rolloptim: Rolling Optimizations
Analytical computation of rolling optimization for
time-series data. The 'rolloptim' package solves constrained quadratic
and linear programs in closed form by applying Lagrangian multipliers
and the Karush-Kuhn-Tucker conditions (Kuhn and Tucker, 1951,
<doi:10.1525/9780520411586-036>) to perform mean-variance portfolio
optimization (Markowitz, 1952,
<doi:10.1111/j.1540-6261.1952.tb01525.x>) over rolling windows. For
each window, the analytical solution computes the optimal weights that
minimize variance, maximize expected return, minimize residual sum of
squares, or maximize quadratic utility, subject to a total-weight
equality constraint and box bounds on each weight. Use cases include
mean-variance portfolio optimization, expected-return maximization,
and constrained regression. The package supports rolling optimizations
with constraints via the total, lower, and upper arguments. The
implementation accepts rolling moments computed via the 'roll' package
and uses 'RcppArmadillo' for linear algebra, with parallelism across
windows provided by 'RcppParallel'.
| Version: |
1.0.0 |
| Depends: |
R (≥ 3.5.0) |
| Imports: |
Rcpp, RcppParallel |
| LinkingTo: |
Rcpp, RcppArmadillo, RcppParallel |
| Suggests: |
covr, CVXR, ROI, ROI.plugin.glpk, ROI.plugin.qpoases, ROI.plugin.quadprog, roll (≥ 1.1.7), testthat, zoo |
| Published: |
2026-07-11 |
| DOI: |
10.32614/CRAN.package.rolloptim (may not be active yet) |
| Author: |
Jason Foster [aut, cre] |
| Maintainer: |
Jason Foster <jason.j.foster at gmail.com> |
| BugReports: |
https://github.com/jasonjfoster/rolloptim/issues |
| License: |
GPL-2 | GPL-3 [expanded from: GPL (≥ 2)] |
| URL: |
https://github.com/jasonjfoster/rolloptim |
| NeedsCompilation: |
yes |
| SystemRequirements: |
GNU make |
| Materials: |
README, NEWS |
| CRAN checks: |
rolloptim results |
Documentation:
Downloads:
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