highOrderPortfolios
0.1.1Design of High-Order Portfolios Including Skewness and Kurtosis
Overview
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.
Install
Health
- NOTE r-devel-linux-x86_64-debian-clang
- NOTE r-devel-linux-x86_64-debian-gcc
- NOTE2026-06-0911 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
- ERROR2026-06-0811 OK · 1 NOTE · 0 WARNING · 1 ERROR · 0 FAILURE
- NOTE2026-03-1012 OK · 2 NOTE · 0 WARNING · 0 ERROR · 0 FAILURE
Documentation
- Examples that run
- 100%
- Documented parameters
- 94%
- Return-value docs
- 100%
- References docs
- 70%
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5 development-tooling and community-health practices detected across 5 families in the upstream repository
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Dependencies
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Code & Tests
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People & History
3 releases. Pick two to compare their code metrics. R releases are shown for context.
- RR 4.6.0 released · 2026-04-24
- RR 4.5.0 released · 2025-04-11
- RR 4.4.0 released · 2024-04-24
- RR 4.3.0 released · 2023-04-21
- 0.1.1Latest
- 0.1.02022-10-19 · diff ↗
- 0.0.22022-10-11
- RR 4.2.0 released · 2022-04-22
Package metadata
- First published
- 2022-10-11
- Total releases
- 3 / 4 yrs
- License
- GPL-3 OSI
- Minimum R
- ≥ 3.5.0
- Bundled data
- 1,008 KB / 3 files
- Download size
- 1.4 MB
- Installed size
- not tracked yet
- With dependencies
- not tracked yet
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