This example will walk you through the steps to build an asset allocation strategy based on hierarchical risk parity (HRP). You will:
- Learn how to use statistics and machine learning techniques to cluster assets into a hierarchical tree structure.
- Understand how to develop allocation strategies based on the tree structure and risk parity concept through recursion.
- Compare its result with Mean-Variance asset allocation.
MathWorks Computational Finance Team (2020). Asset Allocation - Hierarchical Risk Parity (https://www.mathworks.com/matlabcentral/fileexchange/70186-asset-allocation-hierarchical-risk-parity), MATLAB Central File Exchange. Retrieved .
The article below entitled “A constrained hierarchical risk parity algorithm” proposes a method to impose weight constraints to individual assets or group of assets on the HRP optimization.
I hope this helps!
What about if I want to add weight constraints?