[Returnanalytics-commits] r3522 - in pkg/PerformanceAnalytics: . R man tests/Examples
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Tue Sep 2 23:09:56 CEST 2014
Author: braverock
Date: 2014-09-02 23:09:55 +0200 (Tue, 02 Sep 2014)
New Revision: 3522
Added:
pkg/PerformanceAnalytics/man/table.ProbOutPerformance.Rd
Modified:
pkg/PerformanceAnalytics/DESCRIPTION
pkg/PerformanceAnalytics/NAMESPACE
pkg/PerformanceAnalytics/R/CoMoments.R
pkg/PerformanceAnalytics/R/ES.R
pkg/PerformanceAnalytics/R/MultivariateMoments.R
pkg/PerformanceAnalytics/R/table.ProbOutperformance.R
pkg/PerformanceAnalytics/R/zzz.R
pkg/PerformanceAnalytics/man/ActivePremium.Rd
pkg/PerformanceAnalytics/man/AdjustedSharpeRatio.Rd
pkg/PerformanceAnalytics/man/AppraisalRatio.Rd
pkg/PerformanceAnalytics/man/AverageDrawdown.Rd
pkg/PerformanceAnalytics/man/BernardoLedoitRatio.Rd
pkg/PerformanceAnalytics/man/BetaCoMoments.Rd
pkg/PerformanceAnalytics/man/BurkeRatio.Rd
pkg/PerformanceAnalytics/man/CAPM.RiskPremium.Rd
pkg/PerformanceAnalytics/man/CAPM.alpha.Rd
pkg/PerformanceAnalytics/man/CAPM.beta.Rd
pkg/PerformanceAnalytics/man/CAPM.dynamic.Rd
pkg/PerformanceAnalytics/man/CAPM.epsilon.Rd
pkg/PerformanceAnalytics/man/CAPM.jensenAlpha.Rd
pkg/PerformanceAnalytics/man/CDD.Rd
pkg/PerformanceAnalytics/man/CalmarRatio.Rd
pkg/PerformanceAnalytics/man/CoMoments.Rd
pkg/PerformanceAnalytics/man/DRatio.Rd
pkg/PerformanceAnalytics/man/DownsideDeviation.Rd
pkg/PerformanceAnalytics/man/DownsideFrequency.Rd
pkg/PerformanceAnalytics/man/DrawdownDeviation.Rd
pkg/PerformanceAnalytics/man/DrawdownPeak.Rd
pkg/PerformanceAnalytics/man/ES.Rd
pkg/PerformanceAnalytics/man/FamaBeta.Rd
pkg/PerformanceAnalytics/man/Frequency.Rd
pkg/PerformanceAnalytics/man/HurstIndex.Rd
pkg/PerformanceAnalytics/man/InformationRatio.Rd
pkg/PerformanceAnalytics/man/Kappa.Rd
pkg/PerformanceAnalytics/man/KellyRatio.Rd
pkg/PerformanceAnalytics/man/M2Sortino.Rd
pkg/PerformanceAnalytics/man/MSquared.Rd
pkg/PerformanceAnalytics/man/MSquaredExcess.Rd
pkg/PerformanceAnalytics/man/MarketTiming.Rd
pkg/PerformanceAnalytics/man/MartinRatio.Rd
pkg/PerformanceAnalytics/man/MeanAbsoluteDeviation.Rd
pkg/PerformanceAnalytics/man/Modigliani.Rd
pkg/PerformanceAnalytics/man/NetSelectivity.Rd
pkg/PerformanceAnalytics/man/Omega.Rd
pkg/PerformanceAnalytics/man/OmegaExcessReturn.Rd
pkg/PerformanceAnalytics/man/OmegaSharpeRatio.Rd
pkg/PerformanceAnalytics/man/PainIndex.Rd
pkg/PerformanceAnalytics/man/PainRatio.Rd
pkg/PerformanceAnalytics/man/ProspectRatio.Rd
pkg/PerformanceAnalytics/man/Return.Geltner.Rd
pkg/PerformanceAnalytics/man/Return.annualized.Rd
pkg/PerformanceAnalytics/man/Return.annualized.excess.Rd
pkg/PerformanceAnalytics/man/Return.calculate.Rd
pkg/PerformanceAnalytics/man/Return.clean.Rd
pkg/PerformanceAnalytics/man/Return.cumulative.Rd
pkg/PerformanceAnalytics/man/Return.excess.Rd
pkg/PerformanceAnalytics/man/Return.read.Rd
pkg/PerformanceAnalytics/man/Return.relative.Rd
pkg/PerformanceAnalytics/man/Selectivity.Rd
pkg/PerformanceAnalytics/man/SharpeRatio.Rd
pkg/PerformanceAnalytics/man/SharpeRatio.annualized.Rd
pkg/PerformanceAnalytics/man/SkewnessKurtosisRatio.Rd
pkg/PerformanceAnalytics/man/SmoothingIndex.Rd
pkg/PerformanceAnalytics/man/SortinoRatio.Rd
pkg/PerformanceAnalytics/man/SpecificRisk.Rd
pkg/PerformanceAnalytics/man/StdDev.Rd
pkg/PerformanceAnalytics/man/StdDev.annualized.Rd
pkg/PerformanceAnalytics/man/SystematicRisk.Rd
pkg/PerformanceAnalytics/man/TotalRisk.Rd
pkg/PerformanceAnalytics/man/TrackingError.Rd
pkg/PerformanceAnalytics/man/TreynorRatio.Rd
pkg/PerformanceAnalytics/man/UlcerIndex.Rd
pkg/PerformanceAnalytics/man/UpDownRatios.Rd
pkg/PerformanceAnalytics/man/UpsideFrequency.Rd
pkg/PerformanceAnalytics/man/UpsidePotentialRatio.Rd
pkg/PerformanceAnalytics/man/UpsideRisk.Rd
pkg/PerformanceAnalytics/man/VaR.Rd
pkg/PerformanceAnalytics/man/VolatilitySkewness.Rd
pkg/PerformanceAnalytics/man/apply.fromstart.Rd
pkg/PerformanceAnalytics/man/apply.rolling.Rd
pkg/PerformanceAnalytics/man/centeredmoments.Rd
pkg/PerformanceAnalytics/man/chart.ACF.Rd
pkg/PerformanceAnalytics/man/chart.Bar.Rd
pkg/PerformanceAnalytics/man/chart.BarVaR.Rd
pkg/PerformanceAnalytics/man/chart.Boxplot.Rd
pkg/PerformanceAnalytics/man/chart.CaptureRatios.Rd
pkg/PerformanceAnalytics/man/chart.Correlation.Rd
pkg/PerformanceAnalytics/man/chart.CumReturns.Rd
pkg/PerformanceAnalytics/man/chart.Drawdown.Rd
pkg/PerformanceAnalytics/man/chart.ECDF.Rd
pkg/PerformanceAnalytics/man/chart.Events.Rd
pkg/PerformanceAnalytics/man/chart.Histogram.Rd
pkg/PerformanceAnalytics/man/chart.QQPlot.Rd
pkg/PerformanceAnalytics/man/chart.Regression.Rd
pkg/PerformanceAnalytics/man/chart.RelativePerformance.Rd
pkg/PerformanceAnalytics/man/chart.RiskReturnScatter.Rd
pkg/PerformanceAnalytics/man/chart.RollingCorrelation.Rd
pkg/PerformanceAnalytics/man/chart.RollingMean.Rd
pkg/PerformanceAnalytics/man/chart.RollingPerformance.Rd
pkg/PerformanceAnalytics/man/chart.RollingRegression.Rd
pkg/PerformanceAnalytics/man/chart.Scatter.Rd
pkg/PerformanceAnalytics/man/chart.SnailTrail.Rd
pkg/PerformanceAnalytics/man/chart.StackedBar.Rd
pkg/PerformanceAnalytics/man/chart.TimeSeries.Rd
pkg/PerformanceAnalytics/man/chart.VaRSensitivity.Rd
pkg/PerformanceAnalytics/man/charts.PerformanceSummary.Rd
pkg/PerformanceAnalytics/man/charts.RollingPerformance.Rd
pkg/PerformanceAnalytics/man/checkData.Rd
pkg/PerformanceAnalytics/man/clean.boudt.Rd
pkg/PerformanceAnalytics/man/findDrawdowns.Rd
pkg/PerformanceAnalytics/man/kurtosis.Rd
pkg/PerformanceAnalytics/man/legend.Rd
pkg/PerformanceAnalytics/man/lpm.Rd
pkg/PerformanceAnalytics/man/maxDrawdown.Rd
pkg/PerformanceAnalytics/man/mean.geometric.Rd
pkg/PerformanceAnalytics/man/skewness.Rd
pkg/PerformanceAnalytics/man/sortDrawdowns.Rd
pkg/PerformanceAnalytics/man/table.AnnualizedReturns.Rd
pkg/PerformanceAnalytics/man/table.Arbitrary.Rd
pkg/PerformanceAnalytics/man/table.Autocorrelation.Rd
pkg/PerformanceAnalytics/man/table.CAPM.Rd
pkg/PerformanceAnalytics/man/table.CalendarReturns.Rd
pkg/PerformanceAnalytics/man/table.CaptureRatios.Rd
pkg/PerformanceAnalytics/man/table.Correlation.Rd
pkg/PerformanceAnalytics/man/table.Distributions.Rd
pkg/PerformanceAnalytics/man/table.DownsideRisk.Rd
pkg/PerformanceAnalytics/man/table.DownsideRiskRatio.Rd
pkg/PerformanceAnalytics/man/table.Drawdowns.Rd
pkg/PerformanceAnalytics/man/table.DrawdownsRatio.Rd
pkg/PerformanceAnalytics/man/table.HigherMoments.Rd
pkg/PerformanceAnalytics/man/table.InformationRatio.Rd
pkg/PerformanceAnalytics/man/table.MonthlyReturns.Rd
pkg/PerformanceAnalytics/man/table.RollingPeriods.Rd
pkg/PerformanceAnalytics/man/table.SpecificRisk.Rd
pkg/PerformanceAnalytics/man/table.Variability.Rd
pkg/PerformanceAnalytics/man/textplot.Rd
pkg/PerformanceAnalytics/man/zerofill.Rd
pkg/PerformanceAnalytics/tests/Examples/PerformanceAnalytics-Ex.Rout.save
Log:
- clean check in R-release ahead of new CRAN version
Modified: pkg/PerformanceAnalytics/DESCRIPTION
===================================================================
--- pkg/PerformanceAnalytics/DESCRIPTION 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/DESCRIPTION 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,7 +1,7 @@
Package: PerformanceAnalytics
Type: Package
Title: Econometric tools for performance and risk analysis.
-Version: 1.1.6
+Version: 1.1.3522
Date: $Date$
Author: Peter Carl, Brian G. Peterson
Maintainer: Brian G. Peterson <brian at braverock.com>
@@ -14,10 +14,10 @@
work with irregular return data as well, and increasing
numbers of functions will work with P&L or price data
where possible.
+Imports: zoo
Depends:
R (>= 3.0.0),
- zoo,
- xts (>= 0.8-9)
+ xts (>= 0.9)
Suggests:
Hmisc,
MASS,
Modified: pkg/PerformanceAnalytics/NAMESPACE
===================================================================
--- pkg/PerformanceAnalytics/NAMESPACE 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/NAMESPACE 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,5 @@
+# Generated by roxygen2 (4.0.1): do not edit by hand
+
S3method(textplot,character)
S3method(textplot,data.frame)
S3method(textplot,default)
@@ -29,7 +31,9 @@
export(CalculateReturns)
export(CalmarRatio)
export(CoKurtosis)
+export(CoKurtosisMatrix)
export(CoSkewness)
+export(CoSkewnessMatrix)
export(CoVariance)
export(DRatio)
export(DownsideDeviation)
@@ -46,6 +50,8 @@
export(Kappa)
export(KellyRatio)
export(M2Sortino)
+export(M3.MM)
+export(M4.MM)
export(MSquared)
export(MSquaredExcess)
export(MarketTiming)
@@ -202,6 +208,7 @@
export(table.DrawdownsRatio)
export(table.HigherMoments)
export(table.InformationRatio)
+export(table.ProbOutPerformance)
export(table.SFM)
export(table.SpecificRisk)
export(table.Stats)
@@ -231,7 +238,7 @@
export(tol9qualitative)
export(zerofill)
import(xts)
+import(zoo)
importFrom(stats,sd)
importFrom(utils,packageDescription)
-importFrom(zoo,rollapply)
useDynLib(PerformanceAnalytics)
Modified: pkg/PerformanceAnalytics/R/CoMoments.R
===================================================================
--- pkg/PerformanceAnalytics/R/CoMoments.R 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/R/CoMoments.R 2014-09-02 21:09:55 UTC (rev 3522)
@@ -99,6 +99,8 @@
###############################################################################
+#' @rdname CoMoments
+#' @export
CoSkewnessMatrix <-
function (R, ...)
{ # @author Kris Boudt
@@ -107,6 +109,8 @@
###############################################################################
+#' @rdname CoMoments
+#' @export
CoKurtosisMatrix <-
function (R, ...)
{ # @author Kris Boudt
@@ -175,10 +179,13 @@
#' @concept co-moments
#' @concept moments
#' @aliases CoMoments CoVariance CoSkewness CoKurtosis
+#' @param R an xts, vector, matrix, data frame, timeSeries or zoo object of
+#' asset returns
#' @param Ra an xts, vector, matrix, data frame, timeSeries or zoo object of
#' asset returns
#' @param Rb an xts, vector, matrix, data frame, timeSeries or zoo object of
#' index, benchmark, portfolio, or secondary asset returns to compare against
+#' @param \dots any other passthru parameters
#' @author Kris Boudt, Peter Carl, Brian Peterson
#' @seealso \code{\link{BetaCoSkewness}} \cr \code{\link{BetaCoKurtosis}} \cr
#' \code{\link{BetaCoMoments}}
Modified: pkg/PerformanceAnalytics/R/ES.R
===================================================================
--- pkg/PerformanceAnalytics/R/ES.R 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/R/ES.R 2014-09-02 21:09:55 UTC (rev 3522)
@@ -46,7 +46,7 @@
#' judgement on which approach is preferable.
#' @section Background: This function provides several estimation methods for
#' the Expected Shortfall (ES) (also called Expected Tail Loss (ETL)
-#' orConditional Value at Risk (CVaR)) of a return series and the Component ES
+#' or Conditional Value at Risk (CVaR)) of a return series and the Component ES
#' (ETL/CVaR) of a portfolio.
#'
#' At a preset probability level denoted \eqn{c}, which typically is between 1
Modified: pkg/PerformanceAnalytics/R/MultivariateMoments.R
===================================================================
--- pkg/PerformanceAnalytics/R/MultivariateMoments.R 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/R/MultivariateMoments.R 2014-09-02 21:09:55 UTC (rev 3522)
@@ -29,6 +29,8 @@
}
#'@useDynLib PerformanceAnalytics
+#'@export
+#'@rdname CoMoments
M3.MM = function(R, ...){
if(!hasArg(mu)) mu = colMeans(R) else mu=list(...)$mu
@@ -69,6 +71,8 @@
}
#'@useDynLib PerformanceAnalytics
+#'@export
+#'@rdname CoMoments
M4.MM = function(R, ...){
if(!hasArg(mu)) mu = colMeans(R) else mu=list(...)$mu
Modified: pkg/PerformanceAnalytics/R/table.ProbOutperformance.R
===================================================================
--- pkg/PerformanceAnalytics/R/table.ProbOutperformance.R 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/R/table.ProbOutperformance.R 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,11 +1,11 @@
-#' Performance Reporting Fund vs Benchmark
+#' Outperformance Report of Asset vs Benchmark
#'
-#' Table of Performance Reporting vs Benchmark
+#' Table of Outperformance Reporting vs Benchmark
#'
#' Returns a table that contains the counts and probabilities
#' of outperformance relative to benchmark for the various period_lengths
#'
-#' Tool for Robustness analysis of a strategy, can be used to
+#' Tool for robustness analysis of an asset or strategy, can be used to
#' give the probability an investor investing at any point in time will
#' outperform the benchmark over a given horizon. Calculates Count of
#' trailing periods where a fund outperformed its benchmark and calculates
@@ -27,6 +27,7 @@
#'
#' table.ProbOutPerformance(edhec[,1],edhec[,2])
#' title(main='Table of Convertible Arbitrage vs Benchmark')
+#'
#' @export
table.ProbOutPerformance = function(R,Rb,period_lengths=c(1,3,6,9,12,18,36)){
if(nrow(R)!=nrow(Rb)){
Modified: pkg/PerformanceAnalytics/R/zzz.R
===================================================================
--- pkg/PerformanceAnalytics/R/zzz.R 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/R/zzz.R 2014-09-02 21:09:55 UTC (rev 3522)
@@ -19,8 +19,8 @@
#' @importFrom utils packageDescription
#' @importFrom stats sd
-#' @importFrom zoo rollapply
#' @import xts
+#' @import zoo
NULL
###############################################################################
Modified: pkg/PerformanceAnalytics/man/ActivePremium.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/ActivePremium.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/ActivePremium.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{ActiveReturn}
\alias{ActivePremium}
\alias{ActiveReturn}
@@ -6,20 +7,20 @@
ActiveReturn(Ra, Rb, scale = NA)
}
\arguments{
- \item{Ra}{return vector of the portfolio}
+\item{Ra}{return vector of the portfolio}
- \item{Rb}{return vector of the benchmark asset}
+\item{Rb}{return vector of the benchmark asset}
- \item{scale}{number of periods in a year (daily scale =
- 252, monthly scale = 12, quarterly scale = 4)}
+\item{scale}{number of periods in a year (daily scale = 252, monthly scale =
+12, quarterly scale = 4)}
}
\description{
-The return on an investment's annualized return minus the
-benchmark's annualized return.
+The return on an investment's annualized return minus the benchmark's
+annualized return.
}
\details{
-Active Premium = Investment's annualized return -
-Benchmark's annualized return
+Active Premium = Investment's annualized return - Benchmark's annualized
+return
Also commonly referred to as 'active return'.
}
Modified: pkg/PerformanceAnalytics/man/AdjustedSharpeRatio.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/AdjustedSharpeRatio.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/AdjustedSharpeRatio.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{AdjustedSharpeRatio}
\alias{AdjustedSharpeRatio}
\title{Adjusted Sharpe ratio of the return distribution}
@@ -5,26 +6,22 @@
AdjustedSharpeRatio(R, Rf = 0, ...)
}
\arguments{
- \item{R}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{R}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{Rf}{the risk free rate}
+\item{Rf}{the risk free rate}
- \item{\dots}{any other passthru parameters}
+\item{\dots}{any other passthru parameters}
}
\description{
-Adjusted Sharpe ratio was introduced by Pezier and White
-(2006) to adjusts for skewness and kurtosis by
-incorporating a penalty factor for negative skewness and
-excess kurtosis.
+Adjusted Sharpe ratio was introduced by Pezier and White (2006) to adjusts
+for skewness and kurtosis by incorporating a penalty factor for negative skewness
+and excess kurtosis.
}
\details{
-\deqn{Adjusted Sharpe Ratio = SR * [1 + (\frac{S}{6}) * SR
-- (\frac{K - 3}{24}) * SR^2]}{Adjusted Sharpe ratio = SR x
-[1 + (S/6) x SR - ((K-3) / 24) x SR^2]}
+\deqn{Adjusted Sharpe Ratio = SR * [1 + (\frac{S}{6}) * SR - (\frac{K - 3}{24}) * SR^2]}{Adjusted Sharpe ratio = SR x [1 + (S/6) x SR - ((K-3) / 24) x SR^2]}
-where \eqn{SR} is the sharpe ratio with data annualized,
-\eqn{S} is the skewness and \eqn{K} is the kurtosis
+where \eqn{SR} is the sharpe ratio with data annualized, \eqn{S} is the skewness and \eqn{K} is the kurtosis
}
\examples{
data(portfolio_bacon)
@@ -38,8 +35,8 @@
Matthieu Lestel
}
\references{
-Carl Bacon, \emph{Practical portfolio performance
-measurement and attribution}, second edition 2008 p.99
+Carl Bacon, \emph{Practical portfolio performance measurement
+and attribution}, second edition 2008 p.99
}
\keyword{distribution}
\keyword{models}
Modified: pkg/PerformanceAnalytics/man/AppraisalRatio.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/AppraisalRatio.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/AppraisalRatio.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{AppraisalRatio}
\alias{AppraisalRatio}
\title{Appraisal ratio of the return distribution}
@@ -6,46 +7,36 @@
"alternative"), ...)
}
\arguments{
- \item{Ra}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{Ra}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{Rb}{return vector of the benchmark asset}
+\item{Rb}{return vector of the benchmark asset}
- \item{Rf}{risk free rate, in same period as your returns}
+\item{Rf}{risk free rate, in same period as your returns}
- \item{method}{is one of "appraisal" to calculate
- appraisal ratio, "modified" to calculate modified
- Jensen's alpha or "alternative" to calculate alternative
- Jensen's alpha.}
+\item{method}{is one of "appraisal" to calculate appraisal ratio, "modified" to
+calculate modified Jensen's alpha or "alternative" to calculate alternative
+Jensen's alpha.}
- \item{\dots}{any other passthru parameters}
+\item{\dots}{any other passthru parameters}
}
\description{
-Appraisal ratio is the Jensen's alpha adjusted for specific
-risk. The numerator is divided by specific risk instead of
-total risk.
+Appraisal ratio is the Jensen's alpha adjusted for specific risk. The numerator
+is divided by specific risk instead of total risk.
}
\details{
Modified Jensen's alpha is Jensen's alpha divided by beta.
-Alternative Jensen's alpha is Jensen's alpha divided by
-systematic risk.
+Alternative Jensen's alpha is Jensen's alpha divided by systematic risk.
-\deqn{Appraisal ratio =
-\frac{\alpha}{\sigma_{\epsilon}}}{Appraisal ratio =
-Jensen's alpha / specific risk}
+\deqn{Appraisal ratio = \frac{\alpha}{\sigma_{\epsilon}}}{Appraisal ratio = Jensen's alpha / specific risk}
-\deqn{Modified Jensen's alpha =
-\frac{\alpha}{\beta}}{Modified Jensen's alpha = Jensen's
-alpha / beta}
+\deqn{Modified Jensen's alpha = \frac{\alpha}{\beta}}{Modified Jensen's alpha = Jensen's alpha / beta}
-\deqn{Alternative Jensen's alpha =
-\frac{\alpha}{\sigma_S}}{Alternative Jensen's alpha =
-Jensen's alpha / systematic risk}
+\deqn{Alternative Jensen's alpha = \frac{\alpha}{\sigma_S}}{Alternative Jensen's alpha = Jensen's alpha / systematic risk}
-where \eqn{alpha} is the Jensen's alpha,
-\eqn{\sigma_{epsilon}} is the specific risk, \eqn{\sigma_S}
-is the systematic risk.
+where \eqn{alpha} is the Jensen's alpha, \eqn{\sigma_{epsilon}} is the specific risk,
+\eqn{\sigma_S} is the systematic risk.
}
\examples{
data(portfolio_bacon)
@@ -61,8 +52,8 @@
Matthieu Lestel
}
\references{
-Carl Bacon, \emph{Practical portfolio performance
-measurement and attribution}, second edition 2008 p.77
+Carl Bacon, \emph{Practical portfolio performance measurement
+and attribution}, second edition 2008 p.77
}
\keyword{distribution}
\keyword{models}
Modified: pkg/PerformanceAnalytics/man/AverageDrawdown.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/AverageDrawdown.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/AverageDrawdown.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{AverageDrawdown}
\alias{AverageDrawdown}
\alias{AverageRecovery}
@@ -8,14 +9,14 @@
AverageRecovery(R, ...)
}
\arguments{
- \item{R}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{R}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{\dots}{any other passthru parameters}
+\item{\dots}{any other passthru parameters}
}
\description{
-ADD = abs(sum[j=1,2,...,d](D_j/d)) where D'_j = jth
-drawdown over entire period d = total number of drawdowns
-in the entire period
+ADD = abs(sum[j=1,2,...,d](D_j/d)) where
+D'_j = jth drawdown over entire period
+d = total number of drawdowns in the entire period
}
Modified: pkg/PerformanceAnalytics/man/BernardoLedoitRatio.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/BernardoLedoitRatio.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/BernardoLedoitRatio.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{BernardoLedoitRatio}
\alias{BernardoLedoitRatio}
\title{Bernardo and Ledoit ratio of the return distribution}
@@ -5,25 +6,20 @@
BernardoLedoitRatio(R, ...)
}
\arguments{
- \item{R}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{R}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{\dots}{any other passthru parameters}
+\item{\dots}{any other passthru parameters}
}
\description{
-To calculate Bernardo and Ledoit ratio we take the sum of
-the subset of returns that are above 0 and we divide it by
-the opposite of the sum of the subset of returns that are
-below 0
+To calculate Bernardo and Ledoit ratio we take the sum of the subset of
+returns that are above 0 and we divide it by the opposite of the sum of
+the subset of returns that are below 0
}
\details{
-\deqn{BernardoLedoitRatio(R) =
-\frac{\frac{1}{n}\sum^{n}_{t=1}{max(R_{t},0)}}{\frac{1}{n}\sum^{n}_{t=1}{max(-R_{t},0)}}}{BernardoLedoitRatio(R)
-= 1/n*sum(t=1..n)(max(R(t),0)) /
-1/n*sum(t=1..n)(max(-R(t),0))}
+\deqn{BernardoLedoitRatio(R) = \frac{\frac{1}{n}\sum^{n}_{t=1}{max(R_{t},0)}}{\frac{1}{n}\sum^{n}_{t=1}{max(-R_{t},0)}}}{BernardoLedoitRatio(R) = 1/n*sum(t=1..n)(max(R(t),0)) / 1/n*sum(t=1..n)(max(-R(t),0))}
-where \eqn{n} is the number of observations of the entire
-series
+where \eqn{n} is the number of observations of the entire series
}
\examples{
data(portfolio_bacon)
@@ -37,8 +33,8 @@
Matthieu Lestel
}
\references{
-Carl Bacon, \emph{Practical portfolio performance
-measurement and attribution}, second edition 2008 p.95
+Carl Bacon, \emph{Practical portfolio performance measurement
+and attribution}, second edition 2008 p.95
}
\keyword{distribution}
\keyword{models}
Modified: pkg/PerformanceAnalytics/man/BetaCoMoments.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/BetaCoMoments.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/BetaCoMoments.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{BetaCoMoments}
\alias{BetaCoKurtosis}
\alias{BetaCoMoments}
@@ -12,18 +13,17 @@
BetaCoKurtosis(Ra, Rb)
}
\arguments{
- \item{Ra}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{Ra}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{Rb}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of index, benchmark, or secondary asset
- returns to compare against}
+\item{Rb}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+index, benchmark, or secondary asset returns to compare against}
- \item{test}{condition not implemented yet}
+\item{test}{condition not implemented yet}
}
\description{
-calculate higher co-moment betas, or 'systematic' variance,
-skewness, and kurtosis
+calculate higher co-moment betas, or 'systematic' variance, skewness, and
+kurtosis
}
\examples{
data(managers)
@@ -38,15 +38,13 @@
Kris Boudt, Peter Carl, Brian Peterson
}
\references{
-Boudt, Kris, Brian G. Peterson, and Christophe Croux. 2008.
-Estimation and Decomposition of Downside Risk for
-Portfolios with Non-Normal Returns. Journal of Risk.
-Winter.
+Boudt, Kris, Brian G. Peterson, and Christophe Croux. 2008. Estimation and
+Decomposition of Downside Risk for Portfolios with Non-Normal Returns.
+Journal of Risk. Winter.
-Martellini, Lionel, and Volker Ziemann. 2007. Improved
-Forecasts of Higher-Order Comoments and Implications for
-Portfolio Selection. EDHEC Risk and Asset Management
-Research Centre working paper.
+Martellini, Lionel, and Volker Ziemann. 2007. Improved Forecasts of
+Higher-Order Comoments and Implications for Portfolio Selection. EDHEC Risk
+and Asset Management Research Centre working paper.
}
\seealso{
\code{\link{CoMoments}}
@@ -56,28 +54,24 @@
moments
-The co-moments, including covariance, coskewness, and
-cokurtosis, do not allow the marginal impact of an asset on
-a portfolio to be directly measured. Instead, Martellini
-and Zieman (2007) develop a framework that assesses the
-potential diversification of an asset relative to a
-portfolio. They use higher moment betas to estimate how
-much portfolio risk will be impacted by adding an asset, in
-terms of symmetric risk (i.e., volatility), in asymmetry
-risk (i.e., skewness), and extreme risks (i.e. kurtosis).
-That allows them to show that adding an asset to a
-portfolio (or benchmark) will reduce the portfolio's
-variance to be reduced if the second-order beta of the
-asset with respect to the portfolio is less than one. They
-develop the same concepts for the third and fourth order
-moments. The authors offer these higher moment betas as a
-measure of the diversification potential of an asset.
+The co-moments, including covariance, coskewness, and cokurtosis, do not
+allow the marginal impact of an asset on a portfolio to be directly
+measured. Instead, Martellini and Zieman (2007) develop a framework that
+assesses the potential diversification of an asset relative to a portfolio.
+They use higher moment betas to estimate how much portfolio risk will be
+impacted by adding an asset, in terms of symmetric risk (i.e., volatility),
+in asymmetry risk (i.e., skewness), and extreme risks (i.e. kurtosis). That
+allows them to show that adding an asset to a portfolio (or benchmark) will
+reduce the portfolio's variance to be reduced if the second-order beta of
+the asset with respect to the portfolio is less than one. They develop the
+same concepts for the third and fourth order moments. The authors offer
+these higher moment betas as a measure of the diversification potential of
+an asset.
-Higher moment betas are defined as proportional to the
-derivative of the covariance, coskewness and cokurtosis of
-the second, third and fourth portfolio moment with respect
-to the portfolio weights. The beta co-variance is
-calculated as:
+Higher moment betas are defined as proportional to the derivative of the
+covariance, coskewness and cokurtosis of the second, third and fourth
+portfolio moment with respect to the portfolio weights. The beta co-variance
+is calculated as:
\deqn{ BetaCoV(Ra,Rb) = \beta^{(2)}_{a,b} =
\frac{CoV(R_a,R_b)}{\mu^{(2)}(R_b)} }{BetaCoV(Ra,Rb) =
@@ -85,59 +79,50 @@
Beta co-skewness is given as:
-\deqn{ BetaCoS(Ra,Rb) = \beta^{(3)}_{a,b}=
-\frac{CoS(R_a,R_b)}{\mu^{(3)}(R_b)} }{BetaCoS(Ra,Rb) =
+\deqn{ BetaCoS(Ra,Rb) = \beta^{(3)}_{a,b}= \frac{CoS(R_a,R_b)}{\mu^{(3)}(R_b)} }{BetaCoS(Ra,Rb) =
CoS(Ra,Rb)/centeredmoment(Rb,3)}
Beta co-kurtosis is:
-\deqn{ BetaCoK(Ra,Rb)=\beta^{(4)}_{a,b} =
-\frac{CoK(R_a,R_b)}{\mu^{(4)}(R_b)} }{BetaCoK(Ra,Rb) =
+\deqn{ BetaCoK(Ra,Rb)=\beta^{(4)}_{a,b}
+= \frac{CoK(R_a,R_b)}{\mu^{(4)}(R_b)} }{BetaCoK(Ra,Rb) =
CoK(Ra,Rb)/centeredmoment(Rb,4)}
-where the \eqn{n}-th centered moment is calculated as
+where the \eqn{n}-th centered moment is
+calculated as
-\deqn{ \mu^{(n)}(R) = E\lbrack(R-E(R))^n\rbrack
-}{moment^n(R) = E[R-E(R)^n]}
+\deqn{ \mu^{(n)}(R) = E\lbrack(R-E(R))^n\rbrack }{moment^n(R) = E[R-E(R)^n]}
-A beta is greater than one indicates that no
-diversification benefits should be expected from the
-introduction of that asset into the portfolio. Conversely,
-a beta that is less than one indicates that adding the new
-asset should reduce the resulting portfolio's volatility
-and kurtosis, and to an increase in skewness. More
-specifically, the lower the beta the higher the
-diversification effect on normal risk (i.e. volatility).
-Similarly, since extreme risks are generally characterised
-by negative skewness and positive kurtosis, the lower the
-beta, the higher the diversification effect on extreme
-risks (as reflected in Modified Value-at-Risk or ER).
+A beta is greater than one indicates that no diversification benefits should
+be expected from the introduction of that asset into the portfolio.
+Conversely, a beta that is less than one indicates that adding the new asset
+should reduce the resulting portfolio's volatility and kurtosis, and to an
+increase in skewness. More specifically, the lower the beta the higher the
+diversification effect on normal risk (i.e. volatility). Similarly, since
+extreme risks are generally characterised by negative skewness and positive
+kurtosis, the lower the beta, the higher the diversification effect on
+extreme risks (as reflected in Modified Value-at-Risk or ER).
-The addition of a small fraction of a new asset to a
-portfolio leads to a decrease in the portfolio's second
-moment (respectively, an increase in the portfolio's third
-moment and a decrease in the portfolio's fourth moment) if
-and only if the second moment (respectively, the third
-moment and fourth moment) beta is less than one (see
-Martellini and Ziemann (2007) for more details).
+The addition of a small fraction of a new asset to a portfolio leads to a
+decrease in the portfolio's second moment (respectively, an increase in the
+portfolio's third moment and a decrease in the portfolio's fourth moment) if
+and only if the second moment (respectively, the third moment and fourth
+moment) beta is less than one (see Martellini and Ziemann (2007) for more
+details).
-For skewness, the interpretation is slightly more involved.
-If the skewness of the portfolio is negative, we would
-expect an increase in portfolio skewness when the third
-moment beta is lower than one. When the skewness of the
-portfolio is positive, then the condition is that the third
-moment beta is greater than, as opposed to lower than, one.
+For skewness, the interpretation is slightly more involved. If the skewness
+of the portfolio is negative, we would expect an increase in portfolio
+skewness when the third moment beta is lower than one. When the skewness of
+the portfolio is positive, then the condition is that the third moment beta
+is greater than, as opposed to lower than, one.
-%Because the interpretation of beta coskewness is made
-difficult by the need to condition on it's skewness, we
-deviate from the more widely used measure slightly. To
-make the interpretation consistent across all three
-measures, the beta coskewness function tests the skewness
-and multiplies the result by the sign of the skewness.
-That allows an analyst to review the metric and interpret
-it without needing additional information. To use the more
-widely used metric, simply set the parameter \code{test =
-FALSE}.
+%Because the interpretation of beta coskewness is made difficult by the need
+to condition on it's skewness, we deviate from the more widely used measure
+slightly. To make the interpretation consistent across all three measures,
+the beta coskewness function tests the skewness and multiplies the result by
+the sign of the skewness. That allows an analyst to review the metric and
+interpret it without needing additional information. To use the more widely
+used metric, simply set the parameter \code{test = FALSE}.
}
\keyword{distribution}
\keyword{models}
Modified: pkg/PerformanceAnalytics/man/BurkeRatio.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/BurkeRatio.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/BurkeRatio.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{BurkeRatio}
\alias{BurkeRatio}
\title{Burke ratio of the return distribution}
@@ -5,36 +6,27 @@
BurkeRatio(R, Rf = 0, modified = FALSE, ...)
}
\arguments{
- \item{R}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{R}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{Rf}{the risk free rate}
+\item{Rf}{the risk free rate}
- \item{modified}{a boolean to decide which ratio to
- calculate between Burke ratio and modified Burke ratio.}
+\item{modified}{a boolean to decide which ratio to calculate between Burke ratio and modified Burke ratio.}
- \item{\dots}{any other passthru parameters}
+\item{\dots}{any other passthru parameters}
}
\description{
-To calculate Burke ratio we take the difference between the
-portfolio return and the risk free rate and we divide it by
-the square root of the sum of the square of the drawdowns.
-To calculate the modified Burke ratio we just multiply the
-Burke ratio by the square root of the number of datas.
+To calculate Burke ratio we take the difference between the portfolio
+return and the risk free rate and we divide it by the square root of the
+sum of the square of the drawdowns. To calculate the modified Burke ratio
+we just multiply the Burke ratio by the square root of the number of datas.
}
\details{
-\deqn{Burke Ratio = \frac{r_P -
-r_F}{\sqrt{\sum^{d}_{t=1}{D_t}^2}}}{Burke Ratio = (Rp - Rf)
-/ (sqrt(sum(t=1..n)(Dt^2)))}
+\deqn{Burke Ratio = \frac{r_P - r_F}{\sqrt{\sum^{d}_{t=1}{D_t}^2}}}{Burke Ratio = (Rp - Rf) / (sqrt(sum(t=1..n)(Dt^2)))}
-\deqn{Modified Burke Ratio = \frac{r_P -
-r_F}{\sqrt{\sum^{d}_{t=1}\frac{{D_t}^2}{n}}}}{Modified
-Burke Ratio = (Rp - Rf) / (sqrt(sum(t=1..n)(Dt^2 / n)))}
+\deqn{Modified Burke Ratio = \frac{r_P - r_F}{\sqrt{\sum^{d}_{t=1}\frac{{D_t}^2}{n}}}}{Modified Burke Ratio = (Rp - Rf) / (sqrt(sum(t=1..n)(Dt^2 / n)))}
-where \eqn{n} is the number of observations of the entire
-series, \eqn{d} is number of drawdowns, \eqn{r_P} is the
-portfolio return, \eqn{r_F} is the risk free rate and
-\eqn{D_t} the \eqn{t^{th}} drawdown.
+where \eqn{n} is the number of observations of the entire series, \eqn{d} is number of drawdowns, \eqn{r_P} is the portfolio return, \eqn{r_F} is the risk free rate and \eqn{D_t} the \eqn{t^{th}} drawdown.
}
\examples{
data(portfolio_bacon)
@@ -51,8 +43,8 @@
Matthieu Lestel
}
\references{
-Carl Bacon, \emph{Practical portfolio performance
-measurement and attribution}, second edition 2008 p.90-91
+Carl Bacon, \emph{Practical portfolio performance measurement
+and attribution}, second edition 2008 p.90-91
}
\keyword{distribution}
\keyword{models}
Modified: pkg/PerformanceAnalytics/man/CAPM.RiskPremium.Rd
===================================================================
--- pkg/PerformanceAnalytics/man/CAPM.RiskPremium.Rd 2014-09-02 18:54:45 UTC (rev 3521)
+++ pkg/PerformanceAnalytics/man/CAPM.RiskPremium.Rd 2014-09-02 21:09:55 UTC (rev 3522)
@@ -1,3 +1,4 @@
+% Generated by roxygen2 (4.0.1): do not edit by hand
\name{CAPM.CML.slope}
\alias{CAPM.CML}
\alias{CAPM.CML.slope}
@@ -20,77 +21,69 @@
CAPM.SML.slope(Rb, Rf = 0)
}
\arguments{
- \item{Ra}{an xts, vector, matrix, data frame, timeSeries
- or zoo object of asset returns}
+\item{Ra}{an xts, vector, matrix, data frame, timeSeries or zoo object of
+asset returns}
- \item{Rb}{return vector of the benchmark asset}
+\item{Rb}{return vector of the benchmark asset}
- \item{Rf}{risk free rate, in same period as your returns}
+\item{Rf}{risk free rate, in same period as your returns}
}
\description{
The Capital Asset Pricing Model, from which the popular
-\code{\link{SharpeRatio}} is derived, is a theory of market
-equilibrium. These utility functions provide values for
-various measures proposed in the CAPM.
+\code{\link{SharpeRatio}} is derived, is a theory of market equilibrium.
+These utility functions provide values for various measures proposed in the
+CAPM.
}
\details{
-At it's core, the CAPM is a single factor linear model. In
-light of the general ustility and wide use of single factor
-model, all functions in the CAPM suite will also be
-available with SFM (single factor model) prefixes.
+At it's core, the CAPM is a single factor linear model. In light of
+the general ustility and wide use of single factor model, all
+functions in the CAPM suite will also be available with SFM (single factor model)
+prefixes.
-The CAPM provides a justification for passive or index
-investing by positing that assets that are not on the
-efficient frontier will either rise or lower in price until
-they are on the efficient frontier of the market portfolio.
+The CAPM provides a justification for passive or index investing by positing
+that assets that are not on the efficient frontier will either rise or lower
+in price until they are on the efficient frontier of the market portfolio.
-The CAPM Risk Premium on an investment is the measure of
-how much the asset's performance differs from the risk free
-rate. Negative Risk Premium generally indicates that the
-investment is a bad investment, and the money should be
-allocated to the risk free asset or to a different asset
-with a higher risk premium.
+The CAPM Risk Premium on an investment is the measure of how much the
+asset's performance differs from the risk free rate. Negative Risk Premium
+generally indicates that the investment is a bad investment, and the money
+should be allocated to the risk free asset or to a different asset with a
+higher risk premium.
-The Capital Market Line relates the excess expected return
-on an efficient market portfolio to it's Risk. The slope
-of the CML is the Sharpe Ratio for the market portfolio.
-The Security Market line is constructed by calculating the
-line of Risk Premium over \code{\link{CAPM.beta}}. For the
-benchmark asset this will be 1 over the risk premium of the
-benchmark asset. The CML also describes the only path
-allowed by the CAPM to a portfolio that outperforms the
-efficient frontier: it describes the line of reward/risk
-that a leveraged portfolio will occupy. So, according to
-CAPM, no portfolio constructed of the same assets can lie
-above the CML.
+The Capital Market Line relates the excess expected return on an efficient
+market portfolio to it's Risk. The slope of the CML is the Sharpe Ratio for
+the market portfolio. The Security Market line is constructed by calculating
+the line of Risk Premium over \code{\link{CAPM.beta}}. For the benchmark
+asset this will be 1 over the risk premium of the benchmark asset. The CML
+also describes the only path allowed by the CAPM to a portfolio that
+outperforms the efficient frontier: it describes the line of reward/risk
+that a leveraged portfolio will occupy. So, according to CAPM, no portfolio
+constructed of the same assets can lie above the CML.
-Probably the most complete criticism of CAPM in actual
-practice (as opposed to structural or theory critiques) is
-that it posits a market equilibrium, but is most often used
-only in a partial equilibrium setting, for example by using
-the S\&P 500 as the benchmark asset. A better method of
-using and testing the CAPM would be to use a general
-equilibrium model that took global assets from all asset
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/returnanalytics -r 3522
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