Conditional dependence between oil price and stock prices of renewable energy: a vine copula approach

The current paper focusses on the co-movement between oil prices and renewable energy stock markets in a multivariate framework. The vine copula approach that offers a great flexibility in conditional dependence modelling is used. More specifically, we investigate the issue of the average dependence and co-movement between oil prices (West Texas Intermediate [WTI]) and renewable energy stock prices (Wilder Hill New Energy Global Innovation Index [NEX], Wilder Hill Clean Energy Index [ECO] and S and P Global Clean Energy Index [SPGCE]) by applying the vine copula based threshold generalised autoregressive conditional heteroskedasticity (TGARCH) model. Over the period 2003–2016, empirical findings reveal significant and symmetric dependence between the considered markets. Therefore, there is symmetric tail dependence, indicating the evidence of upper and lower tail dependence. This means that movements in oil prices and renewable energy indices are coupled to the same direction. These empirical insights are of particular interest to policymakers, risk managers and investors in renewable energy sector.