The effectiveness of SIFIs indicators on clustering-tune interbank network

How to identify Systemically Important Financial Institutions (SIFIs) which may cause systemic risk is a hotspot after the financial crisis. In this paper, we construct a clustering-tune interbank network based on the Holme-Kim model, and use the Kendall's Tau coefficient to study the effectiveness of four typical SIFIs indicators based on network theory. The results show that the change of clustering coefficient will lead to unstable fluctuation of the effectiveness of SIFIs indicators, and the change of loss giving default (LGD) in the process of contagion will lead to U-shape of effectiveness of SIFIs indicators.