Multilayer networks in the frequency domain: Measuring volatility connectedness among Chinese financial institutions

Abstract

We construct multilayer networks in the frequency domain, including short-term, medium-term, and long-term connectedness networks, to examine the volatility connectedness among Chinese financial institutions. We investigate the network topology of intra-layer and inter-layer by the proposed method on the static and dynamic samples. We observe that the volatility connectedness among financial institutions is heterogeneous in the frequency domain. Specifically, we find that long-term connectedness among financial institutions rises significantly during crisis events. In addition, we note that China Life Insurance, Ping An Bank, and most securities tend to play risk emitters at a specific layer during the period of stress rise. Finally, we find that the stock market crisis in 2015 changed the edge structure among financial institutions in the short-term and long-term. Our work provides a new perspective for financial connectedness and risk contagion.