Forecasting commodity prices using long-short-term memory neural networks
This paper applies a recurrent neural network (RNN) method to forecast cotton and oil prices. We show how these new tools from machine learning, particularly Long-Short Term Memory (LSTM) models, complement traditional methods. Our results show that machine learning methods fit reasonably well with...
| Autores principales: | , , |
|---|---|
| Formato: | Artículo preliminar |
| Lenguaje: | Inglés |
| Publicado: |
International Food Policy Research Institute
2021
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| Materias: | |
| Acceso en línea: | https://hdl.handle.net/10568/143474 |
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