Algo Trading Chapter 1- Processing Data For ML Stock Forecasting
Download the source code from here + Read the chapter here
https://onepagecode.substack.com/p/al...
In this video, we'll walk through the process of preparing stock market data for analysis, focusing on how to handle large datasets efficiently using Python. We'll be working with stock prices, company data, and other financial metrics to generate meaningful insights for further analysis. By the end of this video, you'll understand how to manipulate financial data, calculate monthly returns, and create features that will set the foundation for building predictive models.
We'll cover how to clean and align data from different sources, manage missing values, and apply feature engineering techniques, such as creating lagged returns and categorizing stocks by size and age. This workflow will help transform raw financial data into a format that's ready for machine learning and statistical modeling. Whether you're new to data science or looking to refine your approach, this tutorial will provide essential steps for preparing financial data for analysis.
