With Gurobi Finance, our robust set of documentation for the finance sector, you can explore several self-contained Jupyter notebooks that discuss the modeling of typical features in mean-variance (M-V) portfolio optimization.
Access the Jupyter Notebook Modeling Example
Click on the button below to access the example in Google Colab, which is a free, online Jupyter Notebook environment that allows you to write and execute Python code through your browser.
How to Run the Example
To run the example the first time, choose “Runtime” and then click “Run all”.
All the cells in the Jupyter Notebook will be executed.
The example will install the gurobipy package, which includes a limited Gurobi license that allows you to solve small models.
You can also modify and re-run individual cells.
For subsequent runs, choose “Runtime” and click “on “Restart and run all”.
The Gurobi Optimizer will find the optimal solution of the modeling example.
Check out the Colab Getting Started Guide for full details on how to use Colab Notebooks as well as create your own.
