Study of Economic Variables for Stock Market Trend Prediction via Machine Learning

• Grant number: 24/04789-2
• Support Opportunities: Scholarships in Brazil - Scientific Initiation
• Start date: July 01, 2024
• End date: June 30, 2025
• Field of knowledge: Physical Sciences and Mathematics - Computer Science - Computing Methodologies and Techniques
• Principal Investigator: Guilherme Palermo Coelho
• Grantee: Leonardo Rodrigues da Silva
• Host Institution: Faculdade de Tecnologia (FT). Universidade Estadual de Campinas (UNICAMP). Limeira , SP, Brazil

Abstract

The stock market is expanding, leading more people to invest in various financial products. According to a study by the Associação Brasileira das Entidades dos Mercados Financeiro e de Capitais (ANBIMA) and DataFolha, the percentage of Brazilian investors increased from 31% in 2021 to 36% in 2022, adding 8 million new investors. In this scenario, it is of utmost importance to understand the fluctuations of the financial market to increase the predictability of its movements, enhancing investment security. Therefore, to help investors invest more safely, this project aims to better understand the stock market using historical technical data and relevant economic indicators. This may improve the accuracy of prediction algorithms. To this end, the following activities are planned: (i) an in-depth analysis of a specific economic sector will be made, so that we can (ii) identify relevant indicators that may influence stock price variations; (iii) we will try to identify the connection between the selected indicators and daily stock closing prices; and (iv) we will develop a machine learning-based predictive model using technical stock data and the selected indicators.