highOrderPortfolios
Design of High-Order Portfolios Including Skewness and Kurtosis
The classical Markowitz's mean-variance portfolio formulation ignores heavy tails and skewness. High-order portfolios use higher order moments to better characterize the return distribution. Different formulations and fast algorithms are proposed for high-order portfolios based on the mean, variance, skewness, and kurtosis. The package is based on the papers: R. Zhou and D. P. Palomar (2021). "Solving High-Order Portfolios via Successive Convex Approximation Algorithms." <arXiv:2008.00863>. X. Wang, R. Zhou, J. Ying, and D. P. Palomar (2022). "Efficient and Scalable High-Order Portfolios Design via Parametric Skew-t Distribution." <arXiv:2206.02412>.
Versions across snapshots
| Version | Repository | File | Size |
|---|---|---|---|
0.1.1 |
rolling source/ R- | highOrderPortfolios_0.1.1.tar.gz |
1.3 MiB |
0.1.1 |
rolling linux/jammy R-4.5 | highOrderPortfolios_0.1.1.tar.gz |
1.5 MiB |
0.1.1 |
rolling linux/noble R-4.5 | highOrderPortfolios_0.1.1.tar.gz |
1.5 MiB |
0.1.1 |
latest source/ R- | highOrderPortfolios_0.1.1.tar.gz |
1.3 MiB |
0.1.1 |
latest linux/jammy R-4.5 | highOrderPortfolios_0.1.1.tar.gz |
1.5 MiB |
0.1.1 |
latest linux/noble R-4.5 | highOrderPortfolios_0.1.1.tar.gz |
1.5 MiB |
0.1.1 |
2026-04-23 source/ R- | highOrderPortfolios_0.1.1.tar.gz |
1.3 MiB |
0.1.1 |
2026-04-09 windows/windows R-4.5 | highOrderPortfolios_0.1.1.zip |
1.5 MiB |
0.1.1 |
2025-04-20 source/ R- | highOrderPortfolios_0.1.1.tar.gz |
1.3 MiB |