We provide a rationale for the use for credit ratings even when ratings contain no new information about a risky security (such as in the case of sovereign debt). In our model, an investor contracts with an manager who invests in a risky bond. The bond’s return depends in part on the state. The state is known to both investor and manager, but unverifiable to a third party and therefore non-cont...

In this paper models of default prediction conditional on financial statements of Austrian firms are presented. Apart from giving a discussion on the suggested 65 variables the issue of potential problems in developing rating models is raised and possible solutions are reviewed. A unique data set on credit risk analysis for the Austrian market is constructed and used to derive rating models for...

We review different methods for simulating credit migrations in a nonparametric and discrete or continuous-time Markov chain framework. We suggest the application of a factor model approach in combination with the use of copulas for the joint dynamics of credit rating changes. While there are several applications of copulas in credit risk for modeling joint defaults, it lacks of the same intere...

This paper presents the first comprehensive test of whether well-known conflicts of interest at bond rating agencies importantly influence their actions. This hypothesis is tested against the alternative that rating agency actions are primarily influenced by a countervailing incentive to protect their reputations as delegated monitors. These two hypotheses generate a number of testable predicti...

Credit rating is the evaluation of the likelihood of an obligor to default on a loan. Each obligor in the bank’s credit portfolio is assigned to a certain rating class, or PD (probability of default) bucket; all obligors in a PD bucket then receive the same “pooled” PD, based on which a capital charge against credit risk must be computed. The only analytical approach to this problem is based on...

Ubiquitous data mining (UDM) is a methodology for creating new knowledge by building an integrated financial database in a ubiquitous computing environment, extracting useful rules by using diverse rule-extraction-based data mining techniques, and combining these rules. In this study, we built six credit rating forecasting models using traditional statistical methods (i.e., logistic regression ...