ESG Performance, Financial Risk, and Returns in the Renewable Energy Sector: A Multi-Method Analysis of Heterogeneous Impacts

This multi-method study investigates the complex interplay among Environmental, Social, and Governance (ESG) performance, financial risk, and stock returns within the global renewable energy sector, addressing a critical gap in integrated quantitative analysis. Panel regression results indicate that superior ESG performance, reflecting lower ESG risk, is associated with higher excess returns, particularly in low and medium-ESG-risk portfolios. Time series models reveal varying volatility dynamics across ESG-based portfolios, while Granger causality tests provide limited evidence of direct predictive relationships from ESG scores to future returns. Although raw return predictability remains low, machine learning models, interpreted through SHAP values, identify ESG factors as significantly important relative to traditional financial variables in shaping return direction. Rolling correlation analysis further demonstrates dynamic co-movements between high and low ESG portfolios, with implications for diversification strategies. Collectively, the findings offer nuanced evidence on the financial materiality of ESG within the renewable energy sector, emphasizing that ESG-related effects are heterogeneous and context-dependent. These insights are particularly relevant for asset managers, corporate strategists, and policymakers seeking to align investment decisions with sustainability objectives and risk-adjusted performance in the context of the energy transition.