Overview
Commodity markets demonstrate fundamental economic correlations – resource and product prices move toward long-run equilibrium but experience short-run deviations. Using Vector Error Correction Models (VECM), we quantify these stable long-term relationships and short-term adjustments. Empirical evidence indicates VECMs provide superior forecasts for agricultural commodities and metals, enabling clients to make informed inventory, pricing, and hedging decisions that are rooted in economic fundamentals rather than speculation.
Correlations and volatilities in commodity markets change significantly during periods of market stress. We use GARCH Dynamic Conditional Correlation models (DCC-GARCH) to capture these shifts accurately. This method, supported by extensive research on financial risk diffusion and market integration, enhances real-time risk management by alerting clients to failures in diversification. Thus, DCC-GARCH allows for timely adjustments in hedging strategies, protecting portfolios during turbulent periods.
Correlations and volatilities in commodity markets change significantly during periods of market stress. We use GARCH Dynamic Conditional Correlation models (DCC-GARCH) to capture these shifts accurately. This method, supported by extensive research on financial risk diffusion and market integration, enhances real-time risk management by alerting clients to failures in diversification. Thus, DCC-GARCH allows for timely adjustments in hedging strategies, protecting portfolios during turbulent periods.