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#' @name RiskPortfolios
#' @docType package
#' @title RiskPortfolios: Computation of risk-based portfolios in R
#' @description \code{RiskPortfolios} (Ardia et al., 2017) is an \R package for constructing risk-based portfolios dedicated to
#' portfolio managers and quantitative analysts. It provides a set of
#' functionalities to build mean-variance, minimum variance, inverse-volatility weighted (Leote et al., 2012),
#' equal-risk-contribution (Maillard et al. 2010), maximum diversification (Choueifaty and Coignard, 2008), and
#' risk-efficient (Amenc et al., 2011) portfolios. Optimization is achieved with the \R
#' functions \code{\link[quadprog]{solve.QP}} and \code{\link[nloptr]{slsqp}}. Long or gross constraints can be added to the optimizer.
#' As risk-based portfolios are mainly based on covariances, the package also provides a large set of
#' covariance matrix estimators. A simulation study relying on the package is described in Ardia et al. (2017).
#'
#' @section Functions:
#' \itemize{
#' \item \code{\link{optimalPortfolio}}: Optimization of portfolios.
#' \item \code{\link{meanEstimation}}: Computation of expected returns.
#' \item \code{\link{covEstimation}}: Computation of covariance matrix.
#' \item \code{\link{semidevEstimation}}: Computation of semi-deviation.
#' }
#'
#' @section Update:
#' The latest version of the package is available at \url{https://github.com/ArdiaD/RiskPortfolios}.
#' @author David Ardia, Kris Boudt and Jean-Philippe Gagnon-Fleury.
#' @note By using \code{RiskPortfolios} you agree to the following rules: (1) You must cite Ardia et al. (2017) in
#' working papers and published papers that use \code{RiskPortfolios} (use \code{citation("RiskPortfolios")}), (2) you
#' must place the URL \url{https://CRAN.R-project.org/package=RiskPortfolios} in a footnote to help
#' others find \code{RiskPortfolios}, and (3) you assume all risk for the use of \code{RiskPortfolios}.
#' @references
#' Amenc, N., Goltz, F., Martellini, L., Retowsky, P. (2011).
#' Efficient indexation: An alternative to cap-weighted indices.
#' \emph{Journal of Investment Management} \bold{9}(4), pp.1-23.
#'
#' Ardia, D., Boudt, K. (2015).
#' Implied expected returns and the choice of a mean-variance efficient portfolio proxy.
#' \emph{Journal of Portfolio Management} \bold{41}(4), pp.66-81.
#' \doi{10.3905/jpm.2015.41.4.068}
#'
#' Ardia, D., Bolliger, G., Boudt, K., Gagnon-Fleury, J.-P. (2017).
#' The Impact of covariance misspecification in risk-based portfolios.
#' \emph{Annals of Operations Research} \bold{254}(1-2), pp.1-16.
#' \doi{10.1007/s10479-017-2474-7}
#'
#' Ardia, D., Boudt, K., Gagnon-Fleury, J.-P. (2017).
#' RiskPortfolios: Computation of risk-based portfolios in R.
#' \emph{Journal of Open Source Software} \bold{10}(2).
#' \doi{10.21105/joss.00171}
#'
#' Choueifaty, Y., Coignard, Y. (2008).
#' Toward maximum diversification.
#' \emph{Journal of Portfolio Management} \bold{35}(1), pp.40-51.
#'
#' Choueifaty, Y., Froidure, T., Reynier, J. (2013).
#' Properties of the most diversified portfolio.
#' \emph{Journal of Investment Strategies} \bold{2}(2), pp.49-70.
#'
#' Das, S., Markowitz, H., Scheid, J., Statman, M. (2010).
#' Portfolio optimization with mental accounts.
#' \emph{Journal of Financial and Quantitative Analysis} \bold{45}(2), pp.311-334.
#'
#' DeMiguel, V., Garlappi, L., Uppal, R. (2009).
#' Optimal versus naive diversification: How inefficient is the 1/n portfolio strategy.
#' \emph{Review of Financial Studies} \bold{22}(5), pp.1915-1953.
#'
#' Fan, J., Zhang, J., Yu, K. (2012).
#' Vast portfolio selection with gross-exposure constraints.
#' \emph{Journal of the American Statistical Association} \bold{107}(498), pp.592-606.
#'
#' Maillard, S., Roncalli, T., Teiletche, J. (2010).
#' The properties of equally weighted risk contribution portfolios.
#' \emph{Journal of Portfolio Management} \bold{36}(4), pp.60-70.
#'
#' Martellini, L. (2008).
#' Towards the design of better equity benchmarks.
#' \emph{Journal of Portfolio Management} \bold{34}(4), Summer,pp.34-41.
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