Hybrid Neural Networks Applied to Brazilian Stock Market

Authors

  • Wilson Castello Branco Neto Instituto Federal de Educação, Ciência e Tecnologia de Santa Catarina
  • Andrey de Aguiar Salvi Instituto Federal de Educação, Ciência e Tecnologia de Santa Catarina
  • William Passig de Souza Instituto Federal de Educação, Ciência e Tecnologia de Santa Catarina

DOI:

https://doi.org/10.22456/2175-2745.88911

Keywords:

Artificial Intelligence, Artificial Neural Networks, Genetic Algorithms.

Abstract

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.

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Published

2020-04-27

How to Cite

Branco Neto, W. C., Salvi, A. de A., & Souza, W. P. de. (2020). Hybrid Neural Networks Applied to Brazilian Stock Market. Revista De Informática Teórica E Aplicada, 27(2), 42–65. https://doi.org/10.22456/2175-2745.88911

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Section

Regular Papers