Portfolio optimization in R

Diethelm Wuertz provides a handy overview of the current state-of-the-art in portfolio optimization in R in a recent posting on the r-sig-finance mailing list.

The fPortfolio package (part of the Rmetrics suite) is available for download from CRAN, and handles standard portfolio optimization problems. As Diethelm Wuertz explains, the package can calculate:

Mean-Variance portfolio optimization with a quadratic objective and linear constraints using the "quadprog" solver from R for quadratic programming problems. Note, to this class of problems do not belong the problems of maximizing the return for a given risk, and also not problems with quadratic or nonlinear constraints like portfolios with covariance risk budgeting, or 130/30 portfolios. These portfolios are more complex and require solvers which can handle quadratic and/or nonlinear constraints.

Mean-CVaR portfolios which belong to the class of scenario optimization problems with a linear objective function and linear constraints. The default solver for this kind of portfolio is the solver from the package "Rglpk". Again you cannot solve more complex problems which add quadratic or non-linear  constraints.

There is also ongoing development work in Rmetrics to solve more complex portfolio models, and for functions to perform rolling backtesting, rolling benchmarking, and rolling performance analysis. These functions are available in r-forge with the usual caveats for in-development code -- full details are available in the aforementioned r-sig-finance post.

Diethelm Wuertz: fPortfolio - Status - New Functionalities