| dc.creator | Branco Neto, Wilson Castello | |
| dc.creator | Salvi, Andrey de Aguiar | |
| dc.creator | Souza, William Passig de | |
| dc.date | 2020-04-27 | |
| dc.date.accessioned | 2022-10-04T22:27:26Z | |
| dc.date.available | 2022-10-04T22:27:26Z | |
| dc.identifier | https://seer.ufrgs.br/index.php/rita/article/view/RITA_VOL27_NR2_42 | |
| dc.identifier.uri | http://repositorioslatinoamericanos.uchile.cl/handle/2250/3870397 | |
| dc.description | The stock market is a stochastic, dynamic environment and is in constant evolution, and its prediction represents a big challenge. Many studies presented in the state of the art are facing this challenge, by making use of Artificial Neural Networks (ANN) as a tool to make such prediction. In this paper a comparative study is made with different methods in order to predict the Brazilian stock market through the Bovespa Index. An ANN was developed and its performance was compared against a hybrid model, in which a Genetic Algorithm (GA) is proposed as an alternative to improve the performance of this ANN. The results obtained were an average accuracy of 55.04% and 55.73% respectively, demonstrating that algorithms such as a GA have the capability of improving the performance of ANN for the stock market prediciton. | en-US |
| dc.format | application/pdf | |
| dc.language | eng | |
| dc.publisher | Instituto de Informática - Universidade Federal do Rio Grande do Sul | en-US |
| dc.relation | https://seer.ufrgs.br/index.php/rita/article/view/RITA_VOL27_NR2_42/pdf | |
| dc.rights | Copyright (c) 2020 Wilson Castello Branco Neto, Andrey de Aguiar Salvi, William Passig de Souza | pt-BR |
| dc.source | Revista de Informática Teórica e Aplicada; Vol. 27 No. 2 (2020); 42-65 | en-US |
| dc.source | Revista de Informática Teórica e Aplicada; v. 27 n. 2 (2020); 42-65 | pt-BR |
| dc.source | 2175-2745 | |
| dc.source | 0103-4308 | |
| dc.subject | Artificial Intelligence | en-US |
| dc.subject | Artificial Neural Networks | en-US |
| dc.subject | Genetic Algorithms. | en-US |
| dc.title | Hybrid Neural Networks Applied to Brazilian Stock Market | en-US |
| dc.type | info:eu-repo/semantics/article | |
| dc.type | info:eu-repo/semantics/publishedVersion | |
