Credit Rating: A New Quotation Approach

Abstract

Credit rating agencies rate companies and states by assigning them scores depending on their level of solvency. These scores are inversely proportional to default risk and then proportional to quotes which are proportional to bonds value. Consequently, scores are calculated depending on companies and states bankruptcy risk. In our paper, we assess company solvency using numerical symbols and an accelerating risk model. Although the Big31 rating agencies use uniformly distributed risk to rate corporate bonds, we think that the distribution should vary uniformly. Our theoretical model is based on a homogeneously risk varying path with a fluctuating speed but a constant acceleration of risk. We measure this acceleration and calculate risk intervals by using a linear regression where asset volatility represents the dependent variable, and a set of 20 company categories representing the independent variable. Comparative statics are used to illustrate our analysis. We obtain a very significant coefficient for the exogenous variable, representing homogeneous risk intervals. We use 20 classes of risk to be consistent with the “US equivalent rating”, as the Big3 rating agencies do, which allows us to determine risk classes and rate companies according to the numerical scale obtained. We compare our numerical scale to the equivalent rating tables used by Moody’s, Fitch Ratings and S&P. According to our findings, companies with a risk level under 16 are considered to be solvent, while those with a 17-to-20-risk level are considered to be in trouble. Indeed, the length of risk intervals and the risk acceleration should vary depending on industry sector and population size. Our model is useful for both public and private companies.