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  3. Introduction to Portfolio Analysis in Python

Exercise

Calculating expected risk and returns

For this exercise, you're going to start with the raw price data. What you'll need for portfolio optimization, is the expected risk and return from this data.

With PyPortfolioOpt, you can calculate the expected risk and return in just one line of code, so that makes it very easy for you. The library you need is called pypfopt in short. FYI, you'll see in the next exercise that PyPortfolioOpt gives you the same output if you were to calculate it by hand. Let's give it a try!

Instructions 1/4

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  • Import the risk_models and expected_returns functions from the PyPortfolioOpt library as well the EfficientFrontier function from the efficientfrontier package.