| dc.creator | da Silva Camargo, Sandro | |
| dc.creator | Lopes Silva, Gabriel | |
| dc.date | 2023-05 | |
| dc.date | 2023-08-23T17:47:37Z | |
| dc.date.accessioned | 2024-07-24T03:42:20Z | |
| dc.date.available | 2024-07-24T03:42:20Z | |
| dc.identifier | http://sedici.unlp.edu.ar/handle/10915/156748 | |
| dc.identifier.uri | https://repositorioslatinoamericanos.uchile.cl/handle/2250/9534924 | |
| dc.description | 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. | |
| dc.description | Sociedad Argentina de Informática e Investigación Operativa | |
| dc.format | application/pdf | |
| dc.format | 37-52 | |
| dc.language | en | |
| dc.rights | http://creativecommons.org/licenses/by-nc/4.0/ | |
| dc.rights | Creative Commons Attribution-NonCommercial 4.0 International (CC BY-NC 4.0) | |
| dc.subject | Ciencias Informáticas | |
| dc.subject | Variable Income | |
| dc.subject | Bovespa | |
| dc.subject | Time Series | |
| dc.subject | Recurrent Neural Networks | |
| dc.subject | Finance | |
| dc.title | Recommending buy/sell in brazilian stock market through long short-term memory | |
| dc.type | Articulo | |
| dc.type | Articulo | |
