基于宏观审慎的系统重要性商业银行评价与监管

Identification and Regulation of Systemically Important Commercial Banks

宏观审慎导向的金融监管是理论界和监管当局关注的重点,从国际银行业的发展经验来看,对系统重要性商业银行进行科学评价,可以为监管部门宏观审慎监管提供依据,从而有效防范金融体系的系统性风险的集中爆发并促进金融体系的稳定发展。本文在Adrian与Brunnermeier(2008)研究的基础上,拓展了基于Copula函数和GARCH分布的动态CoVaR模型,推导出了一种系统重要性商业银行的评价方法,提出了一个操作性较强的风险监管指标,并采用中国上市银行的数据,对各商业银行的系统重要性以及监管强度进行排序。研究结论表明,大型商业银行对整个银行系统的风险溢出影响非常大,商业银行的系统重要性具有动态的特征,并与经济周期密切相关,监管当局在对商业银行进行监管时,应该综合考虑商业银行自身的风险水平和它的系统重要性。

This paper extends the model of Adrian and Brunnermeier （2008） by developing a dynamic CoVaR model based on Copula function and GARCH distribution, which serves as a theoretical and operational method to identify systemically important commercial banks. With this model, we rank commercial banks according to their systemic importance using empirical data of China＇s listed banks. The conclusions show that China＇s large commercial banks spill over great risks on the banking system. We also come to the conclusion that systemic importance of commercial banks is dynamic and closely related to economic cycles. When it comes to the regulation of systemically important commercial banks, the authority should take the bank＇s risk and its systemic importance into account.