[Introcompfinr-commits] r12 - in pkg/IntroCompFinR: R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Fri Feb 20 07:59:09 CET 2015
Author: bethanyyollin
Date: 2015-02-20 07:59:09 +0100 (Fri, 20 Feb 2015)
New Revision: 12
Modified:
pkg/IntroCompFinR/R/efficient.frontier.R
pkg/IntroCompFinR/R/efficient.portfolio.R
pkg/IntroCompFinR/R/getPortfolio.R
pkg/IntroCompFinR/R/globalMin.portfolio.R
pkg/IntroCompFinR/R/plot.Markowitz.R
pkg/IntroCompFinR/R/plot.portfolio.R
pkg/IntroCompFinR/R/print.Markowitz.R
pkg/IntroCompFinR/R/print.portfolio.R
pkg/IntroCompFinR/R/summary.Markowitz.R
pkg/IntroCompFinR/R/summary.portfolio.R
pkg/IntroCompFinR/R/tangency.portfolio.R
pkg/IntroCompFinR/man/efficient.frontier.Rd
pkg/IntroCompFinR/man/efficient.portfolio.Rd
pkg/IntroCompFinR/man/getPortfolio.Rd
pkg/IntroCompFinR/man/globalMin.portfolio.Rd
pkg/IntroCompFinR/man/plot.Markowitz.Rd
pkg/IntroCompFinR/man/plot.portfolio.Rd
pkg/IntroCompFinR/man/print.Markowitz.Rd
pkg/IntroCompFinR/man/print.portfolio.Rd
pkg/IntroCompFinR/man/summary.Markowitz.Rd
pkg/IntroCompFinR/man/summary.portfolio.Rd
pkg/IntroCompFinR/man/tangency.portfolio.Rd
Log:
Misc. improvements to documentation.
Modified: pkg/IntroCompFinR/R/efficient.frontier.R
===================================================================
--- pkg/IntroCompFinR/R/efficient.frontier.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/efficient.frontier.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,31 +3,30 @@
#' @author Eric Zivot
#'
#' @description
-#' The function constructs the set of mean-variance efficient portfolios that either allow all assets to be
-#' sold short or not allow any asset to be sold short. The returned object is of class \samp{Markowitz} for
-#' which there are \code{print}, \code{summary} and \code{plot} methods.
+#' The function constructs the set of mean-variance efficient portfolios that either allow all
+#' assets to be sold short or not allow any asset to be sold short. The returned object is of class
+#' \samp{Markowitz} for which there are \samp{print}, \samp{summary} and \samp{plot} methods.
#'
#' @details
-#' If short sales are allowed (negative weights) then the set of efficient portfolios of risky assets
-#' can be computed as a convex combination of
-#' any two efficient portfolios. It is convenient to use the global minimum variance portfolio as
-#' one portfolio and an efficient portfolio with target expected return equal to the maximum
-#' expected return of the assets under consideration as the other portfolio. Call these portfolios
-#' \eqn{m} and \eqn{x}, respectively. Then for any number \samp{alpha}, another efficient
-#' portfolio can be computed as \eqn{z=\alpha m+(1-\alpha)x}. If short sales are not allowed, then the set
-#' of efficient portfolios is computed by repeated calls to the function \code{efficient.portfolio()},
-#' with \code{shorts=FALSE}, for a
-#' grid of target expected returns starting at the expected return of the global minimum variance portfolio
-#' (not allowing short sales) and ending at the expected return equal to the maximum expected return of
+#' If short sales are allowed (negative weights) then the set of efficient portfolios of risky
+#' assets can be computed as a convex combination of any two efficient portfolios. It is convenient
+#' to use the global minimum variance portfolio as one portfolio and an efficient portfolio with
+#' target expected return equal to the maximum expected return of the assets under consideration as
+#' the other portfolio. Call these portfolios \eqn{m} and \eqn{x}, respectively. Then for any number
+#' \samp{alpha}, another efficient portfolio can be computed as \eqn{z=\alpha m+(1-\alpha)x}. If
+#' short sales are not allowed, then the set of efficient portfolios is computed by repeated calls
+#' to the function \samp{efficient.portfolio()}, with \samp{shorts=FALSE}, for a grid of target
+#' expected returns starting at the expected return of the global minimum variance portfolio (not
+#' allowing short sales) and ending at the expected return equal to the maximum expected return of
#' the assets under consideration.
#'
#' @param er \samp{N x 1} vector of expected returns
#' @param cov.mat \samp{N x N} return covariance matrix
#' @param nport scalar, number of efficient portfolios to compute
-#' @param alpha.min minimum value of \samp{alpha}, default is \code{-.5}
-#' @param alpha.max maximum value of \samp{alpha}, default is \code{1.5}
-#' @param shorts logical, if \code{TRUE} then short sales (negative portfolio weights)
-#' are allowed. If \code{FALSE} then no asset is allowed to be sold short
+#' @param alpha.min minimum value of \samp{alpha}, default is \samp{-.5}
+#' @param alpha.max maximum value of \samp{alpha}, default is \samp{1.5}
+#' @param shorts logical, if \samp{TRUE} then short sales (negative portfolio weights)
+#' are allowed. If \samp{FALSE} then no asset is allowed to be sold short
#'
#' @return
#' \item{call}{captures function call}
Modified: pkg/IntroCompFinR/R/efficient.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/efficient.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/efficient.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,23 +3,22 @@
#' @author Eric Zivot
#'
#' @description
-#' Compute minimum variance portfolio subject to target return either allowing all assets
-#' to be sold short or not allowing any asset to be sold short. The returned object is
-#' of class \samp{portfolio}.
+#' Compute minimum variance portfolio subject to target return either allowing all assets to be sold
+#' short or not allowing any asset to be sold short. The returned object is of class
+#' \samp{portfolio}.
#'
#' @details
-#' A mean-variance efficient portfolio \eqn{x} allowing short sales (negative weights)
-#' that achieves the target expected return \eqn{\mu_0}
-#' solves the optimization problem: min \eqn{t(x)\Sigma x} s.t. \eqn{t(x)1=1} and
-#' \eqn{t(x)\mu=\mu_0}, for which there is an analytic solution using matrix algebra.
-#' If short sales are not allowed then the portfolio is computed numerically using the
-#' function \code{solve.QP()} from the \samp{quadprog} package.
+#' A mean-variance efficient portfolio \eqn{x} allowing short sales (negative weights) that achieves
+#' the target expected return \eqn{\mu_0} solves the optimization problem: min \eqn{t(x)\Sigma x}
+#' s.t. \eqn{t(x)1=1} and \eqn{t(x)\mu=\mu_0}, for which there is an analytic solution using matrix
+#' algebra. If short sales are not allowed then the portfolio is computed numerically using the
+#' function \samp{solve.QP()} from the \samp{quadprog} package.
#'
#' @param er \samp{N x 1} vector of expected returns
#' @param cov.mat \samp{N x N} return covariance matrix
#' @param target.return scalar, target expected return
-#' @param shorts logical, if \code{TRUE} then short sales (negative portfolio weights)
-#' are allowed. If \code{FALSE} then no asset is allowed to be sold short.
+#' @param shorts logical, if \samp{TRUE} then short sales (negative portfolio weights)
+#' are allowed. If \samp{FALSE} then no asset is allowed to be sold short.
#'
#' @return
#' \item{call}{captures function call}
Modified: pkg/IntroCompFinR/R/getPortfolio.R
===================================================================
--- pkg/IntroCompFinR/R/getPortfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/getPortfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -6,11 +6,11 @@
#' Create a portfolio object from expected return vector, covariance matrix, and weight vector.
#'
#' @details
-#' To specify a portfolio, an expected return vector and covariance matrix for the assets under
-#' consideration as well as a vector of portfolio weights are needed. The result of \code{getPortfolio}
-#' is a \samp{portfolio} object, which is list with components for the portfolio expected return,
-#' portfolio standard deviation, and portfolio weights. There are \code{print}, \code{summary} and \code{plot}
-#' methods.
+#' To specify a portfolio, an expected return vector and covariance matrix for the assets under
+#' consideration as well as a vector of portfolio weights are needed. The result of
+#' \samp{getPortfolio} is a \samp{portfolio} object, which is list with components for the portfolio
+#' expected return, portfolio standard deviation, and portfolio weights. There are \samp{print},
+#' \samp{summary} and \samp{plot} methods.
#'
#' @param er \samp{N x 1} vector of expected returns
#' @param cov.mat \samp{N x N} return covariance matrix
Modified: pkg/IntroCompFinR/R/globalMin.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/globalMin.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/globalMin.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,21 +3,20 @@
#' @author Eric Zivot
#'
#' @description
-#' Compute global minimum variance portfolio given expected return vector and
-#' covariance matrix. The portfolio can allow all assets to be shorted
-#' or not allow any assets to be shorted. The returned object is of class \samp{portfolio}.
+#' Compute global minimum variance portfolio given expected return vector and covariance matrix. The
+#' portfolio can allow all assets to be shorted or not allow any assets to be shorted. The returned
+#' object is of class \samp{portfolio}.
#'
#' @details
#' The global minimum variance portfolio \eqn{m} allowing for short sales solves the optimization
-#' problem: min \eqn{t(m)\Sigma m} s.t. \eqn{t(m)1=1} for which there is an analytic solution
-#' using matrix algebra. If short sales are not allowed
-#' then the portfolio is computed numerically using the function \code{solve.QP()}
-#' from the \samp{quadprog} package.
+#' problem: min \eqn{t(m)\Sigma m} s.t. \eqn{t(m)1=1} for which there is an analytic solution using
+#' matrix algebra. If short sales are not allowed then the portfolio is computed numerically using
+#' the function \samp{solve.QP()} from the \samp{quadprog} package.
#'
#' @param er \samp{N x 1} vector of expected returns
#' @param cov.mat \samp{N x N} return covariance matrix
-#' @param shorts logical, if \code{TRUE} then short sales (negative portfolio weights)
-#' are allowed. If \code{FALSE} then no asset is allowed to be sold short.
+#' @param shorts logical, if \samp{TRUE} then short sales (negative portfolio weights)
+#' are allowed. If \samp{FALSE} then no asset is allowed to be sold short.
#'
#' @return
#' \item{call}{captures function call}
Modified: pkg/IntroCompFinR/R/plot.Markowitz.R
===================================================================
--- pkg/IntroCompFinR/R/plot.Markowitz.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/plot.Markowitz.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,13 +3,13 @@
#' @author Eric Zivot
#'
#' @description
-#' Plot efficient frontier. The efficient frontier is a plot of portfolio expected return vs. portfolio
-#' standard deviation for a collection of mean-variance efficient portfolios - portfolios that minimize vriance
-#' subject to a target expected return.
+#' Plot efficient frontier. The efficient frontier is a plot of portfolio expected return vs.
+#' portfolio standard deviation for a collection of mean-variance efficient portfolios - portfolios
+#' that minimize variance subject to a target expected return.
#'
#' @param object object of class Markowitz
-#' @param plot.assets if \code{TRUE} then plot asset \code{sd} and \code{er} with asset name labels
-#' @param ... additional arguments passed to \code{plot()}
+#' @param plot.assets if \samp{TRUE} then plot asset \samp{sd} and \samp{er} with asset name labels
+#' @param ... additional arguments passed to \samp{plot()}
#'
#' @examples
#' # construct the data
Modified: pkg/IntroCompFinR/R/plot.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/plot.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/plot.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,10 +3,10 @@
#' @author Eric Zivot
#'
#' @description
-#' The \code{plot()} method shows a bar chart of the portfolio weights.
+#' The \samp{plot()} method shows a bar chart of the portfolio weights.
#'
#' @param object object of class portfolio
-#' @param ... additional arguments passed to \code{barplot()}
+#' @param ... additional arguments passed to \samp{barplot()}
#'
#' @examples
#' # construct the data
Modified: pkg/IntroCompFinR/R/print.Markowitz.R
===================================================================
--- pkg/IntroCompFinR/R/print.Markowitz.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/print.Markowitz.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -6,7 +6,7 @@
#' Print method for \samp{Markowitz} objects.
#'
#' @param object object of class Markowitz
-#' @param ... additional arguments passed to \code{print()}
+#' @param ... additional arguments passed to \samp{print()}
#'
#' @examples
#' # construct the data
Modified: pkg/IntroCompFinR/R/print.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/print.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/print.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -6,7 +6,7 @@
#' Print method for objects of class \samp{portfolio}.
#'
#' @param object object of class portfolio
-#' @param ... additional arguments passed to \code{print()}
+#' @param ... additional arguments passed to \samp{print()}
#'
#' @examples
#' # construct the data
Modified: pkg/IntroCompFinR/R/summary.Markowitz.R
===================================================================
--- pkg/IntroCompFinR/R/summary.Markowitz.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/summary.Markowitz.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,10 +3,10 @@
#' @author Eric Zivot
#'
#' @description
-#' Summary method for objects of class \samp{Markowitz}. For all portfolios on the efficient frontier,
-#' the expected return, standard deviation and asset weights are shown. If \code{risk.free} is given then
-#' efficient portfolios that are combinations of the risk free asset and the tangency portfolio are computed. The
-#' class \code{summary.Markozitz} will be created.
+#' Summary method for objects of class \samp{Markowitz}. For all portfolios on the efficient
+#' frontier, the expected return, standard deviation and asset weights are shown. If
+#' \samp{risk.free} is given then efficient portfolios that are combinations of the risk free asset
+#' and the tangency portfolio are computed. The class \samp{summary.Markozitz} will be created.
#'
#' @param object object of class Markowitz
#' @param risk.free numeric, risk free rate
Modified: pkg/IntroCompFinR/R/summary.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/summary.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/summary.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,13 +3,12 @@
#' @author Eric Zivot
#'
#' @description
-#' Summary method for objects of class \samp{portfolio}. The output is the same
-#' as the \code{print}. If \code{risk.free} is specified then the portfolio Sharpe
-#' ratio is also returned.
+#' Summary method for objects of class \samp{portfolio}. The output is the same as the \samp{print}.
+#' If \samp{risk.free} is specified then the portfolio Sharpe ratio is also returned.
#'
#' @param object object of class portfolio
#' @param risk.free numeric, risk free rate
-#' @param ... additional arguments passed to \code{summary()}
+#' @param ... additional arguments passed to \samp{summary()}
#'
#' @examples
#' # construct the data
Modified: pkg/IntroCompFinR/R/tangency.portfolio.R
===================================================================
--- pkg/IntroCompFinR/R/tangency.portfolio.R 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/R/tangency.portfolio.R 2015-02-20 06:59:09 UTC (rev 12)
@@ -3,21 +3,21 @@
#' @author Eric Zivot
#'
#' @description
-#' Compute tangency (maximum Sharpe ratio) portfolio. The portfolio can allow all assets to be shorted
-#' or not allow any assets to be shorted.
+#' Compute tangency (maximum Sharpe ratio) portfolio. The portfolio can allow all assets to be
+#' shorted or not allow any assets to be shorted.
#'
#' @details
-#' The tangency portfolio \samp{t} is the portfolio of risky assets with the highest Sharpe's slope and
-#' solves the optimization problem: max \eqn{(t(t)\mu-r_f)/(t(t)\Sigma t^{1/2})} s.t. \eqn{t(t)1=1}
-#' where \eqn{r_f} denotes the risk-free rate. If short sales are allowed then there is an analytic
-#' solution using matrix algebra. If short sales are not allowed then the maximum sharpe ratio portfolio must
-#' be computed numerically.
+#' The tangency portfolio \samp{t} is the portfolio of risky assets with the highest Sharpe's slope
+#' and solves the optimization problem: max \eqn{(t(t)\mu-r_f)/(t(t)\Sigma t^{1/2})} s.t.
+#' \eqn{t(t)1=1} where \eqn{r_f} denotes the risk-free rate. If short sales are allowed then there
+#' is an analytic solution using matrix algebra. If short sales are not allowed then the maximum
+#' Sharpe ratio portfolio must be computed numerically.
#'
#' @param er \samp{N x 1} vector of expected returns
#' @param cov.mat \samp{N x N} return covariance matrix
#' @param risk.free numeric, risk free rate
-#' @param shorts logical, if \code{TRUE} then short sales (negative portfolio weights)
-#' are allowed. If \code{FALSE} then no asset is allowed to be sold short.
+#' @param shorts logical, if \samp{TRUE} then short sales (negative portfolio weights)
+#' are allowed. If \samp{FALSE} then no asset is allowed to be sold short.
#'
#' @return
#' \item{call}{captures function call}
Modified: pkg/IntroCompFinR/man/efficient.frontier.Rd
===================================================================
--- pkg/IntroCompFinR/man/efficient.frontier.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/efficient.frontier.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -14,12 +14,12 @@
\item{nport}{scalar, number of efficient portfolios to compute}
-\item{alpha.min}{minimum value of \samp{alpha}, default is \code{-.5}}
+\item{alpha.min}{minimum value of \samp{alpha}, default is \samp{-.5}}
-\item{alpha.max}{maximum value of \samp{alpha}, default is \code{1.5}}
+\item{alpha.max}{maximum value of \samp{alpha}, default is \samp{1.5}}
-\item{shorts}{logical, if \code{TRUE} then short sales (negative portfolio weights)
-are allowed. If \code{FALSE} then no asset is allowed to be sold short}
+\item{shorts}{logical, if \samp{TRUE} then short sales (negative portfolio weights)
+are allowed. If \samp{FALSE} then no asset is allowed to be sold short}
}
\value{
\item{call}{captures function call}
@@ -28,22 +28,21 @@
\item{weights}{\samp{nport x N} matrix of weights of efficient portfolios}
}
\description{
-The function constructs the set of mean-variance efficient portfolios that either allow all assets to be
-sold short or not allow any asset to be sold short. The returned object is of class \samp{Markowitz} for
-which there are \code{print}, \code{summary} and \code{plot} methods.
+The function constructs the set of mean-variance efficient portfolios that either allow all
+assets to be sold short or not allow any asset to be sold short. The returned object is of class
+\samp{Markowitz} for which there are \samp{print}, \samp{summary} and \samp{plot} methods.
}
\details{
-If short sales are allowed (negative weights) then the set of efficient portfolios of risky assets
-can be computed as a convex combination of
-any two efficient portfolios. It is convenient to use the global minimum variance portfolio as
-one portfolio and an efficient portfolio with target expected return equal to the maximum
-expected return of the assets under consideration as the other portfolio. Call these portfolios
-\eqn{m} and \eqn{x}, respectively. Then for any number \samp{alpha}, another efficient
-portfolio can be computed as \eqn{z=\alpha m+(1-\alpha)x}. If short sales are not allowed, then the set
-of efficient portfolios is computed by repeated calls to the function \code{efficient.portfolio()},
-with \code{shorts=FALSE}, for a
-grid of target expected returns starting at the expected return of the global minimum variance portfolio
-(not allowing short sales) and ending at the expected return equal to the maximum expected return of
+If short sales are allowed (negative weights) then the set of efficient portfolios of risky
+assets can be computed as a convex combination of any two efficient portfolios. It is convenient
+to use the global minimum variance portfolio as one portfolio and an efficient portfolio with
+target expected return equal to the maximum expected return of the assets under consideration as
+the other portfolio. Call these portfolios \eqn{m} and \eqn{x}, respectively. Then for any number
+\samp{alpha}, another efficient portfolio can be computed as \eqn{z=\alpha m+(1-\alpha)x}. If
+short sales are not allowed, then the set of efficient portfolios is computed by repeated calls
+to the function \samp{efficient.portfolio()}, with \samp{shorts=FALSE}, for a grid of target
+expected returns starting at the expected return of the global minimum variance portfolio (not
+allowing short sales) and ending at the expected return equal to the maximum expected return of
the assets under consideration.
}
\examples{
Modified: pkg/IntroCompFinR/man/efficient.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/efficient.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/efficient.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -13,8 +13,8 @@
\item{target.return}{scalar, target expected return}
-\item{shorts}{logical, if \code{TRUE} then short sales (negative portfolio weights)
-are allowed. If \code{FALSE} then no asset is allowed to be sold short.}
+\item{shorts}{logical, if \samp{TRUE} then short sales (negative portfolio weights)
+are allowed. If \samp{FALSE} then no asset is allowed to be sold short.}
}
\value{
\item{call}{captures function call}
@@ -23,17 +23,16 @@
\item{weights}{\samp{N x 1} vector of portfolio weights}
}
\description{
-Compute minimum variance portfolio subject to target return either allowing all assets
-to be sold short or not allowing any asset to be sold short. The returned object is
-of class \samp{portfolio}.
+Compute minimum variance portfolio subject to target return either allowing all assets to be sold
+short or not allowing any asset to be sold short. The returned object is of class
+\samp{portfolio}.
}
\details{
-A mean-variance efficient portfolio \eqn{x} allowing short sales (negative weights)
-that achieves the target expected return \eqn{\mu_0}
-solves the optimization problem: min \eqn{t(x)\Sigma x} s.t. \eqn{t(x)1=1} and
-\eqn{t(x)\mu=\mu_0}, for which there is an analytic solution using matrix algebra.
-If short sales are not allowed then the portfolio is computed numerically using the
-function \code{solve.QP()} from the \samp{quadprog} package.
+A mean-variance efficient portfolio \eqn{x} allowing short sales (negative weights) that achieves
+the target expected return \eqn{\mu_0} solves the optimization problem: min \eqn{t(x)\Sigma x}
+s.t. \eqn{t(x)1=1} and \eqn{t(x)\mu=\mu_0}, for which there is an analytic solution using matrix
+algebra. If short sales are not allowed then the portfolio is computed numerically using the
+function \samp{solve.QP()} from the \samp{quadprog} package.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/getPortfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/getPortfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/getPortfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -24,10 +24,10 @@
}
\details{
To specify a portfolio, an expected return vector and covariance matrix for the assets under
-consideration as well as a vector of portfolio weights are needed. The result of \code{getPortfolio}
-is a \samp{portfolio} object, which is list with components for the portfolio expected return,
-portfolio standard deviation, and portfolio weights. There are \code{print}, \code{summary} and \code{plot}
-methods.
+consideration as well as a vector of portfolio weights are needed. The result of
+\samp{getPortfolio} is a \samp{portfolio} object, which is list with components for the portfolio
+expected return, portfolio standard deviation, and portfolio weights. There are \samp{print},
+\samp{summary} and \samp{plot} methods.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/globalMin.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/globalMin.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/globalMin.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -11,8 +11,8 @@
\item{cov.mat}{\samp{N x N} return covariance matrix}
-\item{shorts}{logical, if \code{TRUE} then short sales (negative portfolio weights)
-are allowed. If \code{FALSE} then no asset is allowed to be sold short.}
+\item{shorts}{logical, if \samp{TRUE} then short sales (negative portfolio weights)
+are allowed. If \samp{FALSE} then no asset is allowed to be sold short.}
}
\value{
\item{call}{captures function call}
@@ -21,16 +21,15 @@
\item{weights}{\samp{N x 1} vector of portfolio weights}
}
\description{
-Compute global minimum variance portfolio given expected return vector and
-covariance matrix. The portfolio can allow all assets to be shorted
-or not allow any assets to be shorted. The returned object is of class \samp{portfolio}.
+Compute global minimum variance portfolio given expected return vector and covariance matrix. The
+portfolio can allow all assets to be shorted or not allow any assets to be shorted. The returned
+object is of class \samp{portfolio}.
}
\details{
The global minimum variance portfolio \eqn{m} allowing for short sales solves the optimization
-problem: min \eqn{t(m)\Sigma m} s.t. \eqn{t(m)1=1} for which there is an analytic solution
-using matrix algebra. If short sales are not allowed
-then the portfolio is computed numerically using the function \code{solve.QP()}
-from the \samp{quadprog} package.
+problem: min \eqn{t(m)\Sigma m} s.t. \eqn{t(m)1=1} for which there is an analytic solution using
+matrix algebra. If short sales are not allowed then the portfolio is computed numerically using
+the function \samp{solve.QP()} from the \samp{quadprog} package.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/plot.Markowitz.Rd
===================================================================
--- pkg/IntroCompFinR/man/plot.Markowitz.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/plot.Markowitz.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -9,14 +9,14 @@
\arguments{
\item{object}{object of class Markowitz}
-\item{plot.assets}{if \code{TRUE} then plot asset \code{sd} and \code{er} with asset name labels}
+\item{plot.assets}{if \samp{TRUE} then plot asset \samp{sd} and \samp{er} with asset name labels}
-\item{...}{additional arguments passed to \code{plot()}}
+\item{...}{additional arguments passed to \samp{plot()}}
}
\description{
-Plot efficient frontier. The efficient frontier is a plot of portfolio expected return vs. portfolio
-standard deviation for a collection of mean-variance efficient portfolios - portfolios that minimize vriance
-subject to a target expected return.
+Plot efficient frontier. The efficient frontier is a plot of portfolio expected return vs.
+portfolio standard deviation for a collection of mean-variance efficient portfolios - portfolios
+that minimize variance subject to a target expected return.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/plot.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/plot.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/plot.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -9,10 +9,10 @@
\arguments{
\item{object}{object of class portfolio}
-\item{...}{additional arguments passed to \code{barplot()}}
+\item{...}{additional arguments passed to \samp{barplot()}}
}
\description{
-The \code{plot()} method shows a bar chart of the portfolio weights.
+The \samp{plot()} method shows a bar chart of the portfolio weights.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/print.Markowitz.Rd
===================================================================
--- pkg/IntroCompFinR/man/print.Markowitz.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/print.Markowitz.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -9,7 +9,7 @@
\arguments{
\item{object}{object of class Markowitz}
-\item{...}{additional arguments passed to \code{print()}}
+\item{...}{additional arguments passed to \samp{print()}}
}
\description{
Print method for \samp{Markowitz} objects.
Modified: pkg/IntroCompFinR/man/print.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/print.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/print.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -9,7 +9,7 @@
\arguments{
\item{object}{object of class portfolio}
-\item{...}{additional arguments passed to \code{print()}}
+\item{...}{additional arguments passed to \samp{print()}}
}
\description{
Print method for objects of class \samp{portfolio}.
Modified: pkg/IntroCompFinR/man/summary.Markowitz.Rd
===================================================================
--- pkg/IntroCompFinR/man/summary.Markowitz.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/summary.Markowitz.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -12,10 +12,10 @@
\item{risk.free}{numeric, risk free rate}
}
\description{
-Summary method for objects of class \samp{Markowitz}. For all portfolios on the efficient frontier,
-the expected return, standard deviation and asset weights are shown. If \code{risk.free} is given then
-efficient portfolios that are combinations of the risk free asset and the tangency portfolio are computed. The
-class \code{summary.Markozitz} will be created.
+Summary method for objects of class \samp{Markowitz}. For all portfolios on the efficient
+frontier, the expected return, standard deviation and asset weights are shown. If
+\samp{risk.free} is given then efficient portfolios that are combinations of the risk free asset
+and the tangency portfolio are computed. The class \samp{summary.Markozitz} will be created.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/summary.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/summary.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/summary.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -11,12 +11,11 @@
\item{risk.free}{numeric, risk free rate}
-\item{...}{additional arguments passed to \code{summary()}}
+\item{...}{additional arguments passed to \samp{summary()}}
}
\description{
-Summary method for objects of class \samp{portfolio}. The output is the same
-as the \code{print}. If \code{risk.free} is specified then the portfolio Sharpe
-ratio is also returned.
+Summary method for objects of class \samp{portfolio}. The output is the same as the \samp{print}.
+If \samp{risk.free} is specified then the portfolio Sharpe ratio is also returned.
}
\examples{
# construct the data
Modified: pkg/IntroCompFinR/man/tangency.portfolio.Rd
===================================================================
--- pkg/IntroCompFinR/man/tangency.portfolio.Rd 2015-02-20 00:32:34 UTC (rev 11)
+++ pkg/IntroCompFinR/man/tangency.portfolio.Rd 2015-02-20 06:59:09 UTC (rev 12)
@@ -13,8 +13,8 @@
\item{risk.free}{numeric, risk free rate}
-\item{shorts}{logical, if \code{TRUE} then short sales (negative portfolio weights)
-are allowed. If \code{FALSE} then no asset is allowed to be sold short.}
+\item{shorts}{logical, if \samp{TRUE} then short sales (negative portfolio weights)
+are allowed. If \samp{FALSE} then no asset is allowed to be sold short.}
}
\value{
\item{call}{captures function call}
@@ -23,15 +23,15 @@
\item{weights}{\samp{N x 1} vector of portfolio weights}
}
\description{
-Compute tangency (maximum Sharpe ratio) portfolio. The portfolio can allow all assets to be shorted
-or not allow any assets to be shorted.
+Compute tangency (maximum Sharpe ratio) portfolio. The portfolio can allow all assets to be
+shorted or not allow any assets to be shorted.
}
\details{
-The tangency portfolio \samp{t} is the portfolio of risky assets with the highest Sharpe's slope and
-solves the optimization problem: max \eqn{(t(t)\mu-r_f)/(t(t)\Sigma t^{1/2})} s.t. \eqn{t(t)1=1}
-where \eqn{r_f} denotes the risk-free rate. If short sales are allowed then there is an analytic
-solution using matrix algebra. If short sales are not allowed then the maximum sharpe ratio portfolio must
-be computed numerically.
+The tangency portfolio \samp{t} is the portfolio of risky assets with the highest Sharpe's slope
+and solves the optimization problem: max \eqn{(t(t)\mu-r_f)/(t(t)\Sigma t^{1/2})} s.t.
+\eqn{t(t)1=1} where \eqn{r_f} denotes the risk-free rate. If short sales are allowed then there
+is an analytic solution using matrix algebra. If short sales are not allowed then the maximum
+Sharpe ratio portfolio must be computed numerically.
}
\examples{
# construct the data
More information about the Introcompfinr-commits
mailing list