Stock markets can be unpredictable, and as investors, we must find ways to protect our portfolios from sharp downturns. One method to do this is by hedging, which involves adjusting our portfolio to reduce its sensitivity to overall market movements.
In this article, we’ll build a simple hedge using Python. Our goal is to neutralize market risk by calculating our portfolio’s beta and adjusting it accordingly. By the end of this guide, you’ll learn how to:
- Download stock data for the Magnificent 7 (Mag 7) mega-cap tech stocks.
- Calculate daily returns for both the portfolio and the benchmark.
- Use linear regression to determine portfolio beta.
- Hedge the portfolio to reduce its exposure to market movements.
We’ll keep the coding simple using only two Python libraries:
yfinance (for downloading historical stock data) statsmodels (for performing regression analysis)
Let’s dive in! 
First, we need to fetch stock price data for the Mag 7 stocks:
