Managing Systemic Risk in Energy and Financial Markets: Evidence from Five Portfolio Strategies Based on Connectedness

Abstract

This study investigates the evolving interdependencies and risk transmission mechanisms between energy and financial markets, focusing on gold, West Texas Intermediate (WTI) crude oil, the S&P 500 Index (SP500), and the Shanghai Stock Exchange Composite Index (SSE) from January 2019 to August 2025. Employing daily return data, the analysis integrates multivariate linear regression, Dynamic Conditional Correlation-GARCH (DCC-GARCH) models, and dynamic conditional R² decomposition to capture time-varying connectedness and explanatory power. Grounded in the Diebold and Yılmaz (2012, 2014) framework, augmented by R² decomposition, the findings evince heightened systemic risk during major global disruptions, notably the COVID-19 pandemic and the Russia Ukraine conflict. WTI crude oil emerges as a principal conduit of volatility spillovers, underscoring its pivotal role in the energy-finance nexus. Five portfolio strategies Minimum Variance, Minimum Correlation, Minimum Connectedness, Minimum R², and Minimum Decomposed R² are constructed and evaluated under systemic stress. While the Minimum Variance Portfolio delivers robust risk-adjusted returns, strategies based on connectedness metrics demonstrate superior resilience during crises. These insights offer valuable implications for policymakers, investors, and scholars concerned with energy market stability, financial contagion, and adaptive portfolio design.