Package: HierPortfolios
Type: Package
Title: Hierarchical Clustering-Based Portfolio Allocation Strategies
Version: 1.0.0
Author: Carlos Trucios and Moon Jun Kwon
Maintainer: Carlos Trucios <ctrucios@unicamp.br>
Description: Machine learning portfolio allocation strategies based on hierarchical clustering methods. 
 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>.
License: GPL-2
Depends: R (>= 3.6.0)
Imports: fastcluster, cluster
Encoding: UTF-8
LazyData: true
RoxygenNote: 7.2.1
URL: https://github.com/ctruciosm/HierPortfolios
BugReports: https://github.com/ctruciosm/HierPortfolios/issues
NeedsCompilation: no
Packaged: 2024-03-30 15:59:48 UTC; ctruciosm
Repository: CRAN
Date/Publication: 2024-03-31 09:40:07 UTC
Built: R 4.2.3; ; 2024-04-24 00:56:05 UTC; windows
