A three-step deep neural network methodology for exchange rate forecasting
We present a methodology for volatile time series forecasting using deep learning. We use a three-step methodology in order to remove trend and nonlinearities from data before applying two parallel deep neural networks to forecast two main features from processed data: absolute value and sign. The p...
| Autores Principales: | , , |
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| Formato: | Objeto de conferencia (Conference Object) |
| Lenguaje: | Inglés (English) |
| Publicado: |
Springer Verlag
2017
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| Materias: | |
| Acceso en línea: | https://repository.urosario.edu.co/handle/10336/22520 https://doi.org/10.1007/978-3-319-63309-1_70 |