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  "Title": "Hierarchical Risk Clustering Portfolio Allocation Strategies",
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  "Date": "2025-09-12",
  "Authors@R": "c(\nperson(given = \"Carlos\", family = \"Trucios\", role = c(\"aut\", \"cre\"), email = \"ctrucios@unicamp.br\", comment = c(ORCID = \"0000-0001-8746-8877\")),\nperson(\"Moon Jun Kwon\", role = \"aut\"),\nperson(\"São Paulo Research Foundation (FAPESP), grant 2022/09122-0\",  role = \"fnd\"),\nperson(\"Programa de Incentivo a Novos Docentes da UNICAMP (PIND), grant 2525/23\",  role = \"fnd\"))",
  "Description": "Machine learning hierarchical risk clustering portfolio\nallocation strategies. The implemented methods are:\nHierarchical risk parity (De Prado, 2016) <DOI:\n10.3905/jpm.2016.42.4.059>. Hierarchical clustering-based asset\nallocation (Raffinot, 2017) <DOI: 10.3905/jpm.2018.44.2.089>.\nHierarchical equal risk contribution portfolio (Raffinot, 2018)\n<DOI: 10.2139/ssrn.3237540>. A Constrained Hierarchical Risk\nParity Algorithm with Cluster-based Capital Allocation\n(Pfitzingera and Katzke, 2019)\n<https://www.ekon.sun.ac.za/wpapers/2019/wp142019/wp142019.pdf>.",
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