Green transitions and asymmetric volatility spillovers: A time-varying GAS copula analysis of clean and fossil energy markets

This study examines the asymmetric and time-varying volatility connectedness between clean and fossil energy markets, focusing on nonlinear dependencies and tail risk dynamics. Using a GJR-GARCH model combined with a time-varying GAS copula, we analyze co-movements and tail dependence between clean energy indices and three major fossil fuel markets: Brent Crude, Natural Gas, and Heating Oil. This approach captures features like fat tails, volatility clustering, and asymmetric spillovers, offering deeper insights into inter-market relationships under stress. Results reveal stronger tail co-movements and volatility spillovers during downturns — patterns that static models often miss. The GAS copula framework effectively tracks evolving correlations and volatilities, outperforming constant Copula models. Risk assessments using Value at Risk and Expected Shortfall emphasize the asymmetric nature of downside risk, showing that diversification benefits vary across market regimes. These findings emphasize the need to model asymmetries for more resilient portfolio construction and climate-sensitive risk management in energy finance. They carry important implications for energy portfolio diversification, climate policy design, and the management of systemic financial risk in energy markets.