Beschreibung:
The spillover effects between financial sectors and real economy in different risk levels are of concern for investors and regulatory authorities. Firstly, based on the sector returns of China, the VaRs at different quantiles are estimated by the MVMQ-CAViaR model. Then, we construct the linear and nonlinear risk spillover networks in downside, normal and upside cases by employing DY and nonlinear Granger causality methods. Finally, we analyze the topological characteristics of the linear and nonlinear risk spillover networks at the system and sector levels. The empirical results show that the linear and nonlinear risk spillover networks in different risk levels exhibit distinct topology properties, they are unevenly spread over each risk level (downside, normal and upside cases). Additionally, at the system-level, we observe that there is a significant difference between linear and nonlinear risk spillover networks in uniqueness and overlapping. Thus, we can obtain more comprehensive information by considering both linear and nonlinear spillover effects between sectors. Meanwhile, at the sector-level, the financial sectors (such as DF and RE sectors) can form a certain spillover effect on sectors of real economy across quantiles, but the net spillover effects of the financial sectors are smaller than that of some real economy sectors. Finally, the crisis shocks have impact on risk spillover effects between financial sectors and real economy. In downside and upside cases, the spillover effects between sectors during crisis period is higher than that during pre-crisis period. Specifically, RE sector is always net-emitter of nonlinear risk spillover during crisis period. These results show that our proposed linear and nonlinear risk spillover networks based on different risk levels supply valuable information for market participants, especially for investors whose trading and hedging strategies for portfolios