Linear regression model to investigate the relationship between the values of energy sector companies in Brazil and short-term company indicators

Abstract

This study aims to assess whether multiple linear regression analysis can explain how economic and financial indicators of Brazilian electric sector companies, such as net profit and total debt, are related. The hypothesis tested states that these indicators have a statistically significant relationship with the aggregate economic value of Brazilian electric sector companies. The research employed a hypothetical-deductive approach and a comparative and statistical procedure. Multiple linear regression analysis is used to examine the relationship between independent variables, such as net profit and total debt, and to understand how they influence the performance of electric sector companies. Other approaches that could be considered include logistic regression, in case the dependent variable is binary, and the use of panel data analysis, which allows for the examination of data from different companies over time. Additionally, event studies could be explored to assess the impact of specific events on electric sector companies. The dependent variables in this study were not mentioned in the provided text. However, it is important to note that the independent variables include net profit and total debt of Brazilian electric sector companies. These variables are analyzed to comprehend their relationship with company performance. In summary, this study utilizes multiple linear regression analysis to investigate how economic and financial indicators, such as net profit and total debt, are associated with the performance of Brazilian electric sector companies.