模糊随机环境下的单因子Gaussian Copula模型  

Single Factor Gaussian Copula Model under Fuzzy Environments

作　　者：吴亮[1,2] 庄亚明[1] 

机构地区：[1]东南大学经济管理学院,南京211189 [2]河南科技学院数学科学学院,河南新乡453003

出　　处：《系统管理学报》2015年第4期510-516,共7页Journal of Systems & Management

基　　金：国家自然科学基金资助项目(71171051);中央高校基本科研业务费专项资金资助项目;江苏省普通高校研究生科研创新计划资助项目(KYLX_0213)

摘　　要：现有的对单因子Gaussian Copula模型中相关系数的各种改进,究其本质在于公司资产间相互关系的不可观测性和所获信息的不完全性——人们无法得到关于资产间相互关系大小的精确估计值,对于这一关键信息各人有着不同的模糊性,即现实中的不确定性既包含随机性又包含模糊性。因此,将随机性和模糊性相结合,用于研究诸如违约相关等问题有着现实需要。提出了一种新的带有模糊性分析的单因子Gaussian Copula模型,给出了带有模糊信息的联合违约概率和违约损失率,并用于综合CDO的定价。利用模糊数和随机性分析,不仅可以考虑更多的违约相关过程中不确定性源泉,更能包含投资者对金融市场中各种模糊性的主观判断信度,拓宽了可能的信用利差的范围。The existing improvement of correlation coefficient in single factor Gaussian Copula model lies in the unobservable relationships between assets of the company,and the incomplete information obtained—the relationship between assets has certain inherent ambiguity.Thus it is impossible to get the accurate the relationship,that is,the uncertainty in reality contain both fuzziness and randomness.Hence,using fuzziness and randomness to study the problems is practically necessary.We propose a new factor Gaussian Copula model with fuzziness and present a fuzzy joint default probability and default loss.We then puts them into CDO pricing.Using random analysis and fuzzy numbers can take into consideration of more uncertainty in the process of default correlation and the investors＇ subjective judgment on the financial markets,thus broadening the scope of possible credit spreads.

关 键 词：单因子Gaussian COPULA模型 违约相关 模糊性分析 

分 类 号：F840[经济管理—保险]