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...

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 ...

a r t i c l e i n f o The paper examines the role of newswire messages during the European debt crisis. In particular, this study quantifies how this news metric, revealed by statements electronically recorded, as well as by newspaper articles, affects credit ratings. Through a sample of three European countries with sovereign debt problems and under strict austerity programmes, i.e., Greece, I...

We show that sovereign debt impairments can have a significant impact on financial markets and real economies through a credit ratings channel. Specifically, we find that firms reduce their investment and reliance on credit markets due to a rising cost of debt capital following a sovereign rating downgrade. We identify these effects by exploiting exogenous variation on corporate ratings due to ...

In current credit ratings models, various accounting-based information are usually selected as prediction variables, based on historical information rather than the market’s assessment for future. In the study, we propose credit rating prediction model using market-based information as a predictive variable. In the proposed method, Moody’s KMV (KMV) is employed as a tool to evaluate the market-...

In this paper, we use credibility theory to estimate credit transition matrices in a multivariate Markov chain model for credit rating. A transition matrix is estimated by a linear combination of the prior estimate of the transition matrix and the empirical transition matrix. These estimates can be easily computed by solving a set of Linear Programming (LP) problems. The estimation procedure ca...

The model introduced in this article is designed to provide a consistent representation for both the real-world and pricing measures for the credit process. We find that good agreement with historical and market data can be achieved across all credit ratings simultaneously. The model is characterized by an underlying stochastic process that represents credit quality and default events are assoc...

The financial crisis has brought a new focus on the accuracy of credit rating agencies (CRAs). In this paper, we highlight the incentives of analysts at the CRAs to provide accurate ratings. We construct a model in which analysts initially work at a CRA and can then either remain or move to a bank. The CRA uses incentive contracts to motivate analysts, but does not capture the benefits if the a...

When banks and firms are connected through interpersonal linkages – such as their respective management having attended college or previously worked together – interest rates are markedly reduced, comparable with single shifts in credit ratings. These rate concessions do not appear to reflect sweetheart deals. Subsequent firm performance, such as future credit ratings or stock returns, improves...