% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/ac_ranking.R
\name{ac.ranking}
\alias{ac.ranking}
\title{Asset Ranking}
\usage{
ac.ranking(R, order, ...)
}
\arguments{
\item{R}{xts object of asset returns}
\item{order}{a vector of indexes of the relative ranking of expected asset
returns in ascending order. For example, \code{order = c(2, 3, 1, 4)} means
that the expected returns of \code{R[,2] < R[,3], < R[,1] < R[,4]}.}
\item{\dots}{any other passthrough parameters}
}
\value{
The estimated first moments based on ranking views
}
\description{
Compute the first moment from a single complete sort
}
\details{
This function computes the estimated centroid vector from a single complete
sort using the analytical approximation as described in R. Almgren and
N. Chriss, "Portfolios from Sorts". The centroid is estimated and then
scaled such that it is on a scale similar to the asset returns. By default,
the centroid vector is scaled according to the median of the asset mean
returns.
}
\examples{
data(edhec)
R <- edhec[,1:4]
ac.ranking(R, c(2, 3, 1, 4))
}
\references{
R. Almgren and N. Chriss, "Portfolios from Sorts"
\url{https://papers.ssrn.com/sol3/papers.cfm?abstract_id=720041}
}
\seealso{
\code{\link{centroid.complete.mc}} \code{\link{centroid.sectors}}
\code{\link{centroid.sign}} \code{\link{centroid.buckets}}
}
