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 (2021). Asset Allocation - Hierarchical Risk Parity (https://www.mathworks.com/matlabcentral/fileexchange/70186-asset-allocation-hierarchical-risk-parity), MATLAB Central File Exchange. Retrieved .
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It does. I guess Jingjing Li means Matlab code to implement the weight boundaries. The authors use R: https://github.com/jpfitzinger
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.
https://ideas.repec.org/p/sza/wpaper/wpapers328.html
I hope this helps!
Good work.
What about if I want to add weight constraints?