[Returnanalytics-commits] r2792 - in pkg/PortfolioAnalytics: R demo
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Aug 15 18:32:15 CEST 2013
Author: rossbennett34
Date: 2013-08-15 18:32:14 +0200 (Thu, 15 Aug 2013)
New Revision: 2792
Added:
pkg/PortfolioAnalytics/demo/demo_ROI.R
Modified:
pkg/PortfolioAnalytics/R/optFUN.R
Log:
Adding demo script for ROI. Fixing error in gmv_opt to add mean vector to Amat.
Modified: pkg/PortfolioAnalytics/R/optFUN.R
===================================================================
--- pkg/PortfolioAnalytics/R/optFUN.R 2013-08-15 14:40:04 UTC (rev 2791)
+++ pkg/PortfolioAnalytics/R/optFUN.R 2013-08-15 16:32:14 UTC (rev 2792)
@@ -15,8 +15,12 @@
# check for a target return
if(!is.na(target)) {
# If var is the only objective specified, then moments$mean won't be calculated
- if(all(moments$mean==0)) col_means <- colMeans(R)
- Amat <- rbind(Amat, col_means)
+ if(all(moments$mean==0)){
+ tmp_means <- colMeans(R)
+ } else {
+ tmp_means <- moments$mean
+ }
+ Amat <- rbind(Amat, tmp_means)
dir.vec <- c(dir.vec, "==")
rhs.vec <- c(rhs.vec, target)
}
Added: pkg/PortfolioAnalytics/demo/demo_ROI.R
===================================================================
--- pkg/PortfolioAnalytics/demo/demo_ROI.R (rev 0)
+++ pkg/PortfolioAnalytics/demo/demo_ROI.R 2013-08-15 16:32:14 UTC (rev 2792)
@@ -0,0 +1,220 @@
+# ROI examples
+
+# The following objectives can be solved with optimize_method=ROI
+# maximize return
+# minimum variance
+# maximize quadratic utility
+# minimize ETL
+
+library(PortfolioAnalytics)
+library(ROI)
+library(Rglpk)
+require(ROI.plugin.glpk)
+require(ROI.plugin.quadprog)
+
+# Load the returns data
+data(edhec)
+ret <- edhec[, 1:4]
+funds <- colnames(ret)
+
+# Create portfolio specification
+pspec <- portfolio.spec(assets=funds)
+
+##### Constraints #####
+# Constraints will be specified as separate objects, but could also be added to
+# the portfolio object (see the portfolio vignette for examples of specifying
+# constraints)
+
+# Full investment constraint
+fi_constr <- weight_sum_constraint(min_sum=1, max_sum=1)
+
+# Long only constraint
+lo_constr <- box_constraint(assets=pspec$assets, min=0, max=1)
+
+# Box constraints
+box_constr <- box_constraint(assets=pspec$assets,
+ min=c(0.05, 0.04, 0.1, 0.03),
+ max=c(0.65, 0.45, 0.7, 0.6))
+
+# Position limit constraint
+pl_constr <- position_limit_constraint(assets=pspec$assets, max_pos=2)
+
+# Target mean return constraint
+ret_constr <- return_constraint(return_target=0.007)
+
+# Group constraint
+group_constr <- group_constraint(assets=pspec$assets, groups=c(1, 2, 1),
+ group_min=0, group_max=0.5)
+
+# Factor exposure constraint
+# Industry exposures are used in this example, but other factors could be used as well
+# Note that exposures to industry factors are similar to group constraints
+facexp_constr <- factor_exposure_constraint(assets=pspec$assets,
+ B=cbind(c(1, 0, 0, 0),
+ c(0, 1, 1, 0),
+ c(0, 0, 0, 1)),
+ lower=c(0.1, 0.15, 0.05),
+ upper=c(0.45, 0.65, 0.60))
+
+##### Objectives #####
+# Return objective
+ret_obj <- return_objective(name="mean")
+
+# Variance objective
+var_obj <- portfolio_risk_objective(name="var")
+
+# ETL objective
+etl_obj <- portfolio_risk_objective(name="ETL")
+
+##### Maximize Return Optimization #####
+# The ROI solver uses the glpk plugin to interface to the Rglpk package for
+# objectives to maximimize mean return
+
+# Full investment and long only constraints
+opt_maxret <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr),
+ objectives=list(ret_obj),
+ optimize_method="ROI")
+opt_maxret
+
+# Full investment, box, and target return constraints
+opt_maxret <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, ret_constr),
+ objectives=list(ret_obj),
+ optimize_method="ROI")
+opt_maxret
+
+# Full investment, box, and position_limit constraints
+opt_maxret <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, pl_constr),
+ objectives=list(ret_obj),
+ optimize_method="ROI")
+opt_maxret
+
+# Full investment, box, and group constraints
+opt_maxret <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, group_constr),
+ objectives=list(ret_obj),
+ optimize_method="ROI")
+opt_maxret
+
+# Full investment, box, and factor exposure constraints
+opt_maxret <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, facexp_constr),
+ objectives=list(ret_obj),
+ optimize_method="ROI")
+opt_maxret
+
+##### Minimize Variance Optimization #####
+# The ROI solver uses the quadprog plugin to interface to the quadprog package for
+# objectives to minimize variance
+
+# Global minimum variance portfolio. Only specify the full investment constraint
+opt_minvar <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr),
+ objectives=list(var_obj),
+ optimize_method="ROI")
+opt_minvar
+
+# Full investment, box, and target mean_return constraints
+opt_minvar <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, ret_constr),
+ objectives=list(var_obj),
+ optimize_method="ROI")
+opt_minvar
+
+# Full investment, box, and group constraints
+opt_minvar <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, group_constr),
+ objectives=list(var_obj),
+ optimize_method="ROI")
+opt_minvar
+
+# Full investment, box, and exposure constraints
+opt_minvar <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr, facexp_constr),
+ objectives=list(var_obj),
+ optimize_method="ROI")
+opt_minvar
+
+##### Maximize Quadratic Utility Optimization #####
+# The ROI solver uses the quadprog plugin to interface to the guadprog package for
+# objectives to maximimize quadratic utility
+
+# Create the variance objective with a large risk_aversion paramater
+# A large risk_aversion parameter will approximate the global minimum variance portfolio
+var_obj <- portfolio_risk_objective(name="var", risk_aversion=1e4)
+
+# Full investment and box constraints
+opt_qu <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, box_constr),
+ objectives=list(ret_obj, var_obj),
+ optimize_method="ROI")
+opt_qu
+
+# Change the risk_aversion parameter in the variance objective to a small number
+# A small risk_aversion parameter will approximate the maximum portfolio
+var_obj$risk_aversion <- 1e-4
+
+# Full investment and long only constraints
+opt_qu <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr),
+ objectives=list(ret_obj, var_obj),
+ optimize_method="ROI")
+opt_qu
+
+# Change the risk_aversion parameter to a more reasonable value
+var_obj$risk_aversion <- 0.25
+# Full investment, long only, and factor exposure constraints
+opt_qu <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, facexp_constr),
+ objectives=list(ret_obj, var_obj),
+ optimize_method="ROI")
+opt_qu
+
+# Full investment, long only, target return, and group constraints
+opt_qu <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, ret_constr, group_constr),
+ objectives=list(ret_obj, var_obj),
+ optimize_method="ROI")
+opt_qu
+
+##### Minimize ETL Optimization #####
+# The ROI solver uses the glpk plugin to interface to the Rglpk package for
+# objectives to minimimize expected tail loss
+
+# Full investment and long only constraints
+opt_minetl <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr),
+ objectives=list(etl_obj),
+ optimize_method="ROI")
+opt_minetl
+
+# Full investment, box, and target return constraints
+opt_minetl <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, ret_constr),
+ objectives=list(etl_obj),
+ optimize_method="ROI")
+opt_minetl
+
+# Full investment, long only, and position limit constraints
+opt_minetl <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, pl_constr),
+ objectives=list(etl_obj),
+ optimize_method="ROI")
+opt_minetl
+
+# Full investment, long only, and group constraints
+opt_minetl <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, group_constr),
+ objectives=list(etl_obj),
+ optimize_method="ROI")
+opt_minetl
+
+# Full investment, long only, and factor exposure constraints
+opt_minetl <- optimize.portfolio(R=ret, portfolio=pspec,
+ constraints=list(fi_constr, lo_constr, facexp_constr),
+ objectives=list(etl_obj),
+ optimize_method="ROI")
+opt_minetl
+
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