Risk Spillover from Oil to Chinese New-Energy-Related Stock Markets : A R-Vine Copula-Based Covar Approach

In this article, we propose a R-vine copula model to detect the nonlinear interdependence between the oil market and five Chinese new-energy-related stock markets (photovoltaic, new energy vehicles, energy storage, wind power, and nuclear power industries). Following Reboredo and Ugolini (2015), we measure the downside and upside risk spillover from the oil market to five Chinese new-energy-related stock markets. In addition, we develop CoVaR backtesting methodology (Girardi and Ergun, 2013) to demonstrate the availability of the R-vine copula-CoVaR model. The empirical results exhibit strong evidence of a significant asymmetric risk spillover effect from oil to five Chinese new-energyrelated stock markets. Furthermore, different Chinese new-energy-related stock markets have various performances to the positive and negative impacts of the oil market. Specifically, photovoltaic, energy storage, and wind power industries are more sensitive to adverse effects. New energy vehicles and nuclear power industries, however, are more susceptible to positive impacts