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A compressed sensing based AI learning paradigm for crude oil price forecasting
Yu, Lean; Zhao, Yang; Tang, Ling - In: Energy economics 46 (2014), pp. 236-245
Persistent link: https://www.econbiz.de/10011298594
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Fine structure of the price-demand relationship in the electricity market : multi-scale correlation analysis
Afanasyev, Dmitriy O.; Fedorova, Elena; Popov, Viktor U. - In: Energy economics 51 (2015), pp. 215-226
Persistent link: https://www.econbiz.de/10011564836
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An inquiry into the structure and dynamics of crude oil price using the fast iterative filtering algorithm
Piersanti, Giovanni; Piersanti, Mirko; Cicone, Antonio; … - In: Energy economics 92 (2020), pp. 1-7
Persistent link: https://www.econbiz.de/10012519649
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The long-term trends on the electricity markets : comparison of empirical mode and wavelet decompositions
Afanasyev, Dmitriy O.; Fedorova, Elena - In: Energy economics 56 (2016), pp. 432-442
Persistent link: https://www.econbiz.de/10011664482
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A novel multiscale nonlinear ensemble leaning paradigm for carbon price forecasting
Zhu, Bangzhu; Ye, Shunxin; Wang, Ping; He, Kaijian; … - In: Energy economics 70 (2018), pp. 143-157
Persistent link: https://www.econbiz.de/10011942668
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A new hybrid deep learning model for monthly oil prices forecasting
Guan, Keqin; Gong, Xu - In: Energy economics 128 (2023), pp. 1-21
Persistent link: https://www.econbiz.de/10015072695
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High-frequency volatility connectedness between the US crude oil market and China's agricultural commodity markets
Luo, Jiawen; Ji, Qiang - In: Energy economics 76 (2018), pp. 424-438
Persistent link: https://www.econbiz.de/10011976696