Co-movements among precious metals and implications for portfolio management: A multivariate wavelet-based dynamic analysis: A multivariate wavelet-based dynamic analysis

This paper investigates the co-movements among precious metals (gold, silver, platinum, and palladium) across time-frequency domains and investment horizons and its implications for dynamic hedging, asset allocation, and utility gains. Based on a multiple wavelet coherence analysis, combined with Dynamic Conditional Correlation Generalized Autoregressive Conditional Heteroscedasticity (DCC-GARCH). The uni-directional co-movement is sequential, running from gold to the remaining metals. Silver leads platinum and palladium in returns, and platinum leading palladium. Interestingly, silver and platinum combined contribute to the variability of gold, while gold, silver, and palladium contribute to the variability of platinum, suggesting that some lead-lag relationships are complex and strengthened by multivariate relationships among the metals. The lead-lag dependence is high at medium and long investment horizons and responds to economic, political, and pandemic shocks to the global economy. We find that a wavelet-based dynamic hedging strategy performs better than a conventional hedging strategy. Portfolio weights from the bivariate, three-dimensional, and four-dimensional wavelet analyses vary across investment horizons. Finally, utility gains are higher at long horizons for all multi-dimensional risk strategies, whereas the utility gains are lower with the onslaught of the COVID-19 pandemic.