\HeaderA{table.Autocorrelation}{table for calculating the first six autocorrelation coefficients and significance}{table.Autocorrelation}
\keyword{ts}{table.Autocorrelation}
\keyword{multivariate}{table.Autocorrelation}
\keyword{distribution}{table.Autocorrelation}
\keyword{models}{table.Autocorrelation}
\begin{Description}\relax
Produces data table of autocorrelation coefficients \eqn{\rho}{} and corresponding Q(6)-statistic for each column in R.
\end{Description}
\begin{Usage}
\begin{verbatim}
table.Autocorrelation(R, digits = 4)
\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{digits}] number of digits to round results to for display 
\end{ldescription}
\end{Arguments}
\begin{Value}
data.frame with columns for the first six auto-correlation coefficients and the Q(6) test.
\end{Value}
\begin{Note}\relax
To test returns for autocorrelation, Lo (2001) suggests the use of the Ljung-Box test, a significance test for the auto-correlation coefficients.  Ljung and Box (1978) provide a refinement of the Q-statistic proposed by Box and Pierce (1970) that offers a better fit for the \eqn{\chi^2}{} test for small sample sizes. \code{\LinkA{Box.test}{Box.test}} provides both.
\end{Note}
\begin{Author}\relax
Peter Carl
\end{Author}
\begin{References}\relax
Lo, Andrew W. 2001. Risk Management for Hedge Funds: Introduction and Overview. SSRN
eLibrary.
\end{References}
\begin{SeeAlso}\relax
\code{\LinkA{Box.test}{Box.test}}, \code{\LinkA{acf}{acf}}
\end{SeeAlso}
\begin{Examples}
\begin{ExampleCode}
data(managers)
t(table.Autocorrelation(managers))

\end{ExampleCode}
\end{Examples}

