The identification of systemically important financial institutions (SIFIs) is an important measure to deal with systemic risks. To achieve this goal, we first use generalized variance decomposition method and granger causality test to construct jump volatility spillover networks of Chinese financial institutions based on the 5-min high-frequency data. Then, out-strength and in-strength are adopted to analyze the SIFI. Finally, we use panel data regression model to investigate the determinant of the SIFIs. The empirical results show that: (a) The network density reaches a peak when the financi...
