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braverock
GitHub Repository: braverock/portfolioanalytics
 Path: blob/master/inst/tests/test_all_constraints.R
1433 views
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require(testthat)

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require(PortfolioAnalytics)

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context("constraints")

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N <- 4

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

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# Weight_sum constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="weight_sum", 

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                             min_sum=0.99, 

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                             max_sum=1.01)

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# Box constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="box", 

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                             min=0, 

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                             max=1)

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# Group constraint

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init.portf <- add.constraint(portfolio=init.portf,

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                             type="group",

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                             groups=list(c(1, 3), c(2, 4)),

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                             group_min=c(0.15, 0.25),

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                             group_max=c(0.65, 0.55))

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# Turnover constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="turnover", 

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                             turnover_target=0.6)

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# Diversification constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="diversification", 

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                             div_target=0.55)

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# Position limit constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="position_limit", 

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                             max_pos=3, 

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                             max_pos_long=2,

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                             max_pos_short=1)

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# Return constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="return", 

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                             return_target=0.007)

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# Factor exposure constraint

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init.portf <- add.constraint(portfolio=init.portf, 

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                             type="factor_exposure",

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                             B=rep(1, N),

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                             lower=0.9, 

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                             upper=1.1)

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tmp_constraints <- PortfolioAnalytics:::get_constraints(init.portf)

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test_that("weight_sum constraint is consistent", {

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  expect_that(tmp_constraints$min_sum, equals(0.99))

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  expect_that(tmp_constraints$max_sum, equals(1.01))

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})

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test_that("box constraint is consistent", {

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  expect_that(as.numeric(tmp_constraints$min), equals(rep(0, N)))

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  expect_that(as.numeric(tmp_constraints$max), equals(rep(1, N)))

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})

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test_that("group constraint is consistent", {

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  expect_that(is.list(tmp_constraints$groups), is_true())

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  expect_that(tmp_constraints$groups[[1]], equals(c(1, 3)))

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  expect_that(tmp_constraints$groups[[2]], equals(c(2, 4)))

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  expect_that(tmp_constraints$group_labels, equals(c("group1", "group2")))

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  expect_that(tmp_constraints$cLO, equals(c(0.15, 0.25)))

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  expect_that(tmp_constraints$cUP, equals(c(0.65, 0.55)))

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})

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test_that("turnover constraint is consistent", {

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  expect_that(tmp_constraints$turnover_target, equals(0.6))

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})

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test_that("diversification constraint is consistent", {

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  expect_that(tmp_constraints$div_target, equals(0.55))

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})

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test_that("position limit constraint is consistent", {

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  expect_that(tmp_constraints$max_pos, equals(3))

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  expect_that(tmp_constraints$max_pos_long, equals(2))

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  expect_that(tmp_constraints$max_pos_short, equals(1))

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})

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test_that("return constraint is consistent", {

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  expect_that(tmp_constraints$return_target, equals(0.007))

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})

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B <- matrix(1, ncol=1, nrow=N)

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rownames(B) <- paste("Asset", 1:N, sep=".")

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colnames(B) <- "factor1"

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test_that("factor exposure constraint is consistent", {

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  expect_that(tmp_constraints$B, equals(B))

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  expect_that(tmp_constraints$lower, equals(0.9))

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  expect_that(tmp_constraints$upper, equals(1.1))

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})

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