[Returnanalytics-commits] r1990 - in pkg/PerformanceAnalytics: . R man

noreply at r-forge.r-project.org noreply at r-forge.r-project.org
Wed Jun 6 22:18:48 CEST 2012 

Author: braverock
Date: 2012-06-06 22:18:48 +0200 (Wed, 06 Jun 2012)
New Revision: 1990

Modified:
   pkg/PerformanceAnalytics/DESCRIPTION
   pkg/PerformanceAnalytics/R/chart.QQPlot.R
   pkg/PerformanceAnalytics/man/DownsideDeviation.Rd
   pkg/PerformanceAnalytics/man/chart.ECDF.Rd
   pkg/PerformanceAnalytics/man/chart.QQPlot.Rd
Log:
- update roxygen docs.  bump version

Modified: pkg/PerformanceAnalytics/DESCRIPTION
===================================================================
--- pkg/PerformanceAnalytics/DESCRIPTION	2012-06-06 18:18:50 UTC (rev 1989)
+++ pkg/PerformanceAnalytics/DESCRIPTION	2012-06-06 20:18:48 UTC (rev 1990)
@@ -31,8 +31,8 @@
 License: GPL
 URL: http://r-forge.r-project.org/projects/returnanalytics/
 Copyright: (c) 2004-2012
-Contributors: Kris Boudt,  Diethelm Wuertz, Eric Zivot
-Thanks: A special thanks for contributions from
+Contributors: Kris Boudt,  Diethelm Wuertz, Eric Zivot, Matthieu Lestel
+Thanks: A special thanks for additional contributions from
     Stefan Albrecht, Khahn Nygyen, Jeff Ryan,
     Josh Ulrich, Sankalp Upadhyay, Tobias Verbeke, 
     H. Felix Wittmann, Ram Ahluwalia

Modified: pkg/PerformanceAnalytics/R/chart.QQPlot.R
===================================================================
--- pkg/PerformanceAnalytics/R/chart.QQPlot.R	2012-06-06 18:18:50 UTC (rev 1989)
+++ pkg/PerformanceAnalytics/R/chart.QQPlot.R	2012-06-06 20:18:48 UTC (rev 1990)
@@ -62,22 +62,34 @@
 #' 
 #' library(MASS)
 #' data(managers)
+#' 
 #' x = checkData(managers[,2, drop = FALSE], na.rm = TRUE, method = "vector")
+#' 
 #' #layout(rbind(c(1,2),c(3,4)))
+#' 
 #' # Panel 1, Normal distribution
 #' chart.QQPlot(x, main = "Normal Distribution", distribution = 'norm', envelope=0.95)
 #' # Panel 2, Log-Normal distribution
 #' fit = fitdistr(1+x, 'lognormal')
-#' chart.QQPlot(1+x, main = "Log-Normal Distribution", envelope=0.95, distribution='lnorm')#, meanlog = fit$estimate[[1]], sdlog = fit$estimate[[2]])
+#' chart.QQPlot(1+x, main = "Log-Normal Distribution", envelope=0.95, distribution='lnorm')
+#' #other options could include
+#' #, meanlog = fit$estimate[[1]], sdlog = fit$estimate[[2]])
+#' 
 #' \dontrun{
 #' # Panel 3, Skew-T distribution
 #' library(sn)
 #' fit = st.mle(y=x)
-#' chart.QQPlot(x, main = "Skew T Distribution", envelope=0.95, distribution = 'st', location = fit$dp[[1]], scale = fit$dp[[2]], shape = fit$dp[[3]], df=fit$dp[[4]])
+#' chart.QQPlot(x, main = "Skew T Distribution", envelope=0.95, 
+#'              distribution = 'st', location = fit$dp[[1]], 
+#'              scale = fit$dp[[2]], shape = fit$dp[[3]], df=fit$dp[[4]])
+#' 
 #' #Panel 4: Stable Parietian
 #' library(fBasics)
 #' fit.stable = stableFit(x,doplot=FALSE)
-#' chart.QQPlot(x, main = "Stable Paretian Distribution", envelope=0.95, distribution = 'stable', alpha = fit.stable at fit$estimate[[1]], beta = fit.stable at fit$estimate[[2]], gamma = fit.stable at fit$estimate[[3]], delta = fit.stable at fit$estimate[[4]], pm = 0)
+#' chart.QQPlot(x, main = "Stable Paretian Distribution", envelope=0.95, 
+#'              distribution = 'stable', alpha = fit(stable.fit)$estimate[[1]], 
+#'              beta = fit(stable.fit)$estimate[[2]], gamma = fit(stable.fit)$estimate[[3]], 
+#'              delta = fit(stable.fit)$estimate[[4]], pm = 0)
 #' }
 #' #end examples
 #' 

Modified: pkg/PerformanceAnalytics/man/DownsideDeviation.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/DownsideDeviation.Rd	2012-06-06 18:18:50 UTC (rev 1989)
+++ pkg/PerformanceAnalytics/man/DownsideDeviation.Rd	2012-06-06 20:18:48 UTC (rev 1990)
@@ -6,7 +6,7 @@
 \title{downside risk (deviation, variance) of the return distribution}
 \usage{
   DownsideDeviation(R, MAR = 0,
-    method = c("subset", "full"), ..., potential = FALSE)
+    method = c("full", "subset"), ..., potential = FALSE)
 }
 \arguments{
   \item{R}{an xts, vector, matrix, data frame, timeSeries
@@ -34,7 +34,10 @@
   positive returns when calculating risk.  Instead of using
   the mean return or zero, it uses the Minimum Acceptable
   Return as proposed by Sharpe (which may be the mean
-  historical return or zero).
+  historical return or zero). It measures the the
+  variability of underperformance below a minimum targer
+  rate. The downside variance is the square of the downside
+  potential.
 
   To calculate it, we take the subset of returns that are
   less than the target (or Minimum Acceptable Returns
@@ -42,9 +45,15 @@
   target.  We sum the squares and divide by the total
   number of returns to get a below-target semi-variance.
 
-  \deqn{ DownsideDeviation(R , MAR)= \delta_{MAR} = \sqrt{
-  \frac{\sum^{n}_{t=1}(R_{t} - MAR)^{2}}{n} } }
+  \deqn{ DownsideDeviation(R , MAR)= \delta_{MAR} =
+  \sqrt{\sum^{n}_{t=1}\frac{ min[(R_{t} - MAR), 0]^2}{n}}}
 
+  \deqn{ DownsideVariance(R, MAR) =
+  \sum^{n}_{t=1}\frac{min[(R_{t} - MAR), 0]^2} {n}}
+
+  \deqn{DownsidePotential(R, MAR) =
+  \sum^{n}_{t=1}\frac{min[(R_{t} - MAR), 0]} {n}}
+
   where \eqn{n} is either the number of observations of the
   entire series or the number of observations in the subset
   of the series falling below the MAR.
@@ -84,6 +93,15 @@
   contribution of this nature.
 }
 \examples{
+#with data used in Bacon 2008
+
+portfolio_return <- c(0.3,2.6,1.1,-1.0,1.5,2.5,1.6,6.7,-1.4,4.0,-0.5,8.1,4.0,-3.7,-6.1,1.7,-4.9,-2.2,7.0,5.8,-6.5,2.4,-0.5,-0.9)
+MAR = 0.5
+DownsideDeviation(portfolio_return, MAR) #expected 2.55
+DownsidePotential(portfolio_return, MAR) #expected 1.37
+
+#with data of managers
+
 data(managers)
 apply(managers[,1:6], 2, sd, na.rm=TRUE)
 DownsideDeviation(managers[,1:6])  # MAR 0\%
@@ -94,12 +112,14 @@
 SemiVariance (managers[,1:6]) #calculated using method="subset"
 }
 \author{
-  Peter Carl, Brian G. Peterson
+  Peter Carl, Brian G. Peterson, Matthieu Lestel
 }
 \references{
   Sortino, F. and Price, L. Performance Measurement in a
   Downside Risk Framework. \emph{Journal of Investing}.
-  Fall 1994, 59-65. \cr
+  Fall 1994, 59-65. \cr Carl Bacon, \emph{Practical
+  portfolio performance measurement and attribution},
+  second edition 2008
 
   Plantinga, A., van der Meer, R. and Sortino, F. The
   Impact of Downside Risk on Risk-Adjusted Performance of

Modified: pkg/PerformanceAnalytics/man/chart.ECDF.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/chart.ECDF.Rd	2012-06-06 18:18:50 UTC (rev 1989)
+++ pkg/PerformanceAnalytics/man/chart.ECDF.Rd	2012-06-06 20:18:48 UTC (rev 1990)
@@ -4,8 +4,8 @@
 \usage{
   chart.ECDF(R, main = "Empirical CDF", xlab = "x",
     ylab = "F(x)", colorset = c("black", "#005AFF"),
-    lwd = 1, xlim = NULL, ylim = NULL, lty = c(1, 1),
-    element.color = "darkgray", ...)
+    lwd = 1, lty = c(1, 1), element.color = "darkgray",
+    xaxis = TRUE, yaxis = TRUE, ...)
 }
 \arguments{
   \item{R}{an xts, vector, matrix, data frame, timeSeries
@@ -20,6 +20,10 @@
   \item{ylab}{set the y-axis label, same as in
   \code{\link{plot}}}
 
+  \item{xaxis}{if true, draws the x axis}
+
+  \item{yaxis}{if true, draws the y axis}
+
   \item{colorset}{color palette to use, defaults to
   c("black", "\#005AFF"), where first value is used to
   color the step function and the second color is used for
@@ -28,12 +32,6 @@
   \item{lwd}{set the line width, same as in
   \code{\link{plot}}}
 
-  \item{xlim}{set the x-axis limit, same as in
-  \code{\link{plot}}}
-
-  \item{ylim}{set the y-axis limit, same as in
-  \code{\link{plot}}}
-
   \item{element.color}{specify the color of chart elements.
   Default is "darkgray"}
 

Modified: pkg/PerformanceAnalytics/man/chart.QQPlot.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/chart.QQPlot.Rd	2012-06-06 18:18:50 UTC (rev 1989)
+++ pkg/PerformanceAnalytics/man/chart.QQPlot.Rd	2012-06-06 20:18:48 UTC (rev 1990)
@@ -98,23 +98,36 @@
 \examples{
 library(MASS)
 data(managers)
+
 x = checkData(managers[,2, drop = FALSE], na.rm = TRUE, method = "vector")
+
 #layout(rbind(c(1,2),c(3,4)))
+
 # Panel 1, Normal distribution
 chart.QQPlot(x, main = "Normal Distribution", distribution = 'norm', envelope=0.95)
 # Panel 2, Log-Normal distribution
 fit = fitdistr(1+x, 'lognormal')
-chart.QQPlot(1+x, main = "Log-Normal Distribution", envelope=0.95, distribution='lnorm')#, meanlog = fit$estimate[[1]], sdlog = fit$estimate[[2]])
+chart.QQPlot(1+x, main = "Log-Normal Distribution", envelope=0.95, distribution='lnorm')
+#other options could include
+#, meanlog = fit$estimate[[1]], sdlog = fit$estimate[[2]])
+
 \dontrun{
 # Panel 3, Skew-T distribution
 library(sn)
 fit = st.mle(y=x)
-chart.QQPlot(x, main = "Skew T Distribution", envelope=0.95, distribution = 'st', location = fit$dp[[1]], scale = fit$dp[[2]], shape = fit$dp[[3]], df=fit$dp[[4]])
+chart.QQPlot(x, main = "Skew T Distribution", envelope=0.95,
+             distribution = 'st', location = fit$dp[[1]],
+             scale = fit$dp[[2]], shape = fit$dp[[3]], df=fit$dp[[4]])
+
 #Panel 4: Stable Parietian
 library(fBasics)
 fit.stable = stableFit(x,doplot=FALSE)
-chart.QQPlot(x, main = "Stable Paretian Distribution", envelope=0.95, distribution = 'stable', alpha = fit.stable
+chart.QQPlot(x, main = "Stable Paretian Distribution", envelope=0.95,
+             distribution = 'stable', alpha = fit(stable.fit)$estimate[[1]],
+             beta = fit(stable.fit)$estimate[[2]], gamma = fit(stable.fit)$estimate[[3]],
+             delta = fit(stable.fit)$estimate[[4]], pm = 0)
 }
+#end examples
 }
 \author{
   John Fox, ported by Peter Carl

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