Score contribution per author:
α: calibrated so average coauthorship-adjusted count equals average raw count
This paper introduces a multi-layer network approach to explore risk contagions in a sample of top energy firms in the world. Large energy companies play a very important role in the international energy market. Mapping their responses to different types of shocks provides profound implications for understanding how international energy markets work, and could also create significant value for investors in the energy sector. Specifically, we distinguish three layers of risk spillovers, covering return correlations as well as upper tail and lower tail dependence. Through a multi-layer network setting, we identify both within layer linkages and inter-layer linkages. In addition, the dynamic evolution of this network structure is explored through a rolling-window approach, which enables us to evaluate the level of structural stability. Our empirical results unveil three regional clusters and a dynamic power shifting pattern in the international energy sector. Overall, this multi-layer network approach allows us to detect complex risk contagion patterns in financial markets and could be generalized to other scenarios.