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R/chart.RiskReturnScatter.R
In PerformanceAnalytics: Econometric Tools for Performance and Risk Analysis
#' scatter chart of returns vs risk for comparing multiple instruments
#'
#' A wrapper to create a scatter chart of annualized returns versus annualized
#' risk (standard deviation) for comparing manager performance. Also puts a box
#' plot into the margins to help identify the relative performance quartile.
#'
#'
#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of
#' asset returns
#' @param Rf risk free rate, in same period as your returns
#' @param scale number of periods in a year (daily scale = 252, monthly scale =
#' 12, quarterly scale = 4)
#' @param geometric utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns,
#' default TRUE
#' @param main set the chart title, same as in \code{plot}
#' @param add.names plots the row name with the data point. default TRUE. Can
#' be removed by setting it to NULL
#' @param xlab set the x-axis label, as in \code{\link{plot}}
#' @param ylab set the y-axis label, as in \code{\link{plot}}
#' @param method if set as "calc", then the function will calculate values from
#' the set of returns passed in. If method is set to "nocalc" then we assume
#' that R is a column of return and a column of risk (e.g., annualized returns,
#' annualized risk), in that order. Other method cases may be set for
#' different risk/return calculations.
#' @param add.sharpe this draws a Sharpe ratio line that indicates Sharpe ratio
#' levels of \code{c(1,2,3)}. Lines are drawn with a y-intercept of the risk
#' free rate and the slope of the appropriate Sharpe ratio level. Lines should
#' be removed where not appropriate (e.g., sharpe.ratio = NULL).
#' @param add.boxplots TRUE/FALSE adds a boxplot summary of the data on the
#' axis
#' @param colorset color palette to use, set by default to rational choices
#' @param symbolset from \code{pch} in \code{\link{plot}}, submit a set of
#' symbols to be used in the same order as the data sets submitted
#' @param element.color provides the color for drawing chart elements, such as
#' the box lines, axis lines, etc. Default is "darkgray"
#' @param legend.loc places a legend into one of nine locations on the chart:
#' bottomright, bottom, bottomleft, left, topleft, top, topright, right, or
#' center.
#' @param xlim set the x-axis limit, same as in \code{\link{plot}}
#' @param ylim set the y-axis limit, same as in \code{\link{plot}}
#' @param cex.axis The magnification to be used for axis annotation relative to
#' the current setting of 'cex', same as in \code{\link{plot}}.
#' @param cex.legend The magnification to be used for sizing the legend
#' relative to the current setting of 'cex'.
#' @param cex.main The magnification to be used for sizing the title relative
#' to the current setting of 'cex'.
#' @param cex.lab The magnification to be used for x and y labels relative to
#' the current setting of 'cex'.
#' @param \dots any other passthru parameters to \code{plot}
#' @note Code inspired by a chart on:
#' \url{http://zoonek2.free.fr/UNIX/48_R/03.html}
#' @author Peter Carl
###keywords ts multivariate distribution models hplot
#' @examples
#'
#' data(edhec)
#' chart.RiskReturnScatter(edhec, Rf = .04/12)
#' chart.RiskReturnScatter(edhec, Rf = .04/12, add.boxplots = TRUE)
#'
#' @export
chart.RiskReturnScatter <-
function (R, Rf = 0, main = "Annualized Return and Risk", add.names = TRUE, xlab = "Annualized Risk", ylab = "Annualized Return", method = "calc", geometric = TRUE, scale = NA, add.sharpe = c(1,2,3), add.boxplots = FALSE, colorset = 1, symbolset = 1, element.color = "darkgray", legend.loc = NULL, xlim = NULL, ylim = NULL, cex.legend = 1, cex.axis = 0.8, cex.main = 1, cex.lab = 1, ...)
{ # @author Peter Carl
# DESCRIPTION:
# A wrapper to create a scatter chart of annualized returns versus
# annualized risk (standard deviation) for comparing manager peRformance.
# Also puts a box plot into the margins to help identify the relative
# peRformance quartile.
# Inputs:
# R = usually a set of monthly return, but can also be a pre-calculated
# return and risk measure (set method = "nocalc", see below). If the input
# is a set of monthly peRformance returns, this function will calculate
# the appropriate return and risk summary according to the method flag.
# method = If method is set to "nocalc" then we assume that R is a column of
# return and a column of risk (e.g., annualized returns, annualized risk),
# in that order. Other method cases can be set for different risk/return
# calculations.
# Rf = this is the risk free rate. Remember to set this to the same
# periodicity as the data being passed in.
# add.sharpe = this draws a Sharpe ratio line that indicates Sharpe ratio
# levels. Lines are drawn with a y-intercept of the risk free rate and
# the slope of the appropriate Sharpe ratio level. Lines should be
# removed where not appropriate (e.g., sharpe.ratio = NULL).
# add.names = plots the row name with the data point. Can be removed with
# by setting it to NULL.
# add.boxplots = adds a boxplot summary of the data on the axis.
# Code inspired by a chart on:
# http://zoonek2.free.fr/UNIX/48_R/03.html
if (method == "calc") x = checkData(R, method = "zoo")
else x=R
if(!is.null(dim(Rf)))
Rf = checkData(Rf, method = "zoo")
columns = ncol(x)
rows = nrow(x)
columnnames = colnames(x)
rownames = rownames(x)
# @todo: strip out basic elements to a scatter plot wrapper
if(length(colorset) < columns)
colorset = rep(colorset, length.out = columns)
if(length(symbolset) < columns)
symbolset = rep(symbolset, length.out = columns)
# @todo: add flags to use other risk measures
if(method == "calc"){
# Assume we're passed in a series of monthly returns. First, we'll
# annualized returns and risk
comparison = t(table.AnnualizedReturns(x[,columns:1], Rf = Rf, geometric = geometric, scale = scale))
returns = comparison[,1]
risk = comparison[,2]
#sharpe = comparison[,3]
rnames = row.names(comparison)
} else {
# We have to make an assumption about the input here
#x=t(x[,ncol(x):1])
returns = x[,1]
risk = abs(x[,2])
rnames = rownames
ylab = colnames(x)[1]
xlab = colnames(x)[2]
}
# Set the charts to show the origin
if(is.null(xlim[1]))
xlim = c(0, max(risk) + 0.02)
if(is.null(ylim[1]))
ylim = c(min(c(0,returns)), max(returns) + 0.02)
if(add.boxplots){
original.layout <- par(no.readonly=TRUE)
layout( matrix( c(2,1,0,3), 2, 2, byrow=TRUE ),
c(1,6), c(4,1),
)
par(mar=c(1,1,5,2))
}
# Draw the principal scatterplot
plot(returns ~ risk,
xlab='', ylab='',
las = 1, xlim=xlim, ylim=ylim, col = colorset[columns:1], pch = symbolset[columns:1], axes= FALSE, ...)
# abline(v = 0, col = elementcolor)
if(ylim[1] != 0){
abline(h = 0, col = element.color)
}
axis(1, cex.axis = cex.axis, col = element.color)
axis(2, cex.axis = cex.axis, col = element.color)
if(!add.boxplots){
title(ylab = ylab, cex.lab = cex.lab)
title(xlab = xlab, cex.lab = cex.lab)
}
# Add Sharpe ratio lines
# @todo: Drawing Sharpe ratio lines currently throws warnings; change test statement
if(!is.na(add.sharpe[1])) {
for(line in add.sharpe) {
abline(a=(Rf*12),b=add.sharpe[line],col="gray",lty=2)
}
}
# Label the data points
if(add.names)
text(x = risk,y = returns, labels = rnames, pos=4, cex = 0.8, col = colorset[columns:1]) # adj = -0.1
# Add a rug so that data points are easier to identify
rug(side=1, risk, col = element.color)
rug(side=2, returns, col = element.color)
title(main = main, cex.main = cex.main)
if(!is.null(legend.loc)){
# There's no good place to put this automatically, except under the graph.
# That requires a different solution, but here's the quick fix
legend(legend.loc, inset = 0.02, text.col = colorset, col = colorset, cex = cex.legend, border.col = element.color, pch = symbolset, bg = "white", legend = columnnames)
}
#title(sub='From Inception', line=1)
box(col = element.color)
if(add.boxplots){
# Draw the Y-axis histogram
par(mar=c(1,2,5,1))
boxplot(returns, axes = FALSE, ylim = ylim)
title(ylab = ylab, line = 0, cex.lab = cex.lab)
# Draw the X-axis histogram
par(mar=c(5,1,1,2))
boxplot(risk, horizontal = TRUE, axes = FALSE, ylim=xlim)
title(xlab = xlab, line = 1, cex.lab = cex.lab)
par(original.layout)
}
# par(op)
}
###############################################################################
# R (http://r-project.org/) Econometrics for Performance and Risk Analysis
#
# Copyright (c) 2004-2020 Peter Carl and Brian G. Peterson
#
# This R package is distributed under the terms of the GNU Public License (GPL)
# for full details see the file COPYING
#
# $Id$
#
###############################################################################
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PerformanceAnalytics documentation built on Feb. 6, 2020, 5:11 p.m.
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#' scatter chart of returns vs risk for comparing multiple instruments
#'
#' A wrapper to create a scatter chart of annualized returns versus annualized
#' risk (standard deviation) for comparing manager performance. Also puts a box
#' plot into the margins to help identify the relative performance quartile.
#'
#'
#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of
#' asset returns
#' @param Rf risk free rate, in same period as your returns
#' @param scale number of periods in a year (daily scale = 252, monthly scale =
#' 12, quarterly scale = 4)
#' @param geometric utilize geometric chaining (TRUE) or simple/arithmetic chaining (FALSE) to aggregate returns,
#' default TRUE
#' @param main set the chart title, same as in \code{plot}
#' @param add.names plots the row name with the data point. default TRUE. Can
#' be removed by setting it to NULL
#' @param xlab set the x-axis label, as in \code{\link{plot}}
#' @param ylab set the y-axis label, as in \code{\link{plot}}
#' @param method if set as "calc", then the function will calculate values from
#' the set of returns passed in. If method is set to "nocalc" then we assume
#' that R is a column of return and a column of risk (e.g., annualized returns,
#' annualized risk), in that order. Other method cases may be set for
#' different risk/return calculations.
#' @param add.sharpe this draws a Sharpe ratio line that indicates Sharpe ratio
#' levels of \code{c(1,2,3)}. Lines are drawn with a y-intercept of the risk
#' free rate and the slope of the appropriate Sharpe ratio level. Lines should
#' be removed where not appropriate (e.g., sharpe.ratio = NULL).
#' @param add.boxplots TRUE/FALSE adds a boxplot summary of the data on the
#' axis
#' @param colorset color palette to use, set by default to rational choices
#' @param symbolset from \code{pch} in \code{\link{plot}}, submit a set of
#' symbols to be used in the same order as the data sets submitted
#' @param element.color provides the color for drawing chart elements, such as
#' the box lines, axis lines, etc. Default is "darkgray"
#' @param legend.loc places a legend into one of nine locations on the chart:
#' bottomright, bottom, bottomleft, left, topleft, top, topright, right, or
#' center.
#' @param xlim set the x-axis limit, same as in \code{\link{plot}}
#' @param ylim set the y-axis limit, same as in \code{\link{plot}}
#' @param cex.axis The magnification to be used for axis annotation relative to
#' the current setting of 'cex', same as in \code{\link{plot}}.
#' @param cex.legend The magnification to be used for sizing the legend
#' relative to the current setting of 'cex'.
#' @param cex.main The magnification to be used for sizing the title relative
#' to the current setting of 'cex'.
#' @param cex.lab The magnification to be used for x and y labels relative to
#' the current setting of 'cex'.
#' @param \dots any other passthru parameters to \code{plot}
#' @note Code inspired by a chart on:
#' \url{http://zoonek2.free.fr/UNIX/48_R/03.html}
#' @author Peter Carl
###keywords ts multivariate distribution models hplot
#' @examples
#'
#' data(edhec)
#' chart.RiskReturnScatter(edhec, Rf = .04/12)
#' chart.RiskReturnScatter(edhec, Rf = .04/12, add.boxplots = TRUE)
#'
#' @export
chart.RiskReturnScatter <-
function (R, Rf = 0, main = "Annualized Return and Risk", add.names = TRUE, xlab = "Annualized Risk", ylab = "Annualized Return", method = "calc", geometric = TRUE, scale = NA, add.sharpe = c(1,2,3), add.boxplots = FALSE, colorset = 1, symbolset = 1, element.color = "darkgray", legend.loc = NULL, xlim = NULL, ylim = NULL, cex.legend = 1, cex.axis = 0.8, cex.main = 1, cex.lab = 1, ...)
{ # @author Peter Carl
# DESCRIPTION:
# A wrapper to create a scatter chart of annualized returns versus
# annualized risk (standard deviation) for comparing manager peRformance.
# Also puts a box plot into the margins to help identify the relative
# peRformance quartile.
# Inputs:
# R = usually a set of monthly return, but can also be a pre-calculated
# return and risk measure (set method = "nocalc", see below). If the input
# is a set of monthly peRformance returns, this function will calculate
# the appropriate return and risk summary according to the method flag.
# method = If method is set to "nocalc" then we assume that R is a column of
# return and a column of risk (e.g., annualized returns, annualized risk),
# in that order. Other method cases can be set for different risk/return
# calculations.
# Rf = this is the risk free rate. Remember to set this to the same
# periodicity as the data being passed in.
# add.sharpe = this draws a Sharpe ratio line that indicates Sharpe ratio
# levels. Lines are drawn with a y-intercept of the risk free rate and
# the slope of the appropriate Sharpe ratio level. Lines should be
# removed where not appropriate (e.g., sharpe.ratio = NULL).
# add.names = plots the row name with the data point. Can be removed with
# by setting it to NULL.
# add.boxplots = adds a boxplot summary of the data on the axis.
# Code inspired by a chart on:
# http://zoonek2.free.fr/UNIX/48_R/03.html
if (method == "calc") x = checkData(R, method = "zoo")
else x=R
if(!is.null(dim(Rf)))
Rf = checkData(Rf, method = "zoo")
columns = ncol(x)
rows = nrow(x)
columnnames = colnames(x)
rownames = rownames(x)
# @todo: strip out basic elements to a scatter plot wrapper
if(length(colorset) < columns)
colorset = rep(colorset, length.out = columns)
if(length(symbolset) < columns)
symbolset = rep(symbolset, length.out = columns)
# @todo: add flags to use other risk measures
if(method == "calc"){
# Assume we're passed in a series of monthly returns. First, we'll
# annualized returns and risk
comparison = t(table.AnnualizedReturns(x[,columns:1], Rf = Rf, geometric = geometric, scale = scale))
returns = comparison[,1]
risk = comparison[,2]
#sharpe = comparison[,3]
rnames = row.names(comparison)
} else {
# We have to make an assumption about the input here
#x=t(x[,ncol(x):1])
returns = x[,1]
risk = abs(x[,2])
rnames = rownames
ylab = colnames(x)[1]
xlab = colnames(x)[2]
}
# Set the charts to show the origin
if(is.null(xlim[1]))
xlim = c(0, max(risk) + 0.02)
if(is.null(ylim[1]))
ylim = c(min(c(0,returns)), max(returns) + 0.02)
if(add.boxplots){
original.layout <- par(no.readonly=TRUE)
layout( matrix( c(2,1,0,3), 2, 2, byrow=TRUE ),
c(1,6), c(4,1),
)
par(mar=c(1,1,5,2))
}
# Draw the principal scatterplot
plot(returns ~ risk,
xlab='', ylab='',
las = 1, xlim=xlim, ylim=ylim, col = colorset[columns:1], pch = symbolset[columns:1], axes= FALSE, ...)
# abline(v = 0, col = elementcolor)
if(ylim[1] != 0){
abline(h = 0, col = element.color)
}
axis(1, cex.axis = cex.axis, col = element.color)
axis(2, cex.axis = cex.axis, col = element.color)
if(!add.boxplots){
title(ylab = ylab, cex.lab = cex.lab)
title(xlab = xlab, cex.lab = cex.lab)
}
# Add Sharpe ratio lines
# @todo: Drawing Sharpe ratio lines currently throws warnings; change test statement
if(!is.na(add.sharpe[1])) {
for(line in add.sharpe) {
abline(a=(Rf*12),b=add.sharpe[line],col="gray",lty=2)
}
}
# Label the data points
if(add.names)
text(x = risk,y = returns, labels = rnames, pos=4, cex = 0.8, col = colorset[columns:1]) # adj = -0.1
# Add a rug so that data points are easier to identify
rug(side=1, risk, col = element.color)
rug(side=2, returns, col = element.color)
title(main = main, cex.main = cex.main)
if(!is.null(legend.loc)){
# There's no good place to put this automatically, except under the graph.
# That requires a different solution, but here's the quick fix
legend(legend.loc, inset = 0.02, text.col = colorset, col = colorset, cex = cex.legend, border.col = element.color, pch = symbolset, bg = "white", legend = columnnames)
}
#title(sub='From Inception', line=1)
box(col = element.color)
if(add.boxplots){
# Draw the Y-axis histogram
par(mar=c(1,2,5,1))
boxplot(returns, axes = FALSE, ylim = ylim)
title(ylab = ylab, line = 0, cex.lab = cex.lab)
# Draw the X-axis histogram
par(mar=c(5,1,1,2))
boxplot(risk, horizontal = TRUE, axes = FALSE, ylim=xlim)
title(xlab = xlab, line = 1, cex.lab = cex.lab)
par(original.layout)
}
# par(op)
}
###############################################################################
# R (http://r-project.org/) Econometrics for Performance and Risk Analysis
#
# Copyright (c) 2004-2020 Peter Carl and Brian G. Peterson
#
# This R package is distributed under the terms of the GNU Public License (GPL)
# for full details see the file COPYING
#
# $Id$
#
###############################################################################
Try the PerformanceAnalytics package in your browser
Any scripts or data that you put into this service are public.
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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