Replication data for: predicting the brazilian stock market using sentiment analysis, technical indicators, and stock prices

Version 1.0
Carosia, Arthur Emanuel de Oliveira; Silva, Ana Estela Antunes da; Coelho, Guilherme Palermo, 2022, "Replication data for: predicting the brazilian stock market using sentiment analysis, technical indicators, and stock prices", https://doi.org/10.25824/redu/GFJHFK, Repositório de Dados de Pesquisa da Unicamp , V1
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Description
This package contains the datasets and source codes used in the PhD thesis entitled Predicting the Brazilian stock market using sentiment analysis, technical indicators and stock prices.
The following files are included:
  • File Labeled.zip - financial news labeled in two classes (Positive and Negative), organized to train Sentiment Analysis models. Part of these news were initially presented in [1]. Besides the news in this file, in the related PhD thesis the training dataset was complemented with the labeled news presented in [2].
  • File Unlabeled.zip - general unlabeled financial news collected during the period 2010-2020 from the following online sources: G1, Folha de São Paulo and Estadão. This file contains news from the Bovespa index and from the following companies: Banco do Brasil, Itau, Gerdau and Ambev.
  • File Stocks.zip - stock prices from the companies Banco do Brasil, Itau, Gerdau, Ambev, and the Bovespa index. The considered period ranges from 2010 to 2020.
  • File Models.zip - contains the source codes of the models used in the PhD thesis (i.e., Multilayer Perceptron, Long Short-Term Memory, Bidirectional Long Short-Term Memory, Convolutional Neural Network, and Support Vector Machines).
  • File Utils.zip - contains the source codes of the preprocessing step designed for the methodology of this work (i.e., load data and generate the word embeddings), alongside with stocks manipulation, and investment evaluation.
[1] Carosia, A. E. D. O., Januário, B. A., da Silva, A. E. A., & Coelho, G. P. (2021). Sentiment Analysis Applied to News from the Brazilian Stock Market. IEEE Latin America Transactions, 100. DOI: 10.1109/TLA.2022.9667151
[2] MARTINS, R. F.; PEREIRA, A.; BENEVENUTO, F. An approach to sentiment analysis of web applications in portuguese. Proceedings of the 21st Brazilian Symposium on Multimedia and the Web, ACM, p. 105–112, 2015. DOI: 10.1145/2820426.2820446 (2022-09-20)
Subject Computer and Information Science
Keyword Sentiment analysis, Artificial neural networks, Deep learning, Stock market
Related Publication CAROSIA, Arthur Emanuel de Oliveira. Previsão do mercado de ações brasileiro com o uso de análise de sentimentos, indicadores técnicos e valores de ações. 2022. 1 recurso online (129 p.) Tese (doutorado) - Universidade Estadual de Campinas, Faculdade de Tecnologia, Limeira, SP. handle: 20.500.12733/5361
License/Data Use Agreement

CC BY-NC 4.0

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Labeled.zip
Unknown - 816.0 KB
Published Sep 22, 2022
54 Downloads
MD5: cf6da60c3ce7c01da260a9783b0b4eff
Financial news labeled in two classes (Positive and Negative), organized to train Sentiment Analysis models.
Models.zip
Unknown - 10.3 KB
Published Sep 22, 2022
32 Downloads
MD5: 0f8f361e0148eda3399b75da82c07835
Contains the source codes of the models used in the PhD thesis (i.e.., Multilayer Perceptron, Long Short-Term Memory, Bidirectional Long Short-Term Memory, Convolutional Neural Network, and Support Vector Machines).
Stocks.zip
Unknown - 242.6 KB
Published Sep 22, 2022
27 Downloads
MD5: 22bf7ac22d9cbd29496877df1fc1806a
Stock prices from the companies Banco do Brasil, Itau, Gerdau, Ambev, and the Bovespa index. The considered period ranges from 2010 to 2020.
Unlabeled.zip
Unknown - 5.1 MB
Published Sep 22, 2022
38 Downloads
MD5: e544c0e3a5cb5bc20e2e1437ff6c49c2
General unlabeled financial news collected during the period 2010-2020 from the following online sources: G1, Folha de São Paulo and Estadão. This file contains news from the Bovespa index and from the following companies: Banco do Brasil, Itau, Gerdau and Ambev.
Utils.zip
Unknown - 13.6 KB
Published Sep 22, 2022
32 Downloads
MD5: 7c9f1e6ca494fc7886e069f5e935f625
Contains the source codes of the preprocessing step designed for the methodology of this work (i.e., load data and generate the word embeddings), alongside with stocks manipulation, and investment evaluation.
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