Ansari Saleh Ahmar, Muh. Qodri Alfairus, Nabilah Nursya'bani
This research addresses the critical challenge of sustainable energy price risk management by developing a novel integrated forecasting framework that combines Exponential Smoothing and ARCH-GARCH models. The study aims to overcome limitations of individual forecasting methods that fail to simultaneously capture trend components and volatility dynamics in energy markets. The framework was empirically validated using monthly Brent crude oil prices from 2018 to 2024, encompassing major market disruptions including the COVID-19 pandemic and Russia-Ukraine conflict. The methodology employs a two-stage approach: Double Exponential Smoothing and Triple Exponential Smoothing for systematic component modeling, followed by ARCH-GARCH implementation for volatility dynamics. Results demonstrate that the integrated framework achieves superior performance across multiple metrics, reducing forecast error by 21.3 % compared to the best individual model. The framework significantly improves Value-at-Risk estimates, achieving 95.8 % coverage rate with narrower prediction intervals compared to standalone models. Out-of-sample testing on 2023–2024 data confirms adaptability across different market regimes, from extreme volatility to stabilization phases. Regime-specific analysis reveals consistent performance improvements during COVID-19 disruption, geopolitical conflict, and recovery periods. Cross-commodity validation using West Texas Intermediate crude oil, Henry Hub natural gas, and clean energy indices confirms framework generalizability. The probabilistic forecasting capabilities enable scenario-based decision-making essential for sustainable energy transition planning. This study contributes to sustainable development by providing practitioners with enhanced tools for energy price risk management that quantify uncertainty and support strategic decision-making in volatile market environments. © 2025 Elsevier B.V.
Department of Statistics, Faculty of Mathematics and Natural Sciences, Universitas Negeri Makassar, Makassar, Indonesia
