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中南大学学报(社会科学版)
ZHONGNAN DAXUE XUEBAO(SHEHUI KEXUE BAN)

2016年06月第22卷第3期
   
本文已被:浏览2005次    下载730次   
文章编号:1672-3104(2016)03-0114-10
 
沪深300指数成分股系统性风险贡献分析——基于股票指标关联网络的研究
 
乔海曙 ,杨蕾
 
(湖南大学金融与统计学院,湖南长沙,410082)
 
摘  要: 以沪深300指数成分股为节点构建股票关联网络,运用CoVaR方法测度各成分股对整体市场的系统性风险贡献度,研究个股在股市中关联度的大小与其系统性风险的关系。结果发现,在股票关联网络中处于核心位置的股票,其系统性风险贡献度越高。说明在股票市场中,关联度越广的上市公司,其传导危机的可能性越高,对系统性风险的贡献度越大。在系统性风险监督防范的过程中,应该对市场中关联度广、影响力强的公司给予更高的关注。
 
关键词: 系统性风险;股票关联性;复杂网络;CoVaR方法
 
 
Analysis of systemic risk contribution of CSI 300 Index: Based on the stock correlation network
 
QIAO Haishu, YANG Lei
 
(School of Finance and Statistics, Hunan University, Changsha 410082, China)
 
Abstract: Using individual stocks as nodes to build the network based on the CSI 300 Index, and then using CoVaR method to measure the contribution of stocks to systemic risk, the present study aims at the relationship between the size of correlation of individual stocks in the stock market and its systematic risk. Findings show that the nearer a stock is to the core of the stock correlation network, the higher systematic risk contribution. This illustrates that in the stock market, the stocks with wider correlation are more likely to transfer risks, and contribute more to systemic risks. So, in supervising and preventing systematic risks, we must pay more attention to those companies with wider correlation in the market and stronger influence.
 
Key words: systemic risk; stock correlation; complex network; CoVaR method
 
 
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