Volatility spillovers and conditional correlations between oil, renewables and stock markets: A multivariate GARCH-in-mean analysis

Abstract

We investigate linkages between three different markets: renewable energy (represented by a range of renewable energy ETFs); traditional energy (represented by crude oil ETF); and common stocks (represented by the S&P 500 Index ETF). We use daily data from 2008 to 2021. The econometric framework adopted is the VARMA-DCC-GARCH-in-mean model. We find that this framework is ideal because it allows us to identify the impact of uncertainty in one market on returns in another market, and also volatility spillovers, that is, the phenomenon of high uncertainty in one market spreading to other markets. Our key findings are as follows. Stock-market uncertainty influences traditional energy (negatively) and renewable energy (positively) at the mean level. Stock market volatility has a positive spillover effect on both conventional and renewable energies in the short-run, but these spillover effects are negative in the long-run. Our estimates of the time-paths of dynamic conditional correlations provide evidence that the renewable market is more heavily “financialized” than the traditional energy market, and moreover that the strong financialization of renewables is robust to financial crises.

Keywords

• Volatility spillovers
• Conditional variance
• GARCH-in-mean
• Crude oil future
• Renewable energy
• Exchange-traded fund