The R Journal: article published in 2018, volume 10:1

LP Algorithms for Portfolio Optimization: The PortfolioOptim Package
Andrzej Palczewski , The R Journal (2018) 10:1, pages 308-327.

Abstract The paper describes two algorithms for financial portfolio optimization with the following risk measures: CVaR, MAD, LSAD and dispersion CVaR. These algorithms can be applied to discrete distributions of asset returns since then the optimization problems can be reduced to linear programs. The first algorithm solves a simple recourse problem as described by Haneveld using Benders de composition method. The second algorithm finds an optimal portfolio with the smallest distance to a given benchmark portfolio and is an adaptation of the least norm solution (called also normal solution) of linear programs due to Zhao and Li. The algorithms are implemented in R in the package PortfolioOptim.

Received: 2017-07-23; online 2018-05-21, supplementary material, (1.4 KiB)
CRAN packages: fPortfolio, PortfolioAnalytics, Rglpk, quadprog, DEoptim, GenSA, psoptim, parma, nloptr, PortfolioOptim
CRAN Task Views implied by cited CRAN packages: Optimization, Finance

This article and supplementary materials are licensed under a Creative Commons Attribution 4.0 International license.

@article{RJ-2018-028,
  author = {Andrzej Palczewski},
  title = {{LP Algorithms for Portfolio Optimization: The PortfolioOptim
          Package}},
  year = {2018},
  journal = {{The R Journal}},
  doi = {10.32614/RJ-2018-028},
  url = {https://doi.org/10.32614/RJ-2018-028},
  pages = {308--327},
  volume = {10},
  number = {1}
}