ARIMA with Attention-based CNN-LSTM and XGBoost hybrid model for stock prediction in the US stock market
Absteact: Stock price forecasting is considered one of the most difficult tasks in financial forecasting. Combining ARIMA with neural networks helps to enhance the model’s predictive capabilities when dealing with complex, nonlinear time series data. Attention-based CNN-LSTM and XGBoost hybrid model...
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| Autor principal: | |
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| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
EDP Sciences
2024-01-01
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| coleção: | SHS Web of Conferences |
| Acesso em linha: | https://www.shs-conferences.org/articles/shsconf/pdf/2024/16/shsconf_edma2024_02001.pdf |
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