中国银行业系统性风险溢出效应测度

The Measure of Systematic Risk Spillover Effect in China's Banking Sector

中文关键词:  商业银行  系统性风险  风险溢出效应  CoVaR模型  系统重要性  宏观审慎监管

英文关键词:commercial bank  systemic risk  risk spillover effect  CoVaR model  systemic importance  macro-prudential supervision

中文摘要:

      选取14家上市商业银行2008—2016年的股票日度收益率数据,构建ARMA-GARCH-CoVaR模型,测度各家上市商业银行对整个银行体系的风险贡献程度以及商业银行之间的风险溢出强度。实证结果表明:每家商业银行都存在风险溢出效应,但不同商业银行对系统性风险的贡献程度存在明显差异,商业银行的系统性风险溢出程度与其自身风险水平的相关性较弱。值得注意的是,大型国有商业银行自身风险水平较低,但对银行系统性风险溢出强度最大；不同商业银行之间也存在风险溢出效应,但溢出程度呈现明显的非对称性,国有商业银行、城市商业银行对其关联银行的风险溢出大于股份制商业银行。此外,国内外经济金融形势对我国银行业系统性风险溢出具有重要影响,应将重大经济金融事件纳入到银行系统性风险的动态监测过程中。

英文摘要:

      Based on the model of ARMA-GARCH-CoVaR, this paper measures one bank's marginal contribution to the systemic risk and the spillover effect among the commercial banks using daily stock returns data of 14 listed commercial banks in China from 2008 to 2016. The empirical results show that there is spillover effect in each bank, but obvious differences exist in marginal contribution of different banks to the systemic risk. No significant correlation is found between banking systemic risk and its VaR. It is worth mentioning that the state-owned commercial banks have the highest contribution to systemic risk of banking sector, in spite of their low VaR. The risk spillover effect also occurs among different banks but it is asymmetric, being greater of the state-owned enterprises and city commercial banks to their associated banks than that of joint-equity commercial banks. Besides, both domestic and international economic and financial situation has a major impact on the systemic risk spillover of China's banking industry, making it the focus of future risk prevention and control to integrate macroeconomic events into the dynamic monitoring process of bank risks.