Yang Xin, Zhao Xian, Gong Xu, Yang Xiaoguang, Huang Chuangxia
School of Mathematics and Statistics, Changsha University of Science and Technology, Changsha 410114, China.
Hunan Provincial Key Laboratory of Mathematical Modeling and Analysis in Engineering, Changsha University of Science and Technology, Changsha 410114, China.
Entropy (Basel). 2020 May 24;22(5):588. doi: 10.3390/e22050588.
The investigation of the systemic importance of financial institutions (SIFIs) has become a hot topic in the field of financial risk management. By making full use of 5-min high-frequency data, and with the help of the method of entropy weight technique for order preference by similarities to ideal solution (TOPSIS), this paper builds jump volatility spillover network of China's financial institutions to measure the SIFIs. We find that: (i) state-owned depositories and large insurers display SIFIs according to the score of entropy weight TOPSIS; (ii) total connectedness of financial institution networks reveal that Industrial Bank, Ping An Bank and Pacific Securities play an important role when financial market is under pressure, especially during the subprime crisis, the European sovereign debt crisis and China's stock market disaster; (iii) an interesting finding shows that some small financial institutions are also SIFIs during the financial crisis and cannot be ignored.
对系统重要性金融机构（SIFIs）的研究已成为金融风险管理领域的热门话题。本文充分利用5分钟高频数据，借助逼近理想解排序法（TOPSIS）的熵权技术，构建中国金融机构的跳跃波动率溢出网络以衡量系统重要性金融机构。我们发现：（i）根据熵权TOPSIS得分，国有存款机构和大型保险公司表现出系统重要性金融机构的特征；（ii）金融机构网络的总连通性表明，兴业银行、平安银行和太平洋证券在金融市场承压时发挥着重要作用，尤其是在次贷危机、欧洲主权债务危机和中国股市灾难期间；（iii）一个有趣的发现是，一些小型金融机构在金融危机期间也是系统重要性金融机构，不容忽视。
