Dynamic Linkages and Tail Risks: EGARCH-Quantile Analysis of ESG and Commodity Returns in India

Abstract

Sustainable investing has gained global attention since the COVID-19 pandemic, as investors seek dual goals of robust financial returns alongside meaningful social and environmental outcomes. ESG scores gauge firms’ environmental, social, and governance performance, guiding sustainable investment decisions. However, empirical evidence on ESG-linked stock performance remains inconclusive and fragmented, with scant research delving into their volatility dynamics within emerging markets such as India. This study analyses interrelationships between Indian ESG and commodity (Gold, Energy, Silver) returns using descriptive statistics, EGARCH volatility modelling, and quantile regression on daily data. Results show non-normal distributions with fat tails and high volatility, particularly in Energy and Silver. EGARCH indicates persistent volatility (GARCH 0.95–0.98), asymmetric shocks, and notable leverage effects in ESG and Energy. Quantile regressions reveal strong, positive commodity effects on ESG returns, intensifying in bullish phases. Positive and statistically significant coefficients for Gold, Energy, and Silver at the 25th, 50th, and 75th quantiles indicate that these commodities are consistently positively associated with ESG returns, implying that, across low, middle, and high ESG regimes, increases in commodity returns tend to coincide with higher ESG performance. The findings highlight ESG’s integration into commodity risk networks, emphasising the need for advanced volatility stress tests, improved ESG disclosures, and adaptive hedging strategies.