Dynamic volatility spillover among cryptocurrencies and energy markets: An empirical analysis based on a multilevel complex network

Abstract

Based on the DCC-GARCH-CONNECTEDNESS approach, this paper investigates the dynamic volatility spillover among ten cryptocurrency markets and three energy markets. This study constructed a volatility spillover network weighted by the spillover intensity index. The overall network topological properties, node characteristics, and spillover structure were then analyzed by applying the index quantification and hierarchical clustering algorithm. This research examined the multi-level risk spillover structure while realizing network visualization and also judged the dynamic correlation among the spillover network structures. The findings show that the network topology properties are relatively stable, but there is a large heterogeneity among markets. Compared to the energy market, the cryptocurrency market exhibits more profound features of volatility resonance between different currencies. Traditional cryptocurrency markets display higher risk resonance levels than stable coins. In terms of risk spillover structure, different markets tend to rely on market attributes to demonstrate their spillover and agglomeration characteristics. In addition, the risk spillover resonance among the sub-networks is also dynamic and time-varying, and this network structure will continue over time.