Crandore Hub

HierPortfolios

Hierarchical Risk Clustering Portfolio Allocation Strategies

Machine learning hierarchical risk clustering portfolio allocation strategies. The implemented methods are: Hierarchical risk parity (De Prado, 2016) <DOI: 10.3905/jpm.2016.42.4.059>. Hierarchical clustering-based asset allocation (Raffinot, 2017) <DOI: 10.3905/jpm.2018.44.2.089>. Hierarchical equal risk contribution portfolio (Raffinot, 2018) <DOI: 10.2139/ssrn.3237540>. A Constrained Hierarchical Risk Parity Algorithm with Cluster-based Capital Allocation (Pfitzingera and Katzke, 2019) <https://www.ekon.sun.ac.za/wpapers/2019/wp142019/wp142019.pdf>.

Versions across snapshots

VersionRepositoryFileSize
1.0.2 rolling source/ R- HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 rolling linux/jammy R-4.5 HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 rolling linux/noble R-4.5 HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 latest source/ R- HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 latest linux/jammy R-4.5 HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 latest linux/noble R-4.5 HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 2026-04-23 source/ R- HierPortfolios_1.0.2.tar.gz 1.0 MiB
1.0.2 2026-04-09 windows/windows R-4.5 HierPortfolios_1.0.2.zip 1.0 MiB
1.0.1 2025-04-20 source/ R- HierPortfolios_1.0.1.tar.gz 1.0 MiB

Dependencies (latest)

Imports