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Interval decomposition ensemble approach for crude oil price forecasting

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Cited by:

  1. Feng Gao & Jie Song & Xueyan Shao, 2025. "Short-term interval-valued load forecasting with a combined strategy of iHW and multioutput machine learning," Annals of Operations Research, Springer, vol. 346(3), pages 2009-2033, March.
  2. Sun, Jingyun & Zhao, Panpan & Sun, Shaolong, 2022. "A new secondary decomposition-reconstruction-ensemble approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 77(C).
  3. Thakur, Jagruti & Hesamzadeh, Mohammad Reza & Date, Paresh & Bunn, Derek, 2023. "Pricing and hedging wind power prediction risk with binary option contracts," Energy Economics, Elsevier, vol. 126(C).
  4. Zheng, Li & Sun, Yuying & Wang, Shouyang, 2024. "A novel interval-based hybrid framework for crude oil price forecasting and trading," Energy Economics, Elsevier, vol. 130(C).
  5. Lin, Ling & Jiang, Yong & Xiao, Helu & Zhou, Zhongbao, 2020. "Crude oil price forecasting based on a novel hybrid long memory GARCH-M and wavelet analysis model," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 543(C).
  6. Liu, Jinpei & Zhao, Xiaoman & Luo, Rui & Tao, Zhifu, 2024. "A novel link prediction model for interval-valued crude oil prices based on complex network and multi-source information," Applied Energy, Elsevier, vol. 376(PB).
  7. Xiaolei Sun & Jun Hao & Jianping Li, 2022. "Multi-objective optimization of crude oil-supply portfolio based on interval prediction data," Annals of Operations Research, Springer, vol. 309(2), pages 611-639, February.
  8. Gao, Feng & Shao, Xueyan, 2022. "A novel interval decomposition ensemble model for interval carbon price forecasting," Energy, Elsevier, vol. 243(C).
  9. Jin Shao & Lean Yu & Jingke Hong & Xianzhu Wang, 2025. "Forecasting house price index with social media sentiment: A decomposition–ensemble approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(1), pages 216-241, January.
  10. Rui Luo & Jinpei Liu & Piao Wang & Zhifu Tao & Huayou Chen, 2024. "A multisource data‐driven combined forecasting model based on internet search keyword screening method for interval soybean futures price," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 366-390, March.
  11. Ewald, Christian Oliver & Li, Yaoyu, 2024. "The role of news sentiment in salmon price prediction using deep learning," Journal of Commodity Markets, Elsevier, vol. 36(C).
  12. Yang, Kun & Cheng, Zishu & Li, Mingchen & Wang, Shouyang & Wei, Yunjie, 2024. "Fortify the investment performance of crude oil market by integrating sentiment analysis and an interval-based trading strategy," Applied Energy, Elsevier, vol. 353(PA).
  13. Wang, Bin & Wang, Jun, 2020. "Energy futures and spots prices forecasting by hybrid SW-GRU with EMD and error evaluation," Energy Economics, Elsevier, vol. 90(C).
  14. Zhao, Yuan & Gong, Xue & Zhang, Weiguo & Xu, Weijun, 2024. "Forecasting carbon futures returns using feature selection and Markov chain with sample distribution," Energy Economics, Elsevier, vol. 140(C).
  15. Xu, Guangyue & Chen, Yaqiang & Yang, Mengge & Li, Shuang & Marma, Kyaw Jaw Sine, 2023. "An outlook analysis on China's natural gas consumption forecast by 2035: Applying a seasonal forecasting method," Energy, Elsevier, vol. 284(C).
  16. Sen, Abhibasu & Dutta Choudhury, Karabi, 2024. "Forecasting the Crude Oil prices for last four decades using deep learning approach," Resources Policy, Elsevier, vol. 88(C).
  17. Wang, Zicheng & Gao, Ruobin & Wang, Piao & Chen, Huayou, 2023. "A new perspective on air quality index time series forecasting: A ternary interval decomposition ensemble learning paradigm," Technological Forecasting and Social Change, Elsevier, vol. 191(C).
  18. Xingyu Dai & Roy Cerqueti & Qunwei Wang & Ling Xiao, 2025. "Volatility forecasting: a new GARCH-type model for fuzzy sets-valued time series," Annals of Operations Research, Springer, vol. 348(1), pages 735-775, May.
  19. Petropoulos, Fotios & Apiletti, Daniele & Assimakopoulos, Vassilios & Babai, Mohamed Zied & Barrow, Devon K. & Ben Taieb, Souhaib & Bergmeir, Christoph & Bessa, Ricardo J. & Bijak, Jakub & Boylan, Joh, 2022. "Forecasting: theory and practice," International Journal of Forecasting, Elsevier, vol. 38(3), pages 705-871.
    • Fotios Petropoulos & Daniele Apiletti & Vassilios Assimakopoulos & Mohamed Zied Babai & Devon K. Barrow & Souhaib Ben Taieb & Christoph Bergmeir & Ricardo J. Bessa & Jakub Bijak & John E. Boylan & Jet, 2020. "Forecasting: theory and practice," Papers 2012.03854, arXiv.org, revised Jan 2022.
  20. Du, Pei & Wang, Jianzhou & Yang, Wendong & Niu, Tong, 2020. "Point and interval forecasting for metal prices based on variational mode decomposition and an optimized outlier-robust extreme learning machine," Resources Policy, Elsevier, vol. 69(C).
  21. Jiang, He & Hu, Weiqiang & Xiao, Ling & Dong, Yao, 2022. "A decomposition ensemble based deep learning approach for crude oil price forecasting," Resources Policy, Elsevier, vol. 78(C).
  22. Haowen Bao & Yongmiao Hong & Yuying Sun & Shouyang Wang, 2025. "A Novel Hybrid Nonlinear Forecasting Model for Interval‐Valued Gas Prices," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 44(5), pages 1826-1848, August.
  23. Zhang, Qi & Yang, Kun & Hu, Yi & Jiao, Jianbin & Wang, Shouyang, 2023. "Unveiling the impact of geopolitical conflict on oil prices: A case study of the Russia-Ukraine War and its channels," Energy Economics, Elsevier, vol. 126(C).
  24. Piao Wang & Shahid Hussain Gurmani & Zhifu Tao & Jinpei Liu & Huayou Chen, 2024. "Interval time series forecasting: A systematic literature review," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(2), pages 249-285, March.
  25. Alameer, Zakaria & Fathalla, Ahmed & Li, Kenli & Ye, Haiwang & Jianhua, Zhang, 2020. "Multistep-ahead forecasting of coal prices using a hybrid deep learning model," Resources Policy, Elsevier, vol. 65(C).
  26. Wang, Piao & Tao, Zhifu & Liu, Jinpei & Chen, Huayou, 2023. "Improving the forecasting accuracy of interval-valued carbon price from a novel multi-scale framework with outliers detection: An improved interval-valued time series analysis mode," Energy Economics, Elsevier, vol. 118(C).
  27. Dinggao Liu & Liuqing Wang & Shuo Lin & Zhenpeng Tang, 2025. "A Novel Multi-Task Learning Framework for Interval-Valued Carbon Price Forecasting Using Online News and Search Engine Data," Mathematics, MDPI, vol. 13(3), pages 1-23, January.
  28. Zhu, Mengrui & Xu, Hua & Wang, Minggang & Tian, Lixin, 2024. "Carbon price interval prediction method based on probability density recurrence network and interval multi-layer perceptron," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 636(C).
  29. Sun, Huali & Li, Jiamei & Wang, Tingsong & Xue, Yaofeng, 2022. "A novel scenario-based robust bi-objective optimization model for humanitarian logistics network under risk of disruptions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 157(C).
  30. Cortazar, Gonzalo & Ortega, Hector & Valencia, Consuelo, 2021. "How good are analyst forecasts of oil prices?," Energy Economics, Elsevier, vol. 102(C).
  31. Yiling Ye & Xiaowen Zhuang & Cai Yi & Dinggao Liu & Zhenpeng Tang, 2025. "Enhancing Agricultural Futures Return Prediction: Insights from Rolling VMD, Economic Factors, and Mixed Ensembles," Agriculture, MDPI, vol. 15(11), pages 1-33, May.
  32. Du, Xiaoxu & Tang, Zhenpeng & Chen, Kaijie, 2023. "A novel crude oil futures trading strategy based on volume-price time-frequency decomposition with ensemble deep reinforcement learning," Energy, Elsevier, vol. 285(C).
  33. Yan, Zichun & Tian, Fangzhu & Sun, Yuying & Wang, Shouyang, 2024. "A time-frequency-based interval decomposition ensemble method for forecasting gasoil prices under the trend of low-carbon development," Energy Economics, Elsevier, vol. 134(C).
  34. Li, Ye & Chen, Yiyan & Lean, Hooi Hooi, 2024. "Geopolitical risk and crude oil price predictability: Novel decomposition ensemble approach based ternary interval number series," Resources Policy, Elsevier, vol. 92(C).
  35. Guan, Keqin & Gong, Xu, 2023. "A new hybrid deep learning model for monthly oil prices forecasting," Energy Economics, Elsevier, vol. 128(C).
  36. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2022. "Forecasting natural gas consumption using Bagging and modified regularization techniques," Energy Economics, Elsevier, vol. 106(C).
  37. Yang, Kun & Sun, Yuying & Hong, Yongmiao & Wang, Shouyang, 2024. "Forecasting interval carbon price through a multi-scale interval-valued decomposition ensemble approach," Energy Economics, Elsevier, vol. 139(C).
  38. Wang, Yuhao & Chen, Huayou & Xu, Xuetao, 2025. "A weekly crude oil price interval-valued prediction architecture on fusion of decomposition technique and adaptive integration," Energy, Elsevier, vol. 334(C).
  39. Meira, Erick & Cyrino Oliveira, Fernando Luiz & de Menezes, Lilian M., 2021. "Point and interval forecasting of electricity supply via pruned ensembles," Energy, Elsevier, vol. 232(C).
  40. Zhu, Bangzhu & Wan, Chunzhuo & Wang, Ping, 2022. "Interval forecasting of carbon price: A novel multiscale ensemble forecasting approach," Energy Economics, Elsevier, vol. 115(C).
  41. Liu, Jinpei & Wang, Jiaqi & Zhao, Xiaoman & Tao, Zhifu, 2025. "A multi-objective ensemble prediction model for interval-valued carbon price based on mixed-frequency data and sub-model selection," Energy, Elsevier, vol. 326(C).
  42. Yang, Dongchuan & Guo, Ju-e & Sun, Shaolong & Han, Jing & Wang, Shouyang, 2022. "An interval decomposition-ensemble approach with data-characteristic-driven reconstruction for short-term load forecasting," Applied Energy, Elsevier, vol. 306(PA).
  43. Abhibasu Sen & Karabi Dutta Choudhury & Tapan Kumar Datta, 2023. "An analysis of crude oil prices in the last decade (2011-2020): With deep learning approach," PLOS ONE, Public Library of Science, vol. 18(3), pages 1-32, March.
  44. Hao, Jun & Feng, Qianqian & Yuan, Jiaxin & Sun, Xiaolei & Li, Jianping, 2022. "A dynamic ensemble learning with multi-objective optimization for oil prices prediction," Resources Policy, Elsevier, vol. 79(C).
  45. Dabin Zhang & Qian Li & Amin W. Mugera & Liwen Ling, 2020. "A hybrid model considering cointegration for interval‐valued pork price forecasting in China," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(8), pages 1324-1341, December.
  46. Mingchen Li & Kun Yang & Wencan Lin & Yunjie Wei & Shouyang Wang, 2024. "An interval constraint-based trading strategy with social sentiment for the stock market," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 10(1), pages 1-31, December.
  47. Weixin Sun & Heli Chen & Feng Liu & Yong Wang, 2025. "Point and interval prediction of crude oil futures prices based on chaos theory and multiobjective slime mold algorithm," Annals of Operations Research, Springer, vol. 345(2), pages 1003-1033, February.
  48. Tang, Ling & Zhang, Chengyuan & Li, Ling & Wang, Shouyang, 2020. "A multi-scale method for forecasting oil price with multi-factor search engine data," Applied Energy, Elsevier, vol. 257(C).
  49. Huang, Wenyang & Gao, Tianxiao & Hao, Yun & Wang, Xiuqing, 2023. "Transformer-based forecasting for intraday trading in the Shanghai crude oil market: Analyzing open-high-low-close prices," Energy Economics, Elsevier, vol. 127(PA).
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