This solution is based on linear regression to predict the value of a stock on the stock exchange.
Click here to read my article about it on Medium: Predição de ações na bolsa de valores com Python e Facebook Prophet
Jupyter Notebook
1 - For you to run the notebook, you need to have Jupyter installed on your computer or access it in the cloud.
2 - You need to have installed the following packages
3 - Just run It
This is an experimental example about how to make stock market predictions using linear regression and is working in progress for improvements.
The stock market refers to public markets that exist for issuing, buying, and selling stocks that trade on a stock exchange or over-the-counter. Stocks, also known as equities, represent fractional ownership in a company, and the stock market is a place where investors can buy and sell ownership of such investible assets. An efficiently functioning stock market is considered critical to economic development, as it gives companies the ability to quickly access capital from the public.
Linear Regression is the supervised Machine Learning model in which the model finds the best fit linear line between the independent and dependent variable i.e it finds the linear relationship between the dependent and independent variable.
In this project we will try to predict or get as close as possible to the value of a stock for data not yet observed.
