables for the credit rating forecast(eg. firm size, dividend ratio etc.). Empirical findings of this research show the significant variables which are firm size and dividend policy, and which are also very statistically significant for the credit rating prediction model. Here, the analysis focuses on the financial information which is very useful information for credit ratings.