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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>.
Getting started
Browse package contents
Package details |
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| Author | Carlos Trucios [aut, cre] (<https://orcid.org/0000-0001-8746-8877>), Moon Jun Kwon [aut], São Paulo Research Foundation (FAPESP), grant 2022/09122-0 [fnd], Programa de Incentivo a Novos Docentes da UNICAMP (PIND), grant 2525/23 [fnd] |
| Maintainer | Carlos Trucios <ctrucios@unicamp.br> |
| License | GPL-2 |
| Version | 1.0.1 |
| URL | https://github.com/ctruciosm/HierPortfolios |
| Package repository | View on CRAN |
| Installation |
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