金融机构系统性违约风险及系统重要机构识别  

Systemic Default Risk and Identification of Systemically Important Institutions of China Financial Section

作　　者：王培辉[1] 袁薇[1] Wang Peihui1 Yuan Wei2

机构地区：[1]河北大学经济学院

出　　处：《财经科学》2017年第5期41-53,共13页Finance & Economics

基　　金：作者主持的国家社科基金青年项目"保险业系统性风险与金融稳定关系研究"(14CJY073)阶段性成果

摘　　要：本文基于拓展的系统或有权益分析法研究了我国金融机构系统性违约风险,并识别了系统重要性金融机构。研究结果表明:(1)我国金融机构联合违约概率并不高,危机期间违约风险迅速上升,之后维持在较低水平,2014年底以来再度提高。各子行业违约概率走势相似,但数值上存在较大差异。(2)基于多元极值分布的蒙特卡洛模拟估计了金融机构违约的条件期望损失,较好地识别了系统重要性金融机构,测算了危机期间政府可能面临的救市成本。我国金融机构系统性违约期望损失较小,在可控范围内,并且系统重要金融机构主要来自于银行业,加强银行系统性风险监控仍是监管当局主要任务。Abstract： Based on extended systemic Contingent Claims Analysis, this paper researches systemic default risk of financial institutions in China and identifies systemically important financial institutions. The empirical results indicate that： The joint default probability of of financial institutions is not high. The default probabilities of the sub-sectors follow similar path, but there is a big difference in numerical value. The systemic default loss of financial institutions in China is relatively small, within a controllable rang and doesn＇t impact the macroeconomic stability. And the banks are a major part of the systemically important institutions of China. Monitoring and controlling the Systemic risk of banks are still the main missions of regulatory authorities.

关 键 词：系统性违约风险 或有权益分析法 多元copula 多元极值理论 

分 类 号：F832.3[经济管理—金融学]