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Tools for non-linear time series forecasting in economics - an empirical comparison of regime switching vector autoregressive models and recurrent neural networks
Binner, Jane M.; Elger, Thomas; Nilsson, Birger; … - In: Applications of artificial intelligence in finance and …, (pp. 71-91). 2004
Persistent link: https://www.econbiz.de/10002797215
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Finding or not finding rules in time series
Lin, Jessica; Keogh, Eamonn - In: Applications of artificial intelligence in finance and …, (pp. 175-201). 2004
Persistent link: https://www.econbiz.de/10002797349
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Forecasting day-ahead electricity prices : a comparison of time series and neural network models taking external regressors into account
Lehna, Malte; Scheller, Fabian; Herwartz, Helmut - In: Energy economics 106 (2022), pp. 1-15
Persistent link: https://www.econbiz.de/10013202053
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Crude oil price forecasting : experimental evidence from wavelet decomposition and neural network modeling
Jammazi, Rania; Aloui, Chaker - In: Energy economics 34 (2012) 3, pp. 828-841
Persistent link: https://www.econbiz.de/10010219886
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The VEC-NAR model for short-term forecasting of oil prices
Cheng, Fangzheng; Li, Tian; Wei, Yi-Ming; Fan, Tijun - In: Energy economics 78 (2019), pp. 656-667
Persistent link: https://www.econbiz.de/10012160054
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Interval decomposition ensemble approach for crude oil price forecasting
Sun, Shaolong; Sun, Yuying; Wang, Shouyang; Wei, Yunjie - In: Energy economics 76 (2018), pp. 274-287
Persistent link: https://www.econbiz.de/10011976631
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Denoising or distortion : does decomposition-reconstruction modeling paradigm provide a reliable prediction for crude oil price time series?
Xu, Kunliang; Niu, Hongli - In: Energy economics 128 (2023), pp. 1-16
Persistent link: https://www.econbiz.de/10015072677