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Volatility forecasting of crude oil futures based on a genetic algorithm regularization online extreme learning machine with a forgetting factor: The role of news during the COVID-19 pandemic

Citations

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  1. Xu, Yan & Liu, Tianli & Du, Pei, 2024. "Volatility forecasting of crude oil futures based on Bi-LSTM-Attention model: The dynamic role of the COVID-19 pandemic and the Russian-Ukrainian conflict," Resources Policy, Elsevier, vol. 88(C).
  2. Riso, Luigi & Vacca, Gianmarco, 2024. "Sentiment dynamics and volatility: A study based on GARCH-MIDAS and machine learning," Finance Research Letters, Elsevier, vol. 62(PB).
  3. Li, Mingchen & Cheng, Zishu & Lin, Wencan & Wei, Yunjie & Wang, Shouyang, 2023. "What can be learned from the historical trend of crude oil prices? An ensemble approach for crude oil price forecasting," Energy Economics, Elsevier, vol. 123(C).
  4. Min Bai & Ly Ho, 2023. "How do gold and oil react to the COVID-19 pandemic: A review," Energy & Environment, , vol. 34(7), pages 2876-2902, November.
  5. 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).
  6. Liu, Longlong & Zhou, Suyu & Jie, Qian & Du, Pei & Xu, Yan & Wang, Jianzhou, 2024. "A robust time-varying weight combined model for crude oil price forecasting," Energy, Elsevier, vol. 299(C).
  7. Jianping Zhu & Futian Weng & Muni Zhuang & Xin Lu & Xu Tan & Songjie Lin & Ruoyi Zhang, 2022. "Revealing Public Opinion towards the COVID-19 Vaccine with Weibo Data in China: BertFDA-Based Model," IJERPH, MDPI, vol. 19(20), pages 1-26, October.
  8. Hu, Genhua & Jiang, Haifeng, 2023. "Time-varying jumps in China crude oil futures market impacted by COVID-19 pandemic," Resources Policy, Elsevier, vol. 82(C).
  9. He, Huizi & Sun, Mei & Li, Xiuming & Mensah, Isaac Adjei, 2022. "A novel crude oil price trend prediction method: Machine learning classification algorithm based on multi-modal data features," Energy, Elsevier, vol. 244(PA).
  10. Wei, Yu & Wang, Zhuo & Li, Dongxin & Chen, Xiaodan, 2022. "Can infectious disease pandemic impact the long-term volatility and correlation of gold and crude oil markets?," Finance Research Letters, Elsevier, vol. 47(PA).
  11. Gharib, Cheima & Mefteh-Wali, Salma & Serret, Vanessa & Ben Jabeur, Sami, 2021. "Impact of COVID-19 pandemic on crude oil prices: Evidence from Econophysics approach," Resources Policy, Elsevier, vol. 74(C).
  12. Zhenjie Liang & Futian Weng & Yuanting Ma & Yan Xu & Miao Zhu & Cai Yang, 2022. "Measurement and Analysis of High Frequency Assert Volatility Based on Functional Data Analysis," Mathematics, MDPI, vol. 10(7), pages 1-11, April.
  13. Wu, Menglong & Ye, Yicheng & Ke, Lihua & Hu, Nanyan & Wang, Qihu & Li, Yufei, 2023. "Characteristics analysis and situation prediction of production safety accidents in non-coal mining," Resources Policy, Elsevier, vol. 83(C).
  14. Li, Jieyi & Qian, Shuangyue & Li, Ling & Guo, Yuanxuan & Wu, Jun & Tang, Ling, 2024. "A novel secondary decomposition method for forecasting crude oil price with twitter sentiment," Energy, Elsevier, vol. 290(C).
  15. Asit Kumar Das & Debahuti Mishra & Kaberi Das & Pradeep Kumar Mallick & Sachin Kumar & Mikhail Zymbler & Hesham El-Sayed, 2022. "Prophesying the Short-Term Dynamics of the Crude Oil Future Price by Adopting the Survival of the Fittest Principle of Improved Grey Optimization and Extreme Learning Machine," Mathematics, MDPI, vol. 10(7), pages 1-33, March.
  16. Wang, Lu & Guan, Li & Ding, Qian & Zhang, Hongwei, 2023. "Asymmetric impact of COVID-19 news on the connectedness of the green energy, dirty energy, and non-ferrous metal markets," Energy Economics, Elsevier, vol. 126(C).
  17. Li, Jingyu & Liu, Ranran & Yao, Yanzhen & Xie, Qiwei, 2022. "Time-frequency volatility spillovers across the international crude oil market and Chinese major energy futures markets: Evidence from COVID-19," Resources Policy, Elsevier, vol. 77(C).
  18. Lu, Xinjie & Ma, Feng & Xu, Jin & Zhang, Zehui, 2022. "Oil futures volatility predictability: New evidence based on machine learning models11All the authors contribute to the paper equally," International Review of Financial Analysis, Elsevier, vol. 83(C).
  19. 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).
  20. Wang, Xuerui & Li, Xiangyu & Li, Shaoting, 2022. "Point and interval forecasting system for crude oil price based on complete ensemble extreme-point symmetric mode decomposition with adaptive noise and intelligent optimization algorithm," Applied Energy, Elsevier, vol. 328(C).
  21. Xiangyu Chen & Jittima Tongurai & Pattana Boonchoo, 2024. "Revisiting China’s Commodity Futures Market Amid the Main Waves of COVID-19 Pandemics," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 31(4), pages 1035-1063, December.
  22. Yang, Cai & Zhang, Hongwei & Weng, Futian, 2024. "Effects of COVID-19 vaccination programs on EU carbon price forecasts: Evidence from explainable machine learning," International Review of Financial Analysis, Elsevier, vol. 91(C).
  23. Zhao, Lu-Tao & Wang, Dai-Song & Ren, Zhong-Yuan, 2024. "The impact of joint events on oil price volatility: Evidence from a dynamic graphical news analysis model," Economic Modelling, Elsevier, vol. 130(C).
  24. Anqiang Huang & Xinjun Liu & Changrui Rao & Yi Zhang & Yifan He, 2022. "A New Container Throughput Forecasting Paradigm under COVID-19," Sustainability, MDPI, vol. 14(5), pages 1-20, March.
  25. Futian Weng & Dongsheng Cheng & Muni Zhuang & Xin Lu & Cai Yang, 2024. "The effects of governance quality on renewable and nonrenewable energy consumption: An explainable decision frame," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(6), pages 2146-2162, September.
  26. Qin Lu & Jingwen Liao & Kechi Chen & Yanhui Liang & Yu Lin, 2024. "Predicting Natural Gas Prices Based on a Novel Hybrid Model with Variational Mode Decomposition," Computational Economics, Springer;Society for Computational Economics, vol. 63(2), pages 639-678, February.
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