[Returnanalytics-commits] r3254 - in pkg/PerformanceAnalytics: . sandbox/Shubhankit/noniid.sm/man

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

Author: peter_carl
Date: 2013-11-14 20:02:32 +0100 (Thu, 14 Nov 2013)
New Revision: 3254

Added:
   pkg/PerformanceAnalytics/sandbox/Shubhankit/noniid.sm/man/AcarSim.Rd
Modified:
   pkg/PerformanceAnalytics/NAMESPACE
Log:
- added Modigliani function

Modified: pkg/PerformanceAnalytics/NAMESPACE
===================================================================
--- pkg/PerformanceAnalytics/NAMESPACE	2013-11-14 19:01:26 UTC (rev 3253)
+++ pkg/PerformanceAnalytics/NAMESPACE	2013-11-14 19:02:32 UTC (rev 3254)
@@ -68,6 +68,7 @@
     mean.LCL,
     mean.stderr,
     mean.UCL,
+    Modigliani,
     MSquared,
     MSquaredExcess,
     NetSelectivity,

Copied: pkg/PerformanceAnalytics/sandbox/Shubhankit/noniid.sm/man/AcarSim.Rd (from rev 3012, pkg/PerformanceAnalytics/sandbox/Shubhankit/noniid.sm/man/AcarSim.Rd)
===================================================================
--- pkg/PerformanceAnalytics/sandbox/Shubhankit/noniid.sm/man/AcarSim.Rd	                        (rev 0)
+++ pkg/PerformanceAnalytics/sandbox/Shubhankit/noniid.sm/man/AcarSim.Rd	2013-11-14 19:02:32 UTC (rev 3254)
@@ -0,0 +1,52 @@
+\name{AcarSim}
+\alias{AcarSim}
+\title{Acar-Shane Maximum Loss Plot}
+\usage{
+  AcarSim(R, nsim = 1)
+}
+\arguments{
+  \item{R}{an xts, vector, matrix, data frame, timeSeries
+  or zoo object of asset returns}
+
+  \item{nsim}{number of simulations input}
+}
+\description{
+  To get some insight on the relationships between maximum
+  drawdown per unit of volatility and mean return divided
+  by volatility, we have proceeded to Monte-Carlo
+  simulations. We have simulated cash flows over a period
+  of 36 monthly returns and measured maximum drawdown for
+  varied levels of annualised return divided by volatility
+  varying from minus \emph{two to two} by step of
+  \emph{0.1} . The process has been repeated \bold{six
+  thousand times}.
+}
+\details{
+  Unfortunately, there is no \bold{analytical formulae} to
+  establish the maximum drawdown properties under the
+  random walk assumption. We should note first that due to
+  its definition, the maximum drawdown divided by
+  volatility can be interpreted as the only function of the
+  ratio mean divided by volatility. \deqn{MD/[\sigma]= Min
+  (\sum[X(j)])/\sigma = F(\mu/\sigma)} Where j varies from
+  1 to n ,which is the number of drawdown's in simulation
+}
+\examples{
+library(PerformanceAnalytics)
+#AcarSim(R)
+}
+\author{
+  Shubhankit Mohan
+}
+\references{
+  Maximum Loss and Maximum Drawdown in Financial
+  Markets,\emph{International Conference Sponsored by BNP
+  and Imperial College on: Forecasting Financial Markets,
+  London, United Kingdom, May 1997}
+  \url{http://www.intelligenthedgefundinvesting.com/pubs/easj.pdf}
+}
+\keyword{Drawdown}
+\keyword{Loss}
+\keyword{Maximum}
+\keyword{Simulated}
+