[Returnanalytics-commits] r3047 - pkg/PortfolioAnalytics/demo

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

Author: rossbennett34
Date: 2013-09-10 22:01:31 +0200 (Tue, 10 Sep 2013)
New Revision: 3047

Added:
   pkg/PortfolioAnalytics/demo/demo_proportional_cost.R
Removed:
   pkg/PortfolioAnalytics/demo/demo_proportional_cost_ROI.R
Log:
Added random portfolios example to demo_proportional_cost.R. Renamed demo file to drop the _ROI suffix.

Copied: pkg/PortfolioAnalytics/demo/demo_proportional_cost.R (from rev 3043, pkg/PortfolioAnalytics/demo/demo_proportional_cost_ROI.R)
===================================================================
--- pkg/PortfolioAnalytics/demo/demo_proportional_cost.R	                        (rev 0)
+++ pkg/PortfolioAnalytics/demo/demo_proportional_cost.R	2013-09-10 20:01:31 UTC (rev 3047)
@@ -0,0 +1,76 @@
+library(PortfolioAnalytics)
+library(quadprog)
+
+data(edhec)
+N <- 4
+R <- edhec[, 1:N]
+colnames(R) <- c("CA", "CTAG", "DS", "EM")
+funds <- colnames(R)
+
+# Transaction costs are calculated using the optimal weights and initial set of weights.
+# The initial set of weights is specified in the portfolio object. In the case
+# below, the initial set of weights is an equally-weighted portfolio.
+
+# set up initial portfolio specification object
+pspec <- portfolio.spec(assets=funds)
+pspec <- add.constraint(portfolio=pspec, type="full_investment")
+pspec <- add.constraint(portfolio=pspec, type="long_only")
+pspec <- add.constraint(portfolio=pspec, type="transaction", ptc=0.01)
+
+# add var objective to minimize portfolio variance
+minvar <- add.objective(portfolio=pspec, type="risk", name="var")
+
+# Note that if a return target is not specified, the results may not make sense
+optimize.portfolio(R=R, portfolio=minvar, optimize_method="ROI")
+
+# Add a target return constraint
+minvar <- add.constraint(portfolio=minvar, type="return", return_target=0.007)
+optimize.portfolio(R=R, portfolio=minvar, optimize_method="ROI")
+
+# Add return and risk objective for quadratic utility
+# Note that target return can be specified as a constraint or in the return 
+# objective as shown below
+qu <- add.objective(portfolio=pspec, type="risk", name="var", risk_aversion=0.3)
+qu <- add.objective(portfolio=qu, type="return", name="mean", target=0.007)
+optimize.portfolio(R=R, portfolio=qu, optimize_method="ROI")
+
+# Now use random portfolios
+# set up portfolio with equally weighted portfolio for initial weights
+pspec <- portfolio.spec(assets=funds)
+pspec <- add.constraint(portfolio=pspec, type="full_investment")
+pspec <- add.constraint(portfolio=pspec, type="long_only")
+pspec <- add.constraint(portfolio=pspec, type="transaction", ptc=0.01)
+
+# There is no transaction cost, the penalty should be 0.
+# constrained_objective(w=rep(1/4, 4), R=R, portfolio=pspec)
+# wts <- c(0.2, 0.3, 0.25, 0.25)
+# 10000 * sum(abs(wts - pspec$assets)*pspec$constraints[[3]]$ptc)
+# constrained_objective(w=wts, R=R, portfolio=pspec)
+
+# add objective to minimize standard deviation
+pspec <- add.objective(portfolio=pspec, type="risk", name="StdDev")
+
+# This pushes the optimal portfolio to the initial weights
+opt_rp <- optimize.portfolio(R=R, portfolio=pspec, optimize_method="random", search_size=2000)
+opt_rp
+
+
+# Now use random portfolios
+# set up portfolio with initial weights
+pspec <- portfolio.spec(assets=c(0.15, 0.15, 0.2, 0.5))
+pspec <- add.constraint(portfolio=pspec, type="full_investment")
+pspec <- add.constraint(portfolio=pspec, type="long_only")
+pspec <- add.constraint(portfolio=pspec, type="transaction", ptc=0.01)
+
+# There is no transaction cost, the penalty should be 0.
+# constrained_objective(w=rep(1/4, 4), R=R, portfolio=pspec)
+# wts <- c(0.2, 0.3, 0.25, 0.25)
+# 10000 * sum(abs(wts - pspec$assets)*pspec$constraints[[3]]$ptc)
+# constrained_objective(w=wts, R=R, portfolio=pspec)
+
+# add objective to minimize standard deviation
+pspec <- add.objective(portfolio=pspec, type="risk", name="StdDev")
+
+# This pushes the optimal portfolio to the initial weights
+opt_rp <- optimize.portfolio(R=R, portfolio=pspec, optimize_method="random", search_size=2000)
+opt_rp

Deleted: pkg/PortfolioAnalytics/demo/demo_proportional_cost_ROI.R
===================================================================
--- pkg/PortfolioAnalytics/demo/demo_proportional_cost_ROI.R	2013-09-10 19:29:51 UTC (rev 3046)
+++ pkg/PortfolioAnalytics/demo/demo_proportional_cost_ROI.R	2013-09-10 20:01:31 UTC (rev 3047)
@@ -1,32 +0,0 @@
-library(PortfolioAnalytics)
-library(quadprog)
-
-data(edhec)
-N <- 4
-R <- edhec[, 1:N]
-colnames(R) <- c("CA", "CTAG", "DS", "EM")
-funds <- colnames(R)
-
-# set up initial portfolio specification object
-pspec <- portfolio.spec(assets=funds)
-pspec <- add.constraint(portfolio=pspec, type="full_investment")
-pspec <- add.constraint(portfolio=pspec, type="long_only")
-pspec <- add.constraint(portfolio=pspec, type="transaction", ptc=0.01)
-
-# add var objective to minimize portfolio variance
-minvar <- add.objective(portfolio=pspec, type="risk", name="var")
-
-# Note that if a return target is not specified, the results may not make sense
-optimize.portfolio(R=R, portfolio=minvar, optimize_method="ROI")
-
-# Add a target return constraint
-minvar <- add.constraint(portfolio=minvar, type="return", return_target=0.007)
-optimize.portfolio(R=R, portfolio=minvar, optimize_method="ROI")
-
-# Add return and risk objective for quadratic utility
-# Note that target return can be specified as a constraint or in the return 
-# objective as shown below
-qu <- add.objective(portfolio=pspec, type="risk", name="var", risk_aversion=0.3)
-qu <- add.objective(portfolio=qu, type="return", name="mean", target=0.007)
-optimize.portfolio(R=R, portfolio=qu, optimize_method="ROI")
-