新加坡國立大學金融學教授段錦泉學術研讨會:違約相關性與信用資産分析

時間: 2015-08-29 16:49 來源: 作者: 字号: 打印

主題:Default Correlations and Large-Portfolio Credit Analysis(違約相關性與信用資産分析

主講人:Jin-Chuan Duan(段錦泉),新加坡國立大學金融學教授

日期:2015年9月2日(周三)

時間:下午2:00-3:30

地點清華Betvictor中文版4号樓101教室

語言:英文

摘要:

A factor model with sparsely correlated residuals is used to model short-term probabilities of default and other corporate exits while permitting missing data, and serves as the basis for generating default correlations. This novel factor model can then be used to produce portfolio credit risk profiles (default-rate and portfolio-loss distributions) by complementing an existing credit portfolio aggregation method with a novel simulation-convolution algorithm. We apply the model and portfolio aggregation method on a global sample of 40,560 exchange-listed firms and focus on three large portfolios (the US, Eurozone-12 and ASEAN-5). Our results reaffirm the critical importance of default correlations. With default correlations, both default-rate and portfolio-loss distributions become far more right-skewed, reflecting a much higher likelihood of defaulting together. Our results also reveal that portfolio credit risk profiles evaluated at two different time points can change drastically with moving economic conditions, suggesting the importance of modelling credit risks with a dynamic system. Our factor model coupled with the aggregation algorithm provides a useful tool for active credit portfolio management.


主講人簡介 :

Jin-Chuan Duan is Professor of Finance at Business School, National University of Singapore. Prof. Duan received a MSc and Ph. D in Finance from University of Wisconsin. His research interests are credit risk, banking and insurance, financial econometrics and risk management. Prior to joining the NUS, Duan was the Professor of Finance & Manulife Chair in Financial Svcs, University of Toronto. His papers have appeared in Journal of Business & Economic Statistics, Management Science, and Journal of Banking and Finance and other leading finance journals.


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