Data · dataset · 2022
Replication data for: predicting the brazilian stock market using sentiment analysis, technical indicators, and stock prices
Listed in REDU - Unicamp Institutional Research Data Repository
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.
Description
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.
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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
Links
Where it is published
- Dataverse dataset page redu.unicamp.br/dataset.xhtml?persistentId=doi%3A10.25824%2Fredu%2FGFJHFK ↗
landing page · from redu unicamp br
- DOI doi.org/10.25824/redu/gfjhfk ↗
DOI / persistent id · from redu unicamp br
Catalogue records · 1
- Dataverse API redu.unicamp.br/api/datasets/:persistentId/?persistentId=doi%3A10.25824%2Fredu… ↗
metadata API · from redu unicamp br
Topics
- Stated by source
- Computer and Information Science
- From keywords
- Computer Science & AI · Deep learning · Economics & Finance
Provenance · 1 source records, 10 field assertions
| Source | Key | Last seen | Raw |
|---|---|---|---|
| REDU - Unicamp Institutional Research Data Repository | doi:10.25824/redu/GFJHFK | 12 d ago | JSON v1 |
| Field | Assertion | Extractor | Evidence |
|---|---|---|---|
| concepts[field].anzsrc:field:461103 | mapping · redu unicamp br | vocabulary-mapper@1.0.0 | keywords['Deep learning'] |
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| concepts[field].local:field:computer-science-ai | mapping · redu unicamp br | connector:redu_unicamp_br@1.0.0 | /subjects |
| concepts[field].local:field:economics-finance | mapping · redu unicamp br | connector:redu_unicamp_br@1.0.0 | /subjects |
| created_date | source · redu unicamp br | connector:redu_unicamp_br@1.0.0 | |
| description | source · redu unicamp br | connector:redu_unicamp_br@1.0.0 | /description |
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| title | source · redu unicamp br | connector:redu_unicamp_br@1.0.0 | /name |
| updated_date | source · redu unicamp br | connector:redu_unicamp_br@1.0.0 | |
| version_label | source · redu unicamp br | connector:redu_unicamp_br@1.0.0 |