TY - JOUR
T1 - Volatility spillovers and conditional correlations between oil, renewables and stock markets: A multivariate GARCH-in-mean analysis
AU - Wang, Wenxue
AU - Moffatt, Peter G.
AU - Zhang, Zheng
AU - Raza, Muhammad Yousaf
N1 - Data availability statement: Data will be made available on request.
Funding information: We acknowledge financial support from National Social Science Fund of China (Grant numbers. 23BJY223) and Shandong Provincial Social Science Foundation (Grant numbers. 24CJJJ24).
PY - 2025/1
Y1 - 2025/1
N2 - 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.
AB - 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.
KW - VOLATILITY SPILLOVERS
KW - Conditional Variance
KW - GARCH-in-mean
KW - Crude Oil Future
KW - Renewable Energy
KW - Exchange-traded fund
U2 - 10.1016/j.esr.2025.101639
DO - 10.1016/j.esr.2025.101639
M3 - Article
SN - 2211-467X
VL - 57
JO - Energy Strategy Reviews
JF - Energy Strategy Reviews
M1 - 101639
ER -