摘要
处置不良资产是我国金融业改革和发展的重要问题,大规模批量处置不良贷款是处置不良资产的首选方法之一.不良贷款组合的回收率分布,是不良贷款组合定价的基础.针对不良贷款回收率的双峰分布特性,将不良贷款分为低峰回收贷款和高峰回收贷款,证明了不良贷款组合的回收率收敛于低峰回收率和高峰回收率的条件期望之和.基于信用风险结构模型,进一步证明了高峰回收率条件期望的正态逆变换与低峰回收比率的正态逆变换之间存在线性关系.由于对低峰回收贷款易于判断,很容易估计低峰回收比率,因而可以通过线性回归估计出高峰回收率条件期望,这样就给出了不良贷款组合的整体回收率估计模型.基于这一模型,还给出了估计不良贷款回收率的分位数的计算方法,该方法实际上是VaR方法的推广.
Recovering non-performing loan is a key issue in the innovation and reform of China financial in- dustry. Batch-package method is one of the first alternatives to do with non-performing loan recovering. The core issue in the recovering procedure is to estimate Loss Given Default （LGD） of non-performing loan portfo- lios. Based on the bi-peak feature of recovery rate, we classify non-performing loans into low-recovery loans and high-recovery loans, and prove that the recovery rate of non-performing loan converges to the sum of low- recovery rate and conditional expectation of high-recovery rate. Using classical structural model, we further derive that there is linear relation between the inverse-normal transformation of conditional expectation of high- recovery rate and the inverse-normal transformations of low-recovery ratio. Since it is easy to discriminate the low recovery loan, and hence easy to estimate low-recovery ratio, we can estimate the whole non-performing portfolio recovery rate by linear regression. Then we give an approach to estimate the Loss Given Default of large homogenous non-performing loan portfolio. Based on the model, we give a method to calculate the quantile of non-performing loan portfolio recovery rate, which is an extension of VaR.
出处
《管理科学学报》
CSSCI
北大核心
2010年第2期86-96,共11页
Journal of Management Sciences in China
基金
国家基础研究计划资助项目(973项目)(2007CB814902)
国家自然科学基金创新研究群体资助项目(70221001)
国家自然科学基金重点资助项目(70331001)
国家自然科学基金海外杰出青年基金资助项目(10628104)
关键词
不良贷款组合
巨额同质资产组合
回收率估计
结构模型
non-performing loan
large homogenous portfolio
recovery rate estimation
structural model
