[Returnanalytics-commits] r3400 - pkg/PortfolioAnalytics/demo

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

Author: rossbennett34
Date: 2014-05-28 07:33:17 +0200 (Wed, 28 May 2014)
New Revision: 3400

Added:
   pkg/PortfolioAnalytics/demo/regime_switching.R
Modified:
   pkg/PortfolioAnalytics/demo/00Index
Log:
Adding demo for regime switching

Modified: pkg/PortfolioAnalytics/demo/00Index
===================================================================
--- pkg/PortfolioAnalytics/demo/00Index	2014-05-28 05:30:52 UTC (rev 3399)
+++ pkg/PortfolioAnalytics/demo/00Index	2014-05-28 05:33:17 UTC (rev 3400)
@@ -28,3 +28,4 @@
 risk_budget_backtesting Demonstrate optimize.portfolio.rebalancing with standard deviation risk budget objective.
 chart_concentration Demonstrate chart.Concentration
 multiple_portfolio_optimization Demonstrate passing a list of portfolios to optimize.portfolio and optimize.portfolio.rebalancing
+regime_switching       Demonstrate optimization with support for regime switching to switch portfolios based on the regime.

Added: pkg/PortfolioAnalytics/demo/regime_switching.R
===================================================================
--- pkg/PortfolioAnalytics/demo/regime_switching.R	                        (rev 0)
+++ pkg/PortfolioAnalytics/demo/regime_switching.R	2014-05-28 05:33:17 UTC (rev 3400)
@@ -0,0 +1,78 @@
+library(PortfolioAnalytics)
+data(edhec)
+R <- edhec[,1:6]
+colnames(R) <- c("CA", "CTAG", "DS", "EM", "EMN", "ED")
+funds <- colnames(R)
+
+# create an xts object of regimes
+# Here I just randomly samples values to create regime 1 or regime 2. In 
+# practice, this could based on volatility of other regime switching models
+set.seed(123)
+regime <- xts(sample(1:2, nrow(R), replace=TRUE), index(R))
+
+# portfolio for regime 1
+port1 <- portfolio.spec(funds)
+port1 <- add.constraint(port1, "weight_sum", min_sum=0.99, max_sum=1.01)
+port1 <- add.constraint(port1, "box", min=0.1, max=0.5)
+port1 <- add.objective(port1, type="risk", name="ES", arguments=list(p=0.9))
+port1 <- add.objective(port1, type="risk_budget", name="ES", 
+                       arguments=list(p=0.9), max_prisk=0.5)
+
+# portfolio for regime 2
+port2 <- portfolio.spec(funds)
+port2 <- add.constraint(port2, "weight_sum", min_sum=0.99, max_sum=1.01)
+port2 <- add.constraint(port2, "box", min=0, max=0.6)
+port2 <- add.objective(port2, type="risk", name="StdDev")
+port2 <- add.objective(port2, type="risk_budget", name="StdDev", max_prisk=0.5)
+
+portfolios <- combine.portfolios(list(port1, port2))
+
+regime.port <- regime.portfolios(regime, portfolios)
+
+# should result in portfolio for regime 1
+opt1 <- optimize.portfolio(R, regime.port, 
+                           optimize_method="random", 
+                           search_size=2000, 
+                           trace=TRUE)
+
+# should result in portfolio for regime 2
+opt2 <- optimize.portfolio(R[1:(nrow(R)-2)], regime.port, 
+                           optimize_method="DEoptim", 
+                           search_size=2000, 
+                           trace=TRUE)
+
+# For optimize_method="random", which portfolio do we use and how do we 
+# generate random portfolios
+# - prompt the user to generate random portfolios?
+# - use the first portfolio?
+# - specify which portfolio?
+opt.rebal <- optimize.portfolio.rebalancing(R, regime.port,
+                                            optimize_method="DEoptim", 
+                                            rebalance_on="quarters", 
+                                            training_period=130,
+                                            search_size=2000, 
+                                            trace=TRUE)
+
+opt.rebal
+
+summary(opt.rebal)
+
+lapply(opt.rebal$opt_rebalancing, function(x) x$regime)
+
+# Extract the weights
+wt <- extractWeights(opt.rebal)
+wt
+
+# Extract the objective measures
+obj <- extractObjectiveMeasures(opt.rebal)
+str(obj)
+obj
+
+# Extract the stats
+xt <- extractStats(opt.rebal)
+str(xt)
+
+chart.Weights(opt.rebal, colorset=bluemono)
+
+chart.RiskBudget(opt.rebal, match.col="ES", risk.type="percentage", regime=1, colorset=bluemono)
+chart.RiskBudget(opt.rebal, match.col="StdDev", risk.type="percentage", regime=2, colorset=bluemono)