Systemic Financial Risk of Stock Market Based on Multiscale Networks

This paper investigates the connectedness among 36 financial institutions in China from time-frequency perspective. Specifically, using MEMD and Elastic-Net-VAR methods, we construct multiscale spillover networks, and explore the topological characteristics from system-level and institution-level measures. Our results indicate that the risk contagion between financial institutions of different frequencies exhibit heterogeneity: (1) at a system level, the network characteristics and evolution behaviors in multiscale networks vary across different time scales. Multiscale networks reveal certain unique features that would otherwise not be detected in a single layer analysis, which offers more valuable information on the connectedness among financial institutions; (2) at an institution level, financial institutions play various roles in receiving or sending shocks through different channels of risk spillover or contagion, and the systemic importance of financial institutions varies across different frequency networks. Overall, our multiscale spillover networks provide new insights for participants in financial market, particularly investors or hedgers with varying investment horizons.