[Returnanalytics-commits] r3791 - in pkg/Dowd: . R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Wed Jul 8 14:32:02 CEST 2015
Author: dacharya
Date: 2015-07-08 14:32:01 +0200 (Wed, 08 Jul 2015)
New Revision: 3791
Added:
pkg/Dowd/R/LogtVaRPlot2DCL.R
pkg/Dowd/man/LogtVaRPlot2DCL.Rd
Modified:
pkg/Dowd/NAMESPACE
Log:
Function LogtVaRPlot2DCL added.
Modified: pkg/Dowd/NAMESPACE
===================================================================
--- pkg/Dowd/NAMESPACE 2015-07-07 22:16:23 UTC (rev 3790)
+++ pkg/Dowd/NAMESPACE 2015-07-08 12:32:01 UTC (rev 3791)
@@ -61,6 +61,7 @@
export(LogtES)
export(LogtESPlot2DHP)
export(LogtVaR)
+export(LogtVaRPlot2DCL)
export(LogtVaRPlot2DHP)
export(LopezBacktest)
export(MEFPlot)
Added: pkg/Dowd/R/LogtVaRPlot2DCL.R
===================================================================
--- pkg/Dowd/R/LogtVaRPlot2DCL.R (rev 0)
+++ pkg/Dowd/R/LogtVaRPlot2DCL.R 2015-07-08 12:32:01 UTC (rev 3791)
@@ -0,0 +1,122 @@
+#' Plots log-t VaR against confidence level
+#'
+#' Plots the VaR of a portfolio against confidence level assuming that geometric
+#' returns are Student-t distributed, for specified confidence level and
+#' holding period.
+#'
+#' @param returns Vector of daily geometric return data
+#' @param mu Mean of daily geometric return data
+#' @param sigma Standard deviation of daily geometric return data
+#' @param investment Size of investment
+#' @param df Number of degrees of freedom in the t distribution
+#' @param cl VaR confidence level and must be a vector
+#' @param hp VaR holding period and must be a scalar
+#'
+#' @note The input arguments contain either return data or else mean and
+#' standard deviation data. Accordingly, number of input arguments is either 5
+#' or 6. In case there 5 input arguments, the mean and standard deviation of
+#' data is computed from return data. See examples for details.
+#'
+#' @references Dowd, K. Measuring Market Risk, Wiley, 2007.
+#'
+#' @author Dinesh Acharya
+#' @examples
+#'
+#' # Plots VaR against confidene level given geometric return data
+#' data <- runif(5, min = 0, max = .2)
+#' LogtVaRPlot2DCL(returns = data, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 60)
+#'
+#' # Computes VaR against confidence level given mean and standard deviation of return data
+#' LogtVaRPlot2DCL(mu = .012, sigma = .03, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 40)
+#'
+#'
+#' @export
+LogtVaRPlot2DCL <- function(...){
+ if (nargs() < 5) {
+ stop("Too few arguments")
+ }
+ if (nargs() > 6) {
+ stop("Too many arguments")
+ }
+ args <- list(...)
+ if (nargs() == 6) {
+ mu <- args$mu
+ investment <- args$investment
+ df <- args$df
+ cl <- args$cl
+ sigma <- args$sigma
+ hp <- args$hp
+ }
+ if (nargs() == 5) {
+ mu <- mean(args$returns)
+ investment <- args$investment
+ df <- args$df
+ cl <- args$cl
+ sigma <- sd(args$returns)
+ hp <- args$hp
+ }
+
+ # Check that inputs have correct dimensions
+ mu <- as.matrix(mu)
+ mu.row <- dim(mu)[1]
+ mu.col <- dim(mu)[2]
+ if (max(mu.row, mu.col) > 1) {
+ stop("Mean must be a scalar")
+ }
+ sigma <- as.matrix(sigma)
+ sigma.row <- dim(sigma)[1]
+ sigma.col <- dim(sigma)[2]
+ if (max(sigma.row, sigma.col) > 1) {
+ stop("Standard deviation must be a scalar")
+ }
+ cl <- as.matrix(cl)
+ cl.row <- dim(cl)[1]
+ cl.col <- dim(cl)[2]
+ if (min(cl.row, cl.col) > 1) {
+ stop("Confidence level must be a vector")
+ }
+ hp <- as.matrix(hp)
+ hp.row <- dim(hp)[1]
+ hp.col <- dim(hp)[2]
+ if (max(hp.row, hp.col) > 1) {
+ stop("Holding period must be a scalar")
+ }
+
+ # Check that cl is read as row vector
+ if (cl.row > cl.col) {
+ cl <- t(cl)
+ }
+
+ # Check that inputs obey sign and value restrictions
+ if (sigma < 0) {
+ stop("Standard deviation must be non-negative")
+ }
+ if (max(cl) >= 1){
+ stop("Confidence level(s) must be less than 1")
+ }
+ if (min(cl) <= 0){
+ stop("Confidence level(s) must be greater than 0")
+ }
+ if (min(hp) <= 0){
+ stop("Confidence level(s) must be greater than 0")
+ }
+ # VaR estimation
+ VaR <- investment - exp( ((df-2)/df)*sigma[1,1] * sqrt(hp[1,1]) * qt(1 - cl, df)+mu[1,1]*hp[1,1]*matrix(1,cl.col,cl.row) + log(investment)
+ ) # VaR
+ # Plotting
+ plot(cl, VaR, type = "l", xlab = "Holding Period", ylab = "VaR")
+ title("Log-t VaR against holding period")
+ xmin <-min(cl)+.3*(max(cl)-min(cl))
+ text(xmin,max(VaR)-.1*(max(VaR)-min(VaR)),
+ 'Input parameters', cex=.75, font = 2)
+ text(xmin,max(VaR)-.15*(max(VaR)-min(VaR)),
+ paste('Daily mean geometric return = ',round(mu[1,1],3)),cex=.75)
+ text(xmin,max(VaR)-.2*(max(VaR)-min(VaR)),
+ paste('Stdev. of daily geometric returns = ',round(sigma[1,1],3)),cex=.75)
+ text(xmin,max(VaR)-.25*(max(VaR)-min(VaR)),
+ paste('Degrees of freedom = ',df),cex=.75)
+ text(xmin,max(VaR)-.3*(max(VaR)-min(VaR)),
+ paste('Investment size = ',investment),cex=.75)
+ text(xmin,max(VaR)-.35*(max(VaR)-min(VaR)),
+ paste('Holding period = ',hp,'days'),cex=.75)
+}
Added: pkg/Dowd/man/LogtVaRPlot2DCL.Rd
===================================================================
--- pkg/Dowd/man/LogtVaRPlot2DCL.Rd (rev 0)
+++ pkg/Dowd/man/LogtVaRPlot2DCL.Rd 2015-07-08 12:32:01 UTC (rev 3791)
@@ -0,0 +1,49 @@
+% Generated by roxygen2 (4.1.1): do not edit by hand
+% Please edit documentation in R/LogtVaRPlot2DCL.R
+\name{LogtVaRPlot2DCL}
+\alias{LogtVaRPlot2DCL}
+\title{Plots log-t VaR against confidence level}
+\usage{
+LogtVaRPlot2DCL(...)
+}
+\arguments{
+\item{returns}{Vector of daily geometric return data}
+
+\item{mu}{Mean of daily geometric return data}
+
+\item{sigma}{Standard deviation of daily geometric return data}
+
+\item{investment}{Size of investment}
+
+\item{df}{Number of degrees of freedom in the t distribution}
+
+\item{cl}{VaR confidence level and must be a vector}
+
+\item{hp}{VaR holding period and must be a scalar}
+}
+\description{
+Plots the VaR of a portfolio against confidence level assuming that geometric
+ returns are Student-t distributed, for specified confidence level and
+ holding period.
+}
+\note{
+The input arguments contain either return data or else mean and
+ standard deviation data. Accordingly, number of input arguments is either 5
+ or 6. In case there 5 input arguments, the mean and standard deviation of
+ data is computed from return data. See examples for details.
+}
+\examples{
+# Plots VaR against confidene level given geometric return data
+ data <- runif(5, min = 0, max = .2)
+ LogtVaRPlot2DCL(returns = data, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 60)
+
+ # Computes VaR against confidence level given mean and standard deviation of return data
+ LogtVaRPlot2DCL(mu = .012, sigma = .03, investment = 5, df = 6, cl = seq(.85,.99,.01), hp = 40)
+}
+\author{
+Dinesh Acharya
+}
+\references{
+Dowd, K. Measuring Market Risk, Wiley, 2007.
+}
+
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