Abstract
<jats:p>We employ the forecast error variance decomposition – vector autoregression (FEVD-VAR) and dynamic conditional correlation – generalized autoregressive conditional heteroskedasticity (DCC-GARCH) frameworks to capture volatility spillovers and dynamic connectedness across energy and stock markets and compare ESG and non-ESG stocks in India. The results show that spillovers account for 26.4% of the forecast error variance, indicating meaningful cross-market interdependence. ESG and non-ESG stocks act as net transmitters of volatility, whereas crude oil and natural gas are net recipients. However, during periods of market stress, such as COVID-19, crude oil becomes a net transmitter of volatility. These findings highlight the role of energy assets in portfolio diversification and provide important implications for risk management and asset allocation.</jats:p>