Hybrid Neural Networks Applied to Brazilian Stock Market

Wilson Castello Branco Neto, Andrey de Aguiar Salvi, William Passig de Souza


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.


Artificial Intelligence; Artificial Neural Networks; Genetic Algorithms.

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

Copyright (c) 2020 Wilson Castello Branco Neto, Andrey de Aguiar Salvi, William Passig de Souza

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