Recommending Buy/Sell in Brazilian Stock Market through Recurrent Neural Networks
This work aims to evaluate the accuracy of Long Short-Term Memory Neural Networks to recommend Buy/Sell signals of some Brazilian Stock Market Blue Chips. The population of this study was composed by top 5 volume stocks, which represented nearly 40% of the total volume of Brazilian Stock Market in 2...
Guardado en:
| Autores principales: | , |
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| Formato: | Objeto de conferencia |
| Lenguaje: | Español |
| Publicado: |
2022
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| Acceso en línea: | http://sedici.unlp.edu.ar/handle/10915/151695 https://publicaciones.sadio.org.ar/index.php/JAIIO/article/download/266/217 |
| Aporte de: |
| Sumario: | This work aims to evaluate the accuracy of Long Short-Term Memory Neural Networks to recommend Buy/Sell signals of some Brazilian Stock Market Blue Chips. The population of this study was composed by top 5 volume stocks, which represented nearly 40% of the total volume of Brazilian Stock Market in 2019. It was analyzed the following features: volume traded, closing and opening price, maximum and minimum price, and last five-day closing prices. Models created can forecast the next day's opening or closing price. Obtained results show that forecasting and real values have a coefficient of determination (R²) from 0.91 to 0.99, depending on the stock. |
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