Type: Package Package: rolloptim Title: Rolling Optimizations Version: 1.0.0 Authors@R: person("Jason", "Foster", , "jason.j.foster@gmail.com", role = c("aut", "cre")) Description: 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, ) to perform mean-variance portfolio optimization (Markowitz, 1952, ) 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'. License: GPL (>= 2) URL: https://github.com/jasonjfoster/rolloptim BugReports: https://github.com/jasonjfoster/rolloptim/issues Depends: R (>= 3.5.0) Imports: Rcpp, RcppParallel Suggests: covr, CVXR, ROI, ROI.plugin.glpk, ROI.plugin.qpoases, ROI.plugin.quadprog, roll (>= 1.1.7), testthat, zoo LinkingTo: Rcpp, RcppArmadillo, RcppParallel Config/roxygen2/old_usage: TRUE Config/roxygen2/version: 8.0.0 Encoding: UTF-8 SystemRequirements: GNU make Config/pak/sysreqs: cmake make Repository: https://jasonjfoster.r-universe.dev Date/Publication: 2026-09-02 23:55:19 UTC RemoteUrl: https://github.com/jasonjfoster/rolloptim RemoteRef: HEAD RemoteSha: 7e7a83e5c73ceeea7e1c6d4d1544e2b76175395f NeedsCompilation: yes Packaged: 2026-10-03 06:52:42 UTC; root Author: Jason Foster [aut, cre] Maintainer: Jason Foster