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  3. Introduction to Portfolio Analysis in Python

Exercise

Portfolio variance

Your turn! It's time to calculate the risk of our 4-stock portfolio. Let's start with the pricing data, available under data. You'll have to calculate daily percentage returns and assign weights to your portfolio. You'll then continue by calculating the covariance matrix, and use the following formula: Portfolio variance = Weights transposed x (Covariance matrix x Weights) to get the final portfolio variance.

As calculating portfolio variance is an important part of portfolio analysis, make sure you take your time to understand each step, and go back to the slides if you need to. Good luck!

Instructions 1/4

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  • Calculate the daily returns from the price data and create a NumPy array with the following portfolio weights: 0.05, 0.4, 0.3, 0.25.