摘要
文章以CoVaR方法为基础,构建CoES模型,结合我国金融市场的实际,测度我国系统性金融风险。结果表明,一是CoES方法可有效地测度系统性金融风险;二是不同行业的VaR和DCoES值存在差异,银行业对系统性金融风险的贡献最大,房地产和保险次之,多元金融最小;三是各机构的动态DCoES值具有一定趋同性。银行业和房地产行业对系统性风险的影响大致相同。在极端情况下,类金融业对系统性风险的影响较大。
This paper is based on the CoVaR method to construct a CoES model, and then combines with the reality of China’s financial market to measure China’s systemic financial risk. The results show that firstly the CoES method can effectively measure systemic risk;secondly, there exists difference between the Value at Risk(VaR) of different industries and [Δ CoES] value, and the banking sector contributs the most to systemic financial risk, followed by real estate and insurance, diversified finance the least;thirdly, dynamic [Δ CoES] value of each institution has certain convergence;banking and real estate have roughly the same effect on systematic risk, and in extreme cases, other similar financial sectors have a greater impact on systematic risk.
作者
崔静
Cui Jing(School of Economics and Management,Zhoukou Normal University,Zhoukou Henan 466001,China)
出处
《统计与决策》
CSSCI
北大核心
2019年第20期148-151,共4页
Statistics & Decision
基金
河南省哲学社会科学规划项目（2018BJJ067）
河南省教育厅人文社会科学研究项目（2019-ZDJH-305)
