Green but Different: ESG Component Effects in Mineral Sector Portfolios Using Advanced Risk Metrics and Optimization Algorithms

This study examines the distinct effects of Environmental (E), Social (S), and Governance (G) components on portfolio performance in the mining sector. Using 2017&ndash2021 data and the Glue VaR risk metric, we compared two optimization algorithms (QPA and MIPSO), finding QPA superior for constructing optimal portfolios. Employing QPA and supplementary Mean-Variance analysis, results clearly demonstrated that the Environmental (E) component is the most significant driver of risk-adjusted returns, consistently outperforming both Governance (G) and Social (S) factors. These findings offer crucial insights for investors, portfolio managers, and policymakers in the mineral sector, highlighting the need for differentiated ESG evaluation frameworks.