tests/testthat/test-MVSK_via_skew_t-inactive.R

In highOrderPortfolios: Design of High-Order Portfolios Including Skewness and Kurtosis

#library(testthat)
X <- X50[, 1:10]
w0 <- rep(1/10, 10)
 
# test_that("Checking high-order design via parametric approach", { 
#   X_parameters <- estimate_skew_t(X)
# 
#   lambda <- c(1, 4, 10, 20)
#   # w_check <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "Q-MVSK", maxiter = 10000, ftol = 1e-10, wtol = 1e-10)$w
#   # save(w_check, file = "MVSK_skew_t.RData", version = 2)
#   
#   load("MVSK_skew_t.RData")
# 
#   L_MVSK_result <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "L-MVSK", maxiter = 10000, ftol = 1e-10, wtol = 1e-10)
#   expect_equal(L_MVSK_result$w, w_check, tolerance = 1e-3)
# 
#   Q_MVSK_result <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "Q-MVSK", maxiter = 10000, ftol = 1e-10, wtol = 1e-10)
#   expect_equal(Q_MVSK_result$w, w_check, tolerance = 1e-3)
# 
#   DC_result <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "DC", maxiter = 10000, ftol = 1e-10, wtol = 1e-10)
#   expect_equal(DC_result$w, w_check, tolerance = 1e-3)
# 
#   PGD_result <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "PGD", maxiter = 10000, ftol = 1e-10, wtol = 1e-10, initial_eta = 100)
#   expect_equal(PGD_result$w, w_check, tolerance = 1e-3)
# 
#   RFPA_result <- design_MVSK_portfolio_via_skew_t(lambda, X_parameters, method = "RFPA", maxiter = 10000, ftol = 1e-10, wtol = 1e-10, tau = 100)
#   expect_equal(RFPA_result$w, w_check, tolerance = 1e-3)
# })