A statistical modeling methodology for the analysis of term structure of credit risk and its dependency

Authors:
Jiashen You;Tomohiro Ando
Affiliations:
-;-
Venue:
Expert Systems with Applications: An International Journal
Year:
2013

Citing 9
Cited 0

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Credit risk evaluation using a weighted least squares SVM classifier with design of experiment for parameter selection

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Abstract

This paper presents a statistical modeling methodology for simultaneous estimation of the term structure for the risk-free interest rate, hazard rate, loss given default as well as credit risk dependency structure between bond-issuing industries. A model like this provides a realistic view for the market anticipation of credit risk for corporate bonds and the flexibility in capturing credit risk dependency between industries. Our statistical modeling procedure is carried out without specifying the model likelihood explicitly, and thus robust to the model mis-specification. An empirical analysis is conducted using the financial information on the Japanese bond market data. Numerical results confirm the practicality of the proposed methodology.