One of main economic impacts of Covid19 was the unprecedented drop in crude futures prices. After the crash, a high-volatility period followed, adding more uncertainty to the markets and financial institutions worldwide. Oil Companies rely on oil price projections for trading activities as well as financial and operational planning. We propose a decomposition-ensemble framework based on CEEMDAN algorithm and Adaptive Trees to forecast oil prices with the aim of reducing uncertainty and enabling rapid response in IOC/NOC¿s trading, planning, and operations
