<html><head><meta name="color-scheme" content="light dark"></head><body><pre style="word-wrap: break-word; white-space: pre-wrap;">\HeaderA{Return.clean}{clean returns in a time series to to provide more robust risk estimates}{Return.clean}
\keyword{ts}{Return.clean}
\keyword{multivariate}{Return.clean}
\keyword{distribution}{Return.clean}
\keyword{models}{Return.clean}
\begin{Description}\relax
A function that provides access to multiple methods for cleaning outliers from return data.
\end{Description}
\begin{Usage}
\begin{verbatim}
Return.clean(R, method = c("none", "boudt", "geltner"), alpha = .01, ...)
\end{verbatim}
\end{Usage}
\begin{Arguments}
\begin{ldescription}
\item[\code{R}] an xts, vector, matrix, data frame, timeSeries or zoo object of asset returns 
\item[\code{method}] one of "none", "boudt", which applies the function \code{\LinkA{clean.boudt}{clean.boudt}} or "geltner" which applies the function \code{\LinkA{Return.Geltner}{Return.Geltner}}to R 
\item[\code{alpha}] the percentage of outliers you want to clean 
\item[\code{...}] additional parameters passed into the underlying cleaning function 
\end{ldescription}
\end{Arguments}
\begin{Details}\relax
This is a wrapper for offering multiple data cleaning methods for data objects containing returns.

The primary value of data cleaning lies in creating a more
robust and stable estimation of the distribution generating the
large majority of the return data. The increased robustness and
stability of the estimated moments using cleaned data should be
used for portfolio construction. If an investor wishes to
have a more conservative risk estimate, cleaning may not be
indicated for risk monitoring. 

In actual practice, it is probably best to back-test the results of
both cleaned and uncleaned series to see what works best when forecasting risk with the
particular combination of assets under consideration.

In this version, only one method is supported.  See \code{\LinkA{clean.boudt}{clean.boudt}} for more details.
\end{Details}
\begin{Value}
xts object with the same dimensions as R, containing data cleaned with the method selected.
\end{Value}
\begin{Author}\relax
Peter Carl
\end{Author}
\begin{SeeAlso}\relax
\code{\LinkA{clean.boudt}{clean.boudt}} \\
\code{\LinkA{Return.Geltner}{Return.Geltner}} \\
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(managers)
head(Return.clean(managers[,1:4]),n=20)
chart.BarVaR(managers[,1,drop=FALSE], show.clean=TRUE, clean="boudt", lwd=2, methods="ModifiedVaR")
\end{ExampleCode}
\end{Examples}

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