Overview
The Forecasting & Scenario Modeling solution helps companies manage uncertainty in commodity markets by combining advanced forecasting with scenario analysis. It uses econometric models like ARIMA, GARCH, and especially Vector Error-Correction Models (VECM) to capture both short-term price changes and long-term equilibrium relationships between linked commodities such as crude oil and natural gas.
DCC-GARCH models add value by forecasting changes in volatility and correlations across multiple commodities, essential for diversified portfolios. This approach moves beyond single-point forecasts, providing risk managers with a range of possible outcomes and probabilities, supported by stress tests and narrative scenarios. For example, VECM improves forecasts of price spreads important to refiners, while co-integration tests identify long-term price linkages that guide hedging strategies.
The solution generates scenario matrices showing the impact under different conditions – such as a drought that causes corn prices to rise but volumes to fall – helping companies develop effective contingency plans and make informed decisions amid market volatility.
DCC-GARCH models add value by forecasting changes in volatility and correlations across multiple commodities, essential for diversified portfolios. This approach moves beyond single-point forecasts, providing risk managers with a range of possible outcomes and probabilities, supported by stress tests and narrative scenarios. For example, VECM improves forecasts of price spreads important to refiners, while co-integration tests identify long-term price linkages that guide hedging strategies.
The solution generates scenario matrices showing the impact under different conditions – such as a drought that causes corn prices to rise but volumes to fall – helping companies develop effective contingency plans and make informed decisions amid market volatility.