This paper examines the recent period of relatively low credit spreads in Japan, with particular emphasis on the market’s assessments of the credit risks of large Japanese banks implicit in the prices of credit derivatives. We extract the market-price implied likelihood of a credit event in the future, and explore the nature of the default risk premiums underlying recent changes in bank bond an...

[Abstract] The assessment of credit risk of real-estate of Chinese banks has become a hot point nowadays. Traditional gross risk-evaluation methods are mainly Discriminant Analysis (DA) and logistic regression, and the most common approach is a credit rating system based on logistic regression. Yet the daily ripening neural network technique has opened up a new idea for experts in fields of ban...

A thorough understanding of the joint default behavior of credit-risky securities is essential for credit risk measurement as well as the valuation of multi-name credit derivatives and Collateralized Debt Obligations. In this paper we study a simple and tractable intensity-based model for correlated defaults, in which unpredictable default arrival times are jointly exponentially distributed. Si...

The turmoil in the capital markets in 1997 and 1998 has highlighted the need for systematic stress testing of banks’ portfolios, including both their trading and lending books. We propose that underlying macroeconomic volatility is a key part of a useful conceptual framework for stress testing credit portfolios, and that credit migration matrices provide the specific linkages between underlying...

The assessment of credit risk usually involves the development of rating models that classify credit applicants (firms or individuals) into predefined risk groups. A plethora of methodologies have been proposed to develop such rating models. Among them support vector machines (SVMs) have rapidly evolved in statistical learning theory as new modeling technique for developing classification model...

We study the adoption of automated credit scoring at a large auto finance company and the changes it enabled in lending practices. Credit scoring appears to have increased profits by roughly a thousand dollars per loan. We identify two distinct benefits of risk classification: the ability to screen high-risk borrowers and the ability to target more generous loans to lower-risk borrowers. We sho...

This paper examines the interaction between default risk and interest-rate risk in determining the term structure of credit default swap spreads at different industry sectors and credit rating classes. The paper starts with a parsimonious three-factor interest-rate dynamic term structure and projects the credit spread at each industry sector and rating class to these interest-rate factors while...

A thorough understanding of the joint default behavior of credit-risky securities is essential for credit risk measurement as well as the valuation of multi-name credit derivatives and Collateralized Debt Obligations. In this paper we study a simple and tractable intensity-based model for correlated defaults, in which unpredictable default arrival times are jointly exponentially distributed. Si...

The payoff of many credit derivatives depends on the level of credit spreads. In particular, credit derivatives with a leverage component are subject to gap risk, a risk associated with the occurrence of jumps in the underlying credit default swaps. In the framework of first passage time models, we consider a model that addresses these issues. The principal idea is to model a credit quality pro...