solveRglpk: Linear Programming Solver

In tipdub/ZestFinance: Rmetrics - Portfolio Selection and Optimization - ebook available at www.rmetrics.org

Description

Optimizes a portfolio using the linear programming solver Rglpk.

Usage

solveRglpk(data, spec, constraints)

Arguments

data	a time series or a named list, containing either a series of returns or named entries 'mu' and 'Sigma' being mean and covariance matrix.
spec	an S4 object of class fPFOLIOSPEC as returned by the function portfolioSpec.
constraints	a character string vector, containing the constraints of the form "minW[asset]=percentage" for box constraints resp. "maxsumW[assets]=percentage" for sector constraints.

Value

a list with the following named ebtries: solver, optim, weights, targetReturn, targetRisk, objective, status, message.

References

Wuertz, D., Chalabi, Y., Chen W., Ellis A. (2009); Portfolio Optimization with R/Rmetrics, Rmetrics eBook, Rmetrics Association and Finance Online, Zurich.

Examples

## data - 
   Data = SMALLCAP.RET
   Data = Data[, c("BKE", "GG", "GYMB", "KRON")]
   Data
   
## spec - 
   Spec = portfolioSpec()
   setType(Spec) = "CVaR" 
   setSolver(Spec) = "solveRglpk" 
   setTargetReturn(Spec) = mean(Data)
   Spec

## constraints - 
   Constraints = "LongOnly"
         
## solveRglpk -
   solveRglpk(Data, Spec, Constraints)

tipdub/ZestFinance documentation built on May 31, 2019, 3:37 p.m.