Multilayer network analysis of idiosyncratic volatility connectedness: Evidence from China

Abstract

This paper proposes multilayer networks, including lagged, contemporaneous, and long-run networks, to examine the idiosyncratic connectedness among Chinese financial institutions. We explore the topology of multilayer networks through static and dynamic analysis to capture the information transmission mechanism of idiosyncratic risks. Moreover, we investigate the drivers influencing idiosyncratic connectedness across financial institutions. We find that idiosyncratic risk contagion among financial institutions is stronger in the long-run network. At the same time, we note that the three networks contain different connection structures, which means that the information transmission mechanism of idiosyncratic risks is heterogeneous in multilayer networks. In addition, when the financial system is under stress, we observe that the contemporaneous effect of idiosyncratic connectedness rises rapidly. Institutional level analysis shows that diversified financial institutions play active roles in the lagged network, securities institutions are transmitters of contemporaneous information spillovers, and banking institutions are the main drivers of the long-run network. Finally, our study shows that size is the main factor driving idiosyncratic risk spillovers among financial institutions.