摘要
为了探究中国商业银行系统性风险,基于信息溢出视角,选取中国14家上市商业银行的日收益率为研究对象,按照重大金融事件“钱荒”,“股灾”将数据分为3个阶段,首先运用BEKK-GARCH模型构建了波动溢出网络,通过分析网络的拓扑指标探究了银行波动网络的溢出效应,最后以波动网络为例,利用目标免疫和随机免疫策略对所构建的网络进行了稳健性检验。研究表明:1)在不同阶段下,中国上市商业银行波动溢出网络具有不同的网络结构,风险的冲击可以使得银行之间的联系更加紧密;2)中国上市商业银行之间风险溢出网络在高风险时期,网络集聚系数呈现明显增大趋势,网络的平均路径呈现明显缩短趋势,这一特点表明高风险时期各银行会紧密联系共同抵御风险;3)目标免疫对银行波动溢出网络稳定的影响远大于随机免疫的影响。
In order to explore the systemic risk of China′s commercial banks,this paper considers the impact of positive and negative market news on the bank′s network structure and the complexity of systemic risk in financial institutions,based on the perspective of information spillovers.Firstly,it selected the daily rate of return of listed 14 commercial banks in China.Then,the data is divided into three stages according to major financial events“money shortage”and“stock disaster”.Secondly,it used the complex network method to construct the shock network and the volatility overflow network based on the BEKK-GARCH model,and it explored the wave spillover effect and linkage effect of the bank′s wave network by analyzing the network′s indicators.Finally,it selected the volatility overflow network as an example,and used the target network and the random immune strategy to do a robustness test.The research result shows that:1)at different stages,bank volatility spillover networks have different network structures,and the impact of risks can make banks more closely;2)when the risk spillover network in a high-risk zone system,the network agglomeration coefficient is increasing,and the average path of the network is shortening significantly,this feature indicates that banks in the spillover network will be closely linked to resist risks;3)the impact of target immunity on network stability is much greater than that of random immunity.
作者
毛昌梅
韩景倜
刘举胜
MAO Changmei;HAN Jingti;LIU Jusheng(Postdoctoral Research Station, Shenwan Hongyuan Securities Co. Ltd., Shanghai 200031, China;School of information management and engineering, Shanghai University of Finance and Economics, Shanghai 200433,China;Shanghai Financial Intelligent Engineering Technology Research Center,Shanghai 200433,China)
出处
《复杂系统与复杂性科学》
EI
CSCD
2020年第2期11-21,共11页
Complex Systems and Complexity Science
基金
国家社科基金重大项目(18ZDA088)
国家自然科学基金项目(71871144)
上海市科委“科技创新行动计划”高新技术领域项目(18DZ1112103)
上海财经大学2019年研究生创新基金(CXJJ-2019-400)。
