% Generated by roxygen2: do not edit by hand
% Please edit documentation in R/methods.R
\name{exposureHeterogeneity}
\alias{exposureHeterogeneity}
\title{Factor exposure heterogeneity from a beta screening}
\usage{
exposureHeterogeneity(object)
}
\arguments{
\item{object}{A \code{SCREENING} object produced with
\code{screen_beta = TRUE}.}
}
\value{
A \code{data.frame} of class \code{exposureHeterogeneity} with columns
\code{coefficient}, \code{equalExposure} (\eqn{\pi^0_k}), and
\code{heterogeneity} (\eqn{1-\pi^0_k}).
}
\description{
Aggregates the per-fund equal-performance ratios of a
\code{screen_beta = TRUE} \code{\link{alphaScreening}} into the
factor-by-factor heterogeneity measure of Ardia et al. (2023). For each
coefficient \eqn{k} (the alpha and each factor beta) it reports the average
equal-exposure ratio \eqn{\pi^0_k = \frac1N\sum_i \pi^0_{i,k}} and the
heterogeneity \eqn{1-\pi^0_k}: the share of peers that are significantly
differentiated on coefficient \eqn{k}. A value close to one indicates large
heterogeneity (much room to differentiate); close to zero, homogeneity.
}
\examples{
\donttest{
data("hfdata")
set.seed(1234)
fac <- matrix(rnorm(nrow(hfdata) * 2), ncol = 2,
              dimnames = list(NULL, c("MKT", "SMB")))
sc <- alphaScreening(hfdata[, 1:20], factors = fac, screen_beta = TRUE,
                     control = list(nCore = 1))
exposureHeterogeneity(sc)
}
}
\references{
Ardia, D., Bluteau, K., Lortie-Cloutier, G., Tran, D. (2023).
Factor exposure heterogeneity in green and brown stocks.
\emph{Finance Research Letters} \bold{55}, Part A, 103900.
}
\seealso{
\code{\link{alphaScreening}}.
}
\author{
David Ardia and Kris Boudt.
}
\keyword{htest}
