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braverock
GitHub Repository: braverock/portfolioanalytics
 Path: blob/master/demo/demo_opt_combine.R
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#' ---

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#' title: "Combine Optimizations Demo"

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#' author: Ross Bennett

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#' date: "7/17/2014"

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#' ---

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#' This script demonstrates how to combine optimizations for analysis.

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#' Load the package and data

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library(PortfolioAnalytics)

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library(DEoptim)

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data(edhec)

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R <- edhec[, 1:5]

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funds <- colnames(R)

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#' Construct initial portfolio with basic constraints.

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init.portf <- portfolio.spec(assets=funds)

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init.portf <- add.constraint(portfolio=init.portf, type="leverage", 

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                             min_sum=0.99, max_sum=1.01)

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init.portf <- add.constraint(portfolio=init.portf, type="long_only")

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#' Construct portfolio with objective to maximize portfolio mean return per unit ES.

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MeanES.portf <- add.objective(portfolio=init.portf, type="return", name="mean")

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MeanES.portf <- add.objective(portfolio=MeanES.portf, type="risk", name="ES")

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#' Construct portfolio with objective to maximize mean with risk budget 

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#' percent contribution limit.

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MeanSD.portf <- add.objective(portfolio=init.portf, type="return", name="mean")

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MeanSD.portf <- add.objective(portfolio=MeanSD.portf, type="risk_budget", 

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                              name="StdDev", max_prisk=0.35)

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#' Construct portfolio with objective to minimize portfolio expected shortfall 

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#' with equal ES component contribution.

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ESRB.portf <- add.objective(portfolio=init.portf, type="risk", name="ES")

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ESRB.portf <- add.objective(portfolio=ESRB.portf, type="risk_budget", 

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                            name="ES", min_concentration=TRUE)

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#' Run MeanES optimization.

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MeanES.opt <- optimize.portfolio(R=R, portfolio=MeanES.portf, 

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                                 optimize_method="DEoptim", search_size=2000,

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                                 trace=TRUE)

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#' Run MeanSD optimization

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MeanSD.opt <- optimize.portfolio(R=R, portfolio=MeanSD.portf, 

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                                 optimize_method="DEoptim", search_size=2000, 

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                                 trace=TRUE)

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#' Run ES Risk Budget optimization

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ESRB.opt <- optimize.portfolio(R=R, portfolio=ESRB.portf, 

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                               optimize_method="DEoptim", search_size=2000, 

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                               trace=TRUE)

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#' Combine the optimizations.

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opt <- combine.optimizations(list(MeanES=MeanES.opt, MeanSD=MeanSD.opt, ESRB=ESRB.opt))

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#' Extract the objective measures from each optimize.portfolio object 

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#' evaluated at all objectives.

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obj <- extractObjectiveMeasures(opt)

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#' Extract the optimal weights from each optimize.portfolio object.

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weights <- extractWeights(opt)

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#' Chart the risk contributions for StdDev and ES.

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chart.RiskBudget(opt, match.col="StdDev", risk.type="percentage", ylim=c(0,1), legend.loc="topright")

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chart.RiskBudget(opt, match.col="ES", risk.type="percentage", ylim=c(-0.2,1), legend.loc="topright")

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chart.RiskBudget(opt, match.col="ES", risk.type="percentage", plot.type="bar", ylim=c(-0.2,1), legend.loc="topright")

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#' Chart the optimal weights from each optimize.portfolio object.

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chart.Weights(opt, ylim=c(0,1))

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chart.Weights(opt, plot.type="bar", ylim=c(0,1))

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#' Chart the optimal portfolios in risk-reward space

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chart.RiskReward(opt, main="Optimal Portfolios")

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chart.RiskReward(opt, risk.col="StdDev", main="Optimal Portfolios")

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