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低违约评级组合的违约率估计

Estimation of Probability of Default by Using Ratings-Based Models
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摘要 违约率是信用风险建模的核心输入变量,本文基于评级模型对违约率进行估计。估计违约数据很少的低违约组合的违约率是一个比较困难的问题,用最大谨慎原则方法解决这类问题时结果偏大,过于保守。本文将最大谨慎原则的思想与极大似然方法相结合,估计低违约组合的违约率,其估计的结果比仅用最大谨慎原则估计的结果很大程度上降低了保守度。 Probability of default(PD) is a core input variable in the credit risk model. In this paper, PD is estimated by using ratings - based models. How to estimate PD of the low default portfolios which have few default data is a difficult problem. When using the most prudent estimation principle to solve this problem, the result is too large and over - conservative. Combining the thought of the most prudent estimation principle with the maximum likelihood approach, we estimate PD of the low default portfolios in this paper. Our estimating results are much less conservative than the one which are obtained only by using the most prudent estimation principle.
作者 王国栋
出处 《中国农机化》 北大核心 2010年第4期98-101,共4页 Chinese Agricul Tural Mechanization
基金 国家自然科学基金--一致性风险量度在信用风险的度量与管理中的应用(70573076) 高等学校博士点基金--一致性风险量度的理论与应用的研究(20050056057)
关键词 评级模型 违约率估计 最大谨慎原则 极大似然估计 ratings -based models PD estimation most prudent estimation principle maximum likelihood estimation
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参考文献13

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