In 10 lines of Python code, I can do a full portfolio optimization.
This is wild. Let me show how:
This is wild. Let me show how:
1. Load Python libraries
These are the python packages and functions we'll use.
These are the python packages and functions we'll use.
2. Create a Maximum Sharpe Ratio Portfolio
We create a Maximum Sharpe Ratio model and then fit it on the training set.
portfolio_params are parameters passed to the Portfolio returned by the predict method.
We create a Maximum Sharpe Ratio model and then fit it on the training set.
portfolio_params are parameters passed to the Portfolio returned by the predict method.
3. Create a Benchmark
This is an inverse volatility portfolio that I'll compare my Max Sharpe portfolio against.
This is an inverse volatility portfolio that I'll compare my Max Sharpe portfolio against.
4. Out-Of-Sample Performance
Use Predict Method to get out-of-sample Portfolio Performance
Use Predict Method to get out-of-sample Portfolio Performance
5. Portfolio Composition
The visualizations from skfolio are incredible.
The visualizations from skfolio are incredible.
6. Cumulative Returns
In 1 line of code, we can get cumulative returns for our portfolio and benchmark.
In 1 line of code, we can get cumulative returns for our portfolio and benchmark.
7. Performance Tear Sheet
In 1 line of code, I get a comprehensive performance tear sheet to share with clients.
In 1 line of code, I get a comprehensive performance tear sheet to share with clients.
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