An approach using Pycaret lib, beta variance and yahoo finance to generate metrics to compose a future stock portfolio.
I would like to predict and verify future possible values of which stocks are less risky than others; based on this; I could identify some economy theory and statistics metrics; at this post, I’m going to share some snippets that can deliver insights to play around with stock predictions, more precisely with a Time Series Model called Auto Regressive Integrated Moving Average(ARIMA).