[Returnanalytics-commits] r2049 - pkg/PortfolioAnalytics/sandbox

[noreply at r-forge.r-project.org]

Author: hezkyvaron
Date: 2012-06-23 03:54:09 +0200 (Sat, 23 Jun 2012)
New Revision: 2049

Added:
   pkg/PortfolioAnalytics/sandbox/testing_ROI.R
Log:
- adding file that is being used as testbed for ROI and the new extension for ROI in PA

Added: pkg/PortfolioAnalytics/sandbox/testing_ROI.R
===================================================================
--- pkg/PortfolioAnalytics/sandbox/testing_ROI.R	                        (rev 0)
+++ pkg/PortfolioAnalytics/sandbox/testing_ROI.R	2012-06-23 01:54:09 UTC (rev 2049)
@@ -0,0 +1,89 @@
+# # # # # # # # # # # # # #
+#  OPTIMIZATION TESTING 
+#
+setwd("~/Documents/gsoc_portfolio/tests")
+library(xts)
+library(quantmod)
+library(quadprog)
+library(Rglpk)
+library(PerformanceAnalytics)
+library(ROI)
+library(ROI.plugin.glpk)
+library(ROI.plugin.quadprog)
+library(Ecdat)
+library(PortfolioAnalytics)
+
+data(edhec)
+cov.mat <- var(edhec)
+mu.vec <- apply(edhec, 2, mean)
+n.assets <- ncol(edhec)
+mu.port <- 0.002
+Amat <- cbind(rep(1,n.assets),mu.vec)
+q.prob <- OP(objective=Q_objective(Q=-2*cov.mat, L=mu.vec), 
+             constraints=L_constraint(L=t(Amat),
+                                      dir=c("==","=="),
+                                      rhs=c(1,mu.port)),
+             maximum=TRUE)
+wts <- ROI_solve(x=q.prob, solver="quadprog")$solution
+
+
+
+# Comparing resutls wtih Guy's slides of PortfolioOptimization
+# sllide number 24/70, mean-variance optimization 
+# subject to fully-invested and expected portfolio return constraints
+data(CRSPday)
+R <- 100*CRSPday[,4:6]
+mean_vect <- apply(R,2,mean)
+cov_mat <- var(R)
+Amat <- rbind(rep(1,3),mean_vect)
+mu.port <- 0.1
+q.prob <- OP(objective=Q_objective(Q=2*cov_mat, L=rep(0,3)), 
+             constraints=L_constraint(L=Amat,
+                                      dir=c("==","=="),
+                                      rhs=c(1, mu.port)))
+wts <- ROI_solve(x=q.prob, solver="quadprog")$solution
+# this returuns a long-only portfolio, error within ROI
+
+
+# # # # # # # # # # # # # # # # # # # # # # # # # # # # # # # #
+# Sample portfolio optimization problem....
+
+# =====================
+# Arbitrage
+# 
+# to check the values of this example, I did the same problem with Rnupot.
+# unfortunately, ROI (or Rglpk, more specifically) cannot solve this problem well.
+# when using a RHS term in the constraint of Ax >= 0, the solution is trivial,
+# with RHS = rep(0.001, n.assets), the solution is non-trivial, but wrong.
+#
+# data(edhec)
+# set.seed(123)
+# n.assets <- ncol(edhec)
+# S <- 1 + apply(edhec, 2, sample, n.assets)
+# solution <- solveQP(objL=rep(1, ncol(S)), S,
+#                     cLO=rep(0, nrow(S)), cUP=rep(Inf, nrow(S)),
+#                     type=minimize)
+# wts <- solution$variables$x$current
+# > wts
+# 1           2           3           4           5           6           7 
+# -0.03687089  0.34978850 -0.02893078  0.15988671  0.29418430  0.02867836 -0.29697380 
+# 8           9          10          11          12          13 
+# -0.45799863 -0.30662611 -0.11010508 -0.74430483 -0.02668694  0.18126218
+
+set.seed(123)
+S.mat <- 1 + apply(edhec, 2, sample, size=n.assets)
+bnds <- list(lower = list(ind = seq.int(1L, as.integer(n.assets)), val = rep(-Inf,n.assets)),
+             upper = list(ind = seq.int(1L, as.integer(n.assets)), val = rep(Inf,n.assets)))
+q.prob <- OP(objective = L_objective(L=rep(1, n.assets)),
+             constraints = L_constraint(L=S.mat,
+                                        dir=rep(">=", n.assets),
+                                        rhs=rep(0.001, n.assets)),
+             bounds=bnds)
+test <- ROI_solve(x=q.prob, solver="glpk")
+# > test$solution
+# [1] -0.37584904  0.00000000  0.00000000  0.18434868  0.00000000  0.00000000  0.00000000  0.32167429  0.14030506
+# [10]  0.00000000 -0.41200277 -0.02153654  0.25916374
+
+
+
+