Determinants of credit ratings in Asian listed firms: evidence from discriminant analysis and logit method

The purpose of this paper is to develop a new model that can help to determine the credit ratings. Moreover, a specific new credit rating index is developed by using non-financial listed Asian companies rated by standard and poor. Dependent variable is dummy in nature therefore, discriminant analysis (DA) and logistic regression techniques, are used for transforming financial ratios and macroeconomic factors. The credit rating index is evaluated with the help of 12 financial and macroeconomic variables. Results of DA and logistic regression, shows that seven variables are significant for developing new credit rating index. These variables are leverage, tangibility, size, profitability, total assets turnover ratio, real interest rate, inflation, and domestic stock market (DSM). Prediction accuracy of the DA and logit model is 71.5% and 78% respectively. It is evident that the suggested variables in the models have the potential to be used practically by corporations to determine the credit ratings internally.