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

Carosia, Arthur Emanuel de Oliveira; Silva, Ana Estela Antunes da; Coelho, Guilherme Palermo

Use este identificador para citar ou acessar este item: https://doi.org/10.25824/redu/GFJHFK

DOI:	https://doi.org/10.25824/redu/GFJHFK
Título:	Replication data for: predicting the brazilian stock market using sentiment analysis, technical indicators, and stock prices
Assunto:	Computer and Information Science
Descrição:	This package contains the datasets and source codes used in the PhD thesis entitled <a href="https://hdl.handle.net/20.500.12733/5361" target="_blank">Predicting the Brazilian stock market using sentiment analysis, technical indicators and stock prices</a>. <br> The following files are included: <ul> <li>File <em>Labeled.zip</em> - financial news labeled in two classes (<em>Positive</em> and <em>Negative</em>), 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]. </li> <li>File <em>Unlabeled.zip</em> - 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. </li> <li>File <em>Stocks.zip</em> - stock prices from the companies Banco do Brasil, Itau, Gerdau, Ambev, and the Bovespa index. The considered period ranges from 2010 to 2020. </li> <li> File <em>Models.zip </em> - 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). </li> <li> File <em>Utils.zip</em> - 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. </li> </ul> [1] Carosia, A. E. D. O., Januário, B. A., da Silva, A. E. A., & Coelho, G. P. (2021). <strong>Sentiment Analysis Applied to News from the Brazilian Stock Market</strong>. IEEE Latin America Transactions, 100. DOI: <a href="https://doi.org/10.1109/TLA.2022.9667151" target="_blank">10.1109/TLA.2022.9667151</a> <br> [2] MARTINS, R. F.; PEREIRA, A.; BENEVENUTO, F. <strong>An approach to sentiment analysis of web applications in portuguese</strong>. Proceedings of the 21st Brazilian Symposium on Multimedia and the Web, ACM, p. 105–112, 2015. DOI: <a href="https://doi.org/10.1145/2820426.2820446" target="_blank">10.1145/2820426.2820446</a>
Autor(es):	Carosia, Arthur Emanuel de Oliveira Silva, Ana Estela Antunes da Coelho, Guilherme Palermo
URI:	https://doi.org/10.25824/redu/GFJHFK https://redu.unicamp.br/dataset.xhtml?persistentId=doi:10.25824/redu/GFJHFK
Outros identificadores:
Fomento:	Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
Número do Projeto:	CAPES: 001
Termo de uso:
Data:	22-Set-2022
Data de Disponibilização:	23-Set-2022
Formato:	application/octet-stream application/octet-stream application/octet-stream application/octet-stream application/octet-stream
Tipo:
Editora / Evento / Instituição:	Coelho, Guilherme Palermo
Idioma :
Aparece nas coleções:	Repositório de Dados de Pesquisa da UNICAMP

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