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# This library is free software; you can redistribute it and/or
# modify it under the terms of the GNU Library General Public
# License as published by the Free Software Foundation; either
# version 2 of the License, or (at your option) any later version.
#
# This library is distributed in the hope that it will be useful,
# but WITHOUT ANY WARRANTY; without even the implied warranty of
# MERCHANTABILITY or FITNESS FOR A PARTICULAR Description. See the
# GNU Library General Public License for more details.
#
# You should have received a copy of the GNU Library General
# Public License along with this library; if not, write to the
# Free Foundation, Inc., 59 Temple Place, Suite 330, Boston,
# MA 02111-1307 USA
################################################################################
# FUNCTION: DESCRIPTION:
# solveRipop Portfolio interface to solver Ripop
# .ripopArguments Returns arguments for solver
################################################################################
solveRipop <-
function(data, spec, constraints)
{
# A function implemented by Diethelm Wuertz
# Description:
# Portfolio interface to solver Ripop
# Example:
# data <- 100 * LPP2005.RET[, 1:6]
# spec <- portfolioSpec()
# setTargetReturn(spec) <- mean(data)
# setSolver(spec) <- "solveRipop"
# solveRipop(data, spec)
# FUNCTION:
# Transform Data:
Data <- portfolioData(data, spec)
data <- getSeries(Data)
nAssets <- getNAssets(Data)
# Compile Arguments for Solver:
args <- .ripopArguments(data, spec, constraints)
# Optimize Portfolio:
ans <- try(ipopQP(
objective = args$objective,
par.lower = args$par.lower,
par.upper = args$par.upper,
eqA = args$eqA,
eqA.bound = args$eqA.bound,
ineqA = args$ineqA,
ineqA.lower = args$ineqA.lower,
ineqA.upper = args$ineqA.upper,
control = list()),
silent = TRUE)
if (inherits(ans, "try-error")) {
# When Optimization Failed:
ans <- list(
opt = list(dvec=NA, Dmat=NULL),
objective = 1e99,
status = 1,
message = "error",
weights = rep(0, times=nAssets))
run <- "failed"
} else {
# Set Tiny Weights to Zero:
ans$weights <- .checkWeights(ans$solution)
ans$solution <- NULL
run <- "passed"
}
ans$solver <- "solveRipop"
ans$solution <- ans$weights
attr(ans$weights, "invest") <- sum(ans$weights)
attr(ans$opt, "args") <- args
# Class:
class(ans) <- c("solver", "list")
# Return Value:
ans
}
# -----------------------------------------------------------------------------
.ripopArguments <-
function(data, spec, constraints)
{
# A function implemented by Diethelm Wuertz
# Description:
# Returns ipopQP conform arguments for the solver
# FUNCTION:
# Data and Constraints as S4 Objects:
Data <- portfolioData(data)
data <- getSeries(Data)
nAssets <- getNAssets(Data)
Sigma <- getSigma(Data)
# Box Constraints:
par.lower <- minWConstraints(data, spec, constraints)
par.upper <- maxWConstraints(data, spec, constraints)
# Set up Equality Constraints:
eqsumW <- eqsumWConstraints(data, spec, constraints)
eqA <- eqsumW[, -1]
eqA.bound <- eqsumW[, 1]
# Set up Inequality Constraints:
minsumW <- minsumWConstraints(data, spec, constraints)
maxsumW <- maxsumWConstraints(data, spec, constraints)
ineqA <- NULL
if(!is.null(minsumW)) ineqA = rbind(ineqA, minsumW[, -1])
if(!is.null(maxsumW)) ineqA = rbind(ineqA, maxsumW[, -1])
ineqA.lower <- ineqA.upper <- NULL
if(!is.null(minsumW)) {
ineqA.lower = c(ineqA.lower, +minsumW[, 1])
ineqA.upper = c(ineqA.upper, rep(sum(par.upper), times=length(minsumW[, 1]))) }
if(!is.null(maxsumW)) {
ineqA.lower = c(ineqA.lower, rep(sum(par.lower), times=length(maxsumW[, 1])))
ineqA.upper = c(ineqA.upper, maxsumW[, 1]) }
# Return Value:
list(
objective = list(dvec = rep(0, nAssets), Dmat = Sigma),
par.lower = par.lower,
par.upper = par.upper,
eqA = eqA,
eqA.bound = eqA.bound ,
ineqA = ineqA,
ineqA.lower = ineqA.lower,
ineqA.upper = ineqA.upper
)
}
################################################################################
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