[Returnanalytics-commits] r3728 - pkg/Dowd/tests/testthat

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

Author: dacharya
Date: 2015-06-23 23:25:08 +0200 (Tue, 23 Jun 2015)
New Revision: 3728

Added:
   pkg/Dowd/tests/testthat/testAdjustedVarianceCovarianceVaR.R
Log:
Complete test case for AdjustedVarianceCovarianceVaR added.

Added: pkg/Dowd/tests/testthat/testAdjustedVarianceCovarianceVaR.R
===================================================================
--- pkg/Dowd/tests/testthat/testAdjustedVarianceCovarianceVaR.R	                        (rev 0)
+++ pkg/Dowd/tests/testthat/testAdjustedVarianceCovarianceVaR.R	2015-06-23 21:25:08 UTC (rev 3728)
@@ -0,0 +1,77 @@
+test_that("Adjusted Variance Covariance VaR.",{
+
+  # Success - 1
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5,2,6)
+  cl <- .95
+  hp <- 280
+  val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp)
+  expect_equal(as.matrix(4705.9), val, tolerance=0.001)
+  
+  
+  # Success - 2
+  vc.matrix <- matrix(c(2.6, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 
+                       1, 3.4, -2, -5, -1.2, 3.2, 0, -1.2), 4, 4)
+  mu <- c(-.5, -.3, -1.2, 0)
+  skew <- -.4
+  kurtosis <- 2.2
+  positions <- c(4,1,10,3)
+  cl <- .99
+  hp <- 50
+  val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp)
+  expect_equal(as.matrix(-2898.0), val, tolerance=.1)
+  
+  # Error - 1
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5,2,6)
+  cl <- .95
+  hp <- -10
+  expect_error(val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp))
+  
+  # Error - 2
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5,2,6)
+  cl <- 1.2
+  hp <- 280
+  expect_error(val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp))
+  
+  # Error - 3
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5,2,6)
+  cl <- -.95
+  hp <- 280
+  expect_error(val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp))
+  
+  # Error - 4
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1, 1.2)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5, 2, 6)
+  cl <- -.95
+  hp <- 280
+  expect_error(val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp))
+  
+  # Error - 5
+  vc.matrix <- matrix(c(2.5, 3.4, -1.9, 4.3, 2.3, -3.1, 4.3, -1.2, 1), 3, 3)
+  mu <- c(.4, -.3, .1)
+  skew <- .5
+  kurtosis <- 1.2
+  positions <- c(5,2,6,3)
+  cl <- -.95
+  hp <- 280
+  expect_error(val <- AdjustedVarianceCovarianceVaR(vc.matrix, mu, skew, kurtosis, positions, cl, hp))
+  
+})
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