This repository contains a notebook and dataset used to predict the future price of the S&P 500 Index from historical data. The model is built with scikit-learn's linear regression functions. The S&P 500 is a stock market index that aggregates the stock prices of 500 large companies, more information on the S&P 500 can be found here. Predicting whether the index will go up or down helps forecast how the stock market as a whole will perform.
Note: You shouldn't make trades with any models developed in this notebook. Trading stocks has risks, and nothing in this notebook constitutes stock trading advice.
I'll be working with a csv file containing index prices. Each row in the file contains a daily record of the price of the S&P 500 Index from 1950 to 2015. The dataset is stored in sphist.csv.
I'll be using this dataset to develop the predictive model. I'll train the model with data from 1950-2012, and try to make predictions from 2013-2015.