Multifractal Cross-Market Dependence and Dynamic Hedging Under Crisis Regimes: Evidence from Commodity–Equity Interactions

This study investigates cross-market dependence and dynamic hedging performance between the U.S. equity market and major commodity assets across distinct crisis regimes. Using daily data for the S&P 500 index and four key commodities (WTI crude oil, gold, wheat, and natural gas), we examine how market linkages evolve during systemic disruptions by applying Multifractal Detrended Cross-Correlation Analysis (MFCCA) and the q-dependent detrended correlation coefficient. Hedging performance is assessed using optimal hedge ratios estimated under two multivariate GARCH frameworks: the Asymmetric Dynamic Conditional Correlation (ADCC-GARCH) and the Generalized Orthogonal GARCH (GO-GARCH) model. The findings reveal strong multiscale and time-varying dependencies that intensify during high-volatility periods, reducing the benefits of conventional portfolio diversification. Hedging effectiveness proves to be regime dependent and strongly influenced by nonlinear cross-market interactions. The GO-GARCH model captures volatility spillovers and asymmetric co-movements more effectively, delivering superior hedging results compared with ADCC, especially during episodes of extreme market stress. Among the analysed commodities, crude oil and gold offer the most reliable hedging properties, whereas wheat and natural gas show unstable performance due to supply side shocks. These results emphasize the need for flexible, dynamically adjusted risk-management strategies during crisis environments.