[Returnanalytics-commits] r4004 - pkg/PerformanceAnalytics/sandbox

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

Author: peter_carl
Date: 2015-11-25 23:24:01 +0100 (Wed, 25 Nov 2015)
New Revision: 4004

Modified:
   pkg/PerformanceAnalytics/sandbox/Normalize.R
Log:
- added normalization in units of std dev

Modified: pkg/PerformanceAnalytics/sandbox/Normalize.R
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Normalize.R	2015-11-18 09:47:25 UTC (rev 4003)
+++ pkg/PerformanceAnalytics/sandbox/Normalize.R	2015-11-25 22:24:01 UTC (rev 4004)
@@ -6,8 +6,11 @@
 #'
 #' 
 #' @param R
-#' @param targetMean
-#' @param targetVol
+#' @param targetMean specifies a return level to normalize each column to, in the same time units as the timeseries; default is zero
+#' @param targetVol specifies a volatility level to normalize each column to, in the same time units as the timeseries
+#' @param show.units.sd Normalize the plot's y-axis to units of annualized standard deviation
+#' @param scale number of periods in a year (daily scale = 252, monthly scale =
+#' 12, quarterly scale = 4)
 #' @param ... passes arguments to par
 #' @return xts or other time series
 #' @author Peter Carl
@@ -15,7 +18,7 @@
 #' @rdname Return.normalize
 #' @export Return.normalize
 #' @export chart.NDD
-Return.normalize <- (R, targetMean=0, targetVol=0, ...){
+Return.normalize <- function(R, targetMean=0, targetVol, ...){
   # Peter Carl
   x=checkData(R)
   x.Mean=apply(x, MARGIN=2, FUN="mean", na.rm = TRUE)
@@ -23,19 +26,36 @@
   # @TODO wil this work for vector? checkData as matrix?
   # Apply z-score
   x.Z = apply(x, MARGIN=2, FUN=function(x){ (x - mean(x, na.rm = TRUE))/sd(x, na.rm = TRUE) }) # x.Z has mean=0, sd=1
-  x.N= targetMean + x.Z * (rep(1, nrow(x.R)) %o% rep(targetVol,NCOL(x.R)))
+  x.N= targetMean + x.Z * (rep(1, nrow(x)) %o% rep(targetVol,NCOL(x)))
   x.N = as.xts(x.N, by=index(x.R))
   x.N = reclass(x.N, R)
   return(x.N)
 }
 
-chart.NDD <- function(R, targetMean=0, targetVol=0){
+chart.NDD <- function(R, targetMean=0, targetVol, show.units.sd=FALSE, ylab="Drawdown", scale=NA, ...){
  # Peter Carl 
-  x.N = Return.normalize(x)
+  # @TODO: determine periodicity of R, specify multiplier for x.NDD below
+  if(is.na(scale)) {
+    freq = periodicity(R)
+    switch(freq$scale,
+           minute = {stop("Data periodicity too high")},
+           hourly = {stop("Data periodicity too high")},
+           daily = {scale = 252},
+           weekly = {scale = 52},
+           monthly = {scale = 12},
+           quarterly = {scale = 4},
+           yearly = {scale = 1}
+    )
+  }
+  x.N = Return.normalize(R, targetMean=targetMean, targetVol=targetVol)
   x.NDD = PerformanceAnalytics:::Drawdowns(x.N)
-  par(mar = c(3, 5, 2, 3)+0.1) #c(bottom, left, top, right)
-  chart.TimeSeries(x.NDD[start.date,c(manager.col, index.cols, peer.cols)], colorset=colorset, lwd=lwdset, legend.loc=NULL, lty=lineset, main="", cex.axis=1.2, cex.lab=1.5)
-  par(op)
+  if(show.units.sd){
+    x.NDD = x.NDD/(targetVol*sqrt(scale)) # targetVol must be annualized
+    ylab = "Annualized Std Dev"
+  }
+  # par(mar = c(3, 5, 2, 3)+0.1) #c(bottom, left, top, right)
+  chart.TimeSeries(x.NDD, ylab=ylab, ...)
+  # par(op)
 }
 
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