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braverock
GitHub Repository: braverock/portfolioanalytics
 Path: blob/master/sandbox/testing_groups.R
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library(PortfolioAnalytics)

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library(ROI)

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library(ROI.plugin.quadprog)

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library(ROI.plugin.glpk)

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# data(edhec)

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# R <- edhec[, 1:4]

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# colnames(R) <- c("CA", "CTAG", "DS", "EM")

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# funds <- colnames(R)

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load("~/Desktop/Testing/crsp.short.Rdata")

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R <- cbind(microcap.ts[, 1:2],

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           smallcap.ts[, 1:2],

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           midcap.ts[, 1:2],

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           largecap.ts[, 1:2])

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funds <- colnames(R)

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cap_labels <- c(rep("MICRO", 2), rep("SMALL", 2), 

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                rep("MID", 2), rep("LARGE", 2))

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# Create initial portfolio object with category_labels

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init <- portfolio.spec(assets=funds, category_labels=cap_labels)

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# Add some weight constraints

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

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

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# Add objective to minimize variance

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minvar <- add.objective(portfolio=init, type="risk", name="var")

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# Specify group constraints by passing in category_labels from initial

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# portfolio object

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group1 <- add.constraint(portfolio=init, type="group",

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                        groups=init$category_labels,

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                        group_min=c(0.15, 0.25, 0.15, 0.2),

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                        group_max=c(0.4, 0.4, 0.6, 0.6))

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# Alternative way by specifying a list for group constraints

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group2 <- add.constraint(portfolio=init, type="group",

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                        groups=list(MICRO=c(1, 2),

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                                    SMALL=c(3, 4),

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                                    MID=c(5, 6),

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                                    LARGE=c(7, 8)),

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                        group_min=c(0.2, 0.1, 0.2, 0.2),

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                        group_max=c(0.4, 0.4, 0.4, 0.45))

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group2$category_labels <- NULL

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all.equal(group1$constraints[[3]]$groups, group2$constraints[[3]]$groups)

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opt_group1 <- optimize.portfolio(R=R, portfolio=group1, optimize_method="ROI")

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extractGroups(opt_group1)

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chart.GroupWeights(opt_group1, type="b", col="blue", pch=15, lty=2)

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opt_group2 <- optimize.portfolio(R=R, portfolio=group2, optimize_method="ROI")

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extractGroups(opt_group2)

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chart.GroupWeights(opt_group2, type="b", col="black", pch=21, bg="gray")

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