[Uwgarp-commits] r139 - in pkg/GARPFRM: . R demo man vignettes
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Thu Mar 27 06:01:49 CET 2014
Author: rossbennett34
Date: 2014-03-27 06:01:48 +0100 (Thu, 27 Mar 2014)
New Revision: 139
Added:
pkg/GARPFRM/demo/00Index
Removed:
pkg/GARPFRM/demo/00Index.txt
pkg/GARPFRM/man/garch11.Rd
Modified:
pkg/GARPFRM/.Rbuildignore
pkg/GARPFRM/DESCRIPTION
pkg/GARPFRM/NAMESPACE
pkg/GARPFRM/R/EWMA.R
pkg/GARPFRM/R/backTestVaR.R
pkg/GARPFRM/R/capm.R
pkg/GARPFRM/R/garch11.R
pkg/GARPFRM/R/generic_forecast.R
pkg/GARPFRM/R/monte_carlo.R
pkg/GARPFRM/demo/univariate_GARCH.R
pkg/GARPFRM/man/GARP_FRM-package.Rd
pkg/GARPFRM/man/backTestVaR.Rd
pkg/GARPFRM/man/forecast.uvEWMAvol.Rd
pkg/GARPFRM/man/getCor.Rd
pkg/GARPFRM/man/getCov.Rd
pkg/GARPFRM/man/hypTest.Rd
pkg/GARPFRM/man/monteCarlo.Rd
pkg/GARPFRM/man/plot.EWMA.Rd
pkg/GARPFRM/man/plot.capm_mlm.Rd
pkg/GARPFRM/man/plot.capm_uv.Rd
pkg/GARPFRM/man/plotEndingPrices.Rd
pkg/GARPFRM/man/uvGARCH.Rd
pkg/GARPFRM/vignettes/DelineatingEfficientPortfolios.Rnw
pkg/GARPFRM/vignettes/EstimatingVolatilitiesCorrelation.Rnw
pkg/GARPFRM/vignettes/QuantifyingVolatilityVaRModels.Rnw
Log:
Cleaning up man files and vignettes
Modified: pkg/GARPFRM/.Rbuildignore
===================================================================
--- pkg/GARPFRM/.Rbuildignore 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/.Rbuildignore 2014-03-27 05:01:48 UTC (rev 139)
@@ -1,2 +1,5 @@
^.*\.Rproj$
^\.Rproj\.user$
+^\.Rhistory$
+^\.Rapp\.Rhistory$
+^\.DS_Store$
\ No newline at end of file
Modified: pkg/GARPFRM/DESCRIPTION
===================================================================
--- pkg/GARPFRM/DESCRIPTION 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/DESCRIPTION 2014-03-27 05:01:48 UTC (rev 139)
@@ -4,7 +4,7 @@
Version: 0.1.0
Date: 2013-11-17
Author: Ross Bennett, Thomas Fillebeen, Guy Yollin
-Maintainer: Who to complain to <yourfault at somewhere.net>
+Maintainer: Thomas Fillebeen <tdf17 at uw.edu>
Description: Global Association of Risk Professionals: Financial Risk Manager
Depends:
R (>= 2.15.0),
@@ -12,7 +12,9 @@
PerformanceAnalytics (>= 1.0.0)
Suggests:
quadprog,
- rugarch (>= 1.3.1)
+ rugarch (>= 1.3.1),
+ PortfolioAnalytics,
+ foreach (>= 1.4.1)
License: GPL
Collate:
'backTestVaR.R'
Modified: pkg/GARPFRM/NAMESPACE
===================================================================
--- pkg/GARPFRM/NAMESPACE 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/NAMESPACE 2014-03-27 05:01:48 UTC (rev 139)
@@ -18,9 +18,7 @@
export(estimateLambdaCov)
export(estimateLambdaVol)
export(EWMA)
-export(fcstGarch11)
export(forecast)
-export(garch11)
export(getAlphas)
export(getBetas)
export(getCor)
@@ -33,8 +31,6 @@
export(hypTest)
export(minVarPortfolio)
export(monteCarlo)
-export(plot.capm_mlm)
-export(plot.capm_uv)
export(plotEndingPrices)
export(portReturnTwoAsset)
export(portSDTwoAsset)
@@ -48,7 +44,6 @@
export(simpleVolatility)
export(tangentPortfolio)
export(uvGARCH)
-S3method(fcstGarch11,DCCfit)
S3method(forecast,uvEWMAvol)
S3method(forecast,uvGARCH)
S3method(getAlphas,capm_mlm)
@@ -64,6 +59,8 @@
S3method(hypTest,capm_mlm)
S3method(hypTest,capm_uv)
S3method(plot,backtestVaR)
+S3method(plot,capm_mlm)
+S3method(plot,capm_uv)
S3method(plot,efficient.frontier)
S3method(plot,efTwoAsset)
S3method(plot,EWMA)
Modified: pkg/GARPFRM/R/EWMA.R
===================================================================
--- pkg/GARPFRM/R/EWMA.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/EWMA.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -569,7 +569,7 @@
#'
#' Extract the covariance of two assets from an \code{mvEWMAcov} object
#'
-#' @param object an EWMA object created by \code{\link{EWMA}}
+#' @param EWMA an EWMA object created by \code{\link{EWMA}}
#' @param assets character vector or numeric vector. The assets can be
#' specified by name or index.
#' @examples
@@ -655,7 +655,7 @@
#'
#' Extract the correlation of two assets from an \code{mvEWMAcor} object
#'
-#' @param object an EWMA object created by \code{\link{EWMA}}
+#' @param EWMA an EWMA object created by \code{\link{EWMA}}
#' @param assets character vector or numeric vector. The assets can be
#' specified by name or index.
#' @examples
@@ -707,16 +707,17 @@
#'
#' Plot method for EWMA objects.
#'
-#' @param x an EWMA object created via \code{\link{EWMA}}
-#' @param y not used
-#' @param \dots passthrough parameters to \code{plot.xts}
+#' @param x an EWMA object created via \code{\link{EWMA}}.
+#' @param y not used.
+#' @param \dots passthrough parameters to \code{plot.xts}.
#' @param assets character vector or numeric vector of assets to extract from
#' the covariance or correlation matrix. The assets can be specified by name or
#' index. This argument is only usd for multivariate EWMA estimates of
#' a covariance or correlation matrix.
#' @param legendLoc location of legend. If NULL, the legend will be omitted
-#' from the plot
-#' @param main main title for the plot
+#' from the plot.
+#' @param main main title for the plot.
+#' @param legendCex numerical value giving the amount by which the legend.
#' @examples
#' # data and parameters for EWMA estimate
#' data(crsp_weekly)
@@ -751,7 +752,7 @@
#' @author Ross Bennett
#' @method plot EWMA
#' @S3method plot EWMA
-plot.EWMA <- function(x, y=NULL, ..., assets=c(1,2), legendLoc=NULL, main="EWMA Estimate", cexLegend=0.8){
+plot.EWMA <- function(x, y=NULL, ..., assets=c(1,2), legendLoc=NULL, main="EWMA Estimate", legendCex=0.8){
type <- x$model$type
if(inherits(x, "uvEWMAvol") | inherits(x, "uvEWMAcov") | inherits(x, "uvEWMAcor")){
# all uvEWMA* objects have same format
@@ -770,6 +771,6 @@
plot.xts(x=estValues, ...=..., type="l", ylab=type, main=main)
if(!is.null(legendLoc)){
legend(legendLoc, legend=c("EWMA Estimate"),
- lty=1, col="black", bty="n", cex=cexLegend)
+ lty=1, col="black", bty="n", cex=legendCex)
}
}
Modified: pkg/GARPFRM/R/backTestVaR.R
===================================================================
--- pkg/GARPFRM/R/backTestVaR.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/backTestVaR.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -69,6 +69,7 @@
#' @param p confidence level for the VaR estimate.
#' @param method method for the VaR calculation. Valid choices are "modified", "guassian", "historical", and "kernel"
#' @param bootstrap TRUE/FALSE use the bootstrap estimate for the VaR calculation, (default FALSE).
+#' @param replications number of bootstrap replications.
#' @param bootParallel TRUE/FALSE run the bootstrap in parallel, (default FALSE).
#' @author Ross Bennett
#' @seealso \code{\link[PerformanceAnalytics]{VaR}}, \code{\link{bootVaR}}
@@ -151,7 +152,7 @@
# GARCH model VaR Backtesting
# http://www.unstarched.net/wp-content/uploads/2013/06/an-example-in-rugarch.pdf
# extract R from the fit object
- R <- xts(garchModel$fit at model$modeldata$data, garchModel$fit at model$modeldata$index)
+ R <- xts(garch$fit at model$modeldata$data, garch$fit at model$modeldata$index)
# call ugarchroll
modelRoll <- ugarchroll(spec=getSpec(garch), data=R, n.ahead=nAhead,
refit.every=refitEvery, refit.window="moving",
Modified: pkg/GARPFRM/R/capm.R
===================================================================
--- pkg/GARPFRM/R/capm.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/capm.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -166,7 +166,9 @@
#' @param y not used
#' @param \dots passthrough parameters to \code{\link{plot}}.
#' @param main a main title for the plot
-#' @export
+#' @author Thomas Fillebeen
+#' @method plot capm_uv
+#' @S3method plot capm_uv
plot.capm_uv <- function(x, y, ..., main="CAPM"){
xlab <- colnames(x$x_data)
ylab <- colnames(x$y_data)
@@ -177,8 +179,8 @@
a_tstat = coef(summary(x))[1,2]
beta = coef(summary(x))[2,1]
b_tstat = coef(summary(x))[2,2]
- legend("topleft", legend=c(paste("alpha =", round(alpha,dig=2),"(", round(a_tstat,dig=2),")"),
- paste("beta =", round(beta,dig=2),"(", round(b_tstat,dig=2),")")), cex=.8, bty="n")
+ legend("topleft", legend=c(paste("alpha =", round(alpha,digits=2),"(", round(a_tstat,digits=2),")"),
+ paste("beta =", round(beta,digits=2),"(", round(b_tstat,digits=2),")")), cex=.8, bty="n")
}
@@ -190,7 +192,9 @@
#' @param y not used
#' @param \dots passthrough parameters to \code{\link{plot}}.
#' @param main a main title for the plot
-#' @export
+#' @author Thomas Fillebeen
+#' @method plot capm_mlm
+#' @S3method plot capm_mlm
plot.capm_mlm <- function(x, y, ..., main="CAPM"){
if(ncol(x$y_data) > 4) warning("Only first 4 assets will be graphically displayed")
par(mfrow=c(2,round(ncol(coef(x))/2)))
@@ -234,6 +238,7 @@
#' Returns a true (reject) or false (fail to reject).
#'
#' @param object a capm object created by \code{\link{CAPM}}
+#' @param CI confidence level
#' @export
hypTest <- function(object,CI){
UseMethod("hypTest")
Modified: pkg/GARPFRM/R/garch11.R
===================================================================
--- pkg/GARPFRM/R/garch11.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/garch11.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -12,71 +12,71 @@
## I think we should omit this for phase 1 and maybe reconsider in phase 2
## or beyond.
-#' GARCH Models
-#'
-#' This function is a basic wrapper of functions in the rugarch and rmgarch
-#' packages to specify and fit GARCH models. The rugarch and rmgarch packages
-#' provide functions to specify and fit a rich set of GARCH models.
-#' The purpose of this function is to specify and fit a GARCH model while
-#' abstracting away some complexities.
-#'
-#' The rugarch package implements univariate garch models and the
-#' rmgarch package implements multivariate garch models. Univariate or
-#' multivariate data is automatically detected and the appropriate GARCH model
-#' will be specified and fit.
-#'
-#' For complete functionality of GARCH models, it is recommended to
-#' directly use functions in the rugarch and rmgarch packages.
-#'
-#' @param R xts object of asset returns
-#' @param model “sGARCH”, “fGARCH”, “eGARCH”, “gjrGARCH”, “apARCH” and “iGARCH” and “csGARCH”
-#' @param distribution.model. Valid choices are “norm” for the normal distibution, “snorm” for the skew-normal distribution, “std” for the student-t, “sstd” for the skew-student, “ged” for the generalized error distribution, “sged” for the skew-generalized error distribution, “nig” for the normal inverse gaussian distribution, “ghyp” for the Generalized Hyperbolic, and “jsu” for Johnson's SU distribution.
-#' @export
+# GARCH Models
+#
+# This function is a basic wrapper of functions in the rugarch and rmgarch
+# packages to specify and fit GARCH models. The rugarch and rmgarch packages
+# provide functions to specify and fit a rich set of GARCH models.
+# The purpose of this function is to specify and fit a GARCH model while
+# abstracting away some complexities.
+#
+# The rugarch package implements univariate garch models and the
+# rmgarch package implements multivariate garch models. Univariate or
+# multivariate data is automatically detected and the appropriate GARCH model
+# will be specified and fit.
+#
+# For complete functionality of GARCH models, it is recommended to
+# directly use functions in the rugarch and rmgarch packages.
+#
+# @param R xts object of asset returns
+# @param model “sGARCH”, “fGARCH”, “eGARCH”, “gjrGARCH”, “apARCH” and “iGARCH” and “csGARCH”
+# @param distribution.model. Valid choices are “norm” for the normal distibution, “snorm” for the skew-normal distribution, “std” for the student-t, “sstd” for the skew-student, “ged” for the generalized error distribution, “sged” for the skew-generalized error distribution, “nig” for the normal inverse gaussian distribution, “ghyp” for the Generalized Hyperbolic, and “jsu” for Johnson's SU distribution.
+# @export
# By default we use UV N~GARCH(1,1) and Bollerslev for each series
-garch11 <- function(R, model = "sGARCH", distribution.model = "norm"){
- # if univariate data, load the rugarch package
- # if multivariate data, load the rmgarch package
-
- garch11.spec = ugarchspec(mean.model = list(armaOrder = c(0,0)),
- variance.model = list(garchOrder = c(1,1), model = model),
- distribution.model)
-
- # DCC specification: GARCH(1,1) for conditional cor
- nbColumns = ncol(R)
- dcc.garch11.spec = dccspec(uspec = multispec( replicate(nbColumns, garch11.spec) ),
- dccOrder = c(1,1), distribution = "mvnorm")
- dcc.garch11.spec
-
- dcc.fit = dccfit(dcc.garch11.spec, data = R)
- class(dcc.fit)
- slotNames(dcc.fit)
- names(dcc.fit at mfit)
- names(dcc.fit at model)
- return(dcc.fit)
-}
+# garch11 <- function(R, model = "sGARCH", distribution.model = "norm"){
+# # if univariate data, load the rugarch package
+# # if multivariate data, load the rmgarch package
+#
+# garch11.spec = ugarchspec(mean.model = list(armaOrder = c(0,0)),
+# variance.model = list(garchOrder = c(1,1), model = model),
+# distribution.model)
+#
+# # DCC specification: GARCH(1,1) for conditional cor
+# nbColumns = ncol(R)
+# dcc.garch11.spec = dccspec(uspec = multispec( replicate(nbColumns, garch11.spec) ),
+# dccOrder = c(1,1), distribution = "mvnorm")
+# dcc.garch11.spec
+#
+# dcc.fit = dccfit(dcc.garch11.spec, data = R)
+# class(dcc.fit)
+# slotNames(dcc.fit)
+# names(dcc.fit at mfit)
+# names(dcc.fit at model)
+# return(dcc.fit)
+# }
-#' Forecast GARCH(1,1)
-#'
-#' Description of forecast GARCH(1,1)
-#'
-#' @param garch11 object created by \code{\link{GARCH(1,1)}}
-#' @param window is the forecast window (default is set to window = 100)
-#' @export
-fcstGarch11 <- function(object, window){
- UseMethod("fcstGarch11")
-}
+# Forecast GARCH(1,1)
+#
+# Description of forecast GARCH(1,1)
+#
+# @param garch11 object created by \code{\link{garch11}}
+# @param window is the forecast window (default is set to window = 100)
+# @export
+# fcstGarch11 <- function(object, window){
+# UseMethod("fcstGarch11")
+# }
-#' @method fcstGarch11 Dccfit
-#' @S3method fcstGarch11 DCCfit
-fcstGarch11.DCCfit <- function(object, window = 100){
- #if ((window > nrow(object))) {stop("Window is too large to forecast")}
- result = dccforecast(object, n.ahead=window)
- class(result)
- slotNames(result)
- class(result at mforecast)
- names(result at mforecast)
- return(result)
-}
+# @method fcstGarch11 Dccfit
+# @S3method fcstGarch11 DCCfit
+# fcstGarch11.DCCfit <- function(object, window = 100){
+# #if ((window > nrow(object))) {stop("Window is too large to forecast")}
+# result = dccforecast(object, n.ahead=window)
+# class(result)
+# slotNames(result)
+# class(result at mforecast)
+# names(result at mforecast)
+# return(result)
+# }
#' Univariate GARCH Model
@@ -92,19 +92,19 @@
#'
#' @param R xts object of asset returns.
#' @param model GARCH Model to specify and fit. Valid GARCH models are
-#' “sGARCH”, “fGARCH”, “eGARCH”, “gjrGARCH”, “apARCH”, “iGARCH” and “csGARCH”.
+#' "sGARCH", "fGARCH", "eGARCH", "gjrGARCH", "apARCH", "iGARCH", and "csGARCH".
#' @param garchOrder the ARCH(q) and GARCH(p) orders.
#' @param armaOrder the autoregressive and moving average orders.
#' @param distribution conditional density to use for the innovations. Valid
-#' distributions are “norm” for the normal distibution, “snorm” for the
-#' skew-normal distribution, “std” for the student-t,
-#' “sstd” for the skew-student, “ged” for the generalized error distribution,
-#' “sged” for the skew-generalized error distribution,
-#' “nig” for the normal inverse gaussian distribution,
-#' “ghyp” for the Generalized Hyperbolic, and “jsu” for Johnson's SU distribution.
+#' distributions are "norm" for the normal distibution, "snorm" for the
+#' skew-normal distribution, "std" for the student-t,
+#' "sstd for the skew-student, "ged" for the generalized error distribution,
+#' "sged" for the skew-generalized error distribution,
+#' "nig" for the normal inverse gaussian distribution,
+#' "ghyp" for the Generalized Hyperbolic, and "jsu" for Johnson's SU distribution.
#' @param fixedParams named list of parameters to keep fixed.
#' @param solver the solver to use to fit the GARCH model. Valid solvers are
-#' “nlminb”, “solnp”, “lbfgs”, “gosolnp”, “nloptr” or “hybrid”
+#' "nlminb", "solnp", "lbfgs", "gosolnp", "nloptr", or "hybrid".
#' @param outSample number of periods of data used to fit the model.
#' \code{nrow(R) - outSample} number of periods to keep as out of sample data
#' points.
Modified: pkg/GARPFRM/R/generic_forecast.R
===================================================================
--- pkg/GARPFRM/R/generic_forecast.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/generic_forecast.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -46,9 +46,6 @@
#' @param model EWMA model fit via \code{\link{EWMA}}
#' @param nAhead number of steps ahead to forecast. (nAhead = 1 only supported)
#' @param \dots additional passthrough parameters
-#' @param nRoll number of rolling forecasts
-#' @param externalForecasts named list of external regressors in the mean and/or
-#' variance equations
#' @return one period ahead EWMA volatility forecast
#' @method forecast uvEWMAvol
#' @S3method forecast uvEWMAvol
Modified: pkg/GARPFRM/R/monte_carlo.R
===================================================================
--- pkg/GARPFRM/R/monte_carlo.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/R/monte_carlo.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -64,7 +64,7 @@
#' @param mu annualized expected return
#' @param sigma annualized standard deviation
#' @param N number of simulations
-#' @param Time length of simulation (in years)
+#' @param time length of simulation (in years)
#' @param steps number of time steps
#' @param starting_value asset price starting value
#' @return matrix of simulated price paths where each column represents a price path
@@ -111,8 +111,11 @@
#'
#' Plot the kernel density estimate and histogram of the ending prices
#' from a Monte Carlo simulation.
-#' @param mc monte carlo object created with \code{monteCarlo}
-#' @param \dots additional arguments passed to \code{hist}
+#' @param mc monte carlo object created with \code{monteCarlo}.
+#' @param \dots additional arguments passed to \code{hist}.
+#' @param main a main title for the plot.
+#' @param xlab x-axis label, same as in \code{\link{plot}}.
+#' @param ylab y-axis label, same as in \code{\link{plot}}.
#' @examples
#' library(GARPFRM)
#'
Copied: pkg/GARPFRM/demo/00Index (from rev 134, pkg/GARPFRM/demo/00Index.txt)
===================================================================
--- pkg/GARPFRM/demo/00Index (rev 0)
+++ pkg/GARPFRM/demo/00Index 2014-03-27 05:01:48 UTC (rev 139)
@@ -0,0 +1,7 @@
+bootstrap demonstrates using bootstrap method to estimate various statistics
+demo_CAPM demonstrate Capital Asset Pricing Model functions
+demo_EWMA_GARCH11 demonstrate exponentially weighted moving average and GARCH models
+EWMA demonstrate exponentially weighted moving average model
+monte_carlo demonstrate monte carlo method to simulate asset price paths
+univariate_GARCH demonstrate fitting a GARCH model to a univariate data set
+backtest_VaR demonstrate Value at Risk backtesting
Deleted: pkg/GARPFRM/demo/00Index.txt
===================================================================
--- pkg/GARPFRM/demo/00Index.txt 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/demo/00Index.txt 2014-03-27 05:01:48 UTC (rev 139)
@@ -1,7 +0,0 @@
-bootstrap.R demonstrates using bootstrap method to estimate various statistics
-demo_CAPM.R demonstrate Capital Asset Pricing Model functions
-demo_EWMA_GARCH11.R demonstrate exponentially weighted moving average and GARCH models
-EWMA.R demonstrate exponentially weighted moving average model
-monte_carlo.R demonstrate monte carlo method to simulate asset price paths
-univariate_GARCH.R demonstrate fitting a GARCH model to a univariate data set
-backtest_VaR.R demonstrate Value at Risk backtesting
Modified: pkg/GARPFRM/demo/univariate_GARCH.R
===================================================================
--- pkg/GARPFRM/demo/univariate_GARCH.R 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/demo/univariate_GARCH.R 2014-03-27 05:01:48 UTC (rev 139)
@@ -11,7 +11,7 @@
# The uvGARCH function uses the excellent rugarch package, which has a rich
# set of functions for analysis of fitted GARCH models. The fitted model can
-# be extracted with the getFit function. Refer to help("uGARCHfit-class")
+# be extracted with the getFit function. Refer to help("uGARCHfit-class")
# for available all methods for the uGARCHfit object that is returned by getFit.
# Here we can extract the GARCH model specification and fit
spec <- getSpec(model0)
@@ -34,7 +34,7 @@
plot(fit)
plot(fit, which=1)
-# Forecast 10 periods ahead using the standard ARMA(0,0)-GARCH(1,1) model
+# Forecast 10 periods ahead using the standard ARMA(0,0)-GARCH(1,1) model
forecast1 <- forecast(model0, nAhead=10)
forecast1
plot(forecast1)
@@ -52,27 +52,27 @@
plot(forecast2, which=2)
# Several distributions are available for the innovations. Distributions include:
-# “norm”: normal distibution
-# “snorm”: skew-normal distribution
-# “std”: student-t distribution
-# “sstd”: skew-student distribution
-# “ged”: generalized error distribution
-# “sged”: skew-generalized error distribution
-# “nig”: normal inverse gaussian distribution
-# “ghyp”: Generalized Hyperbolic distribution
-# “jsu”: Johnson's SU distribution.
+# "norm": normal distibution
+# "snorm": skew-normal distribution
+# "std": student-t distribution
+# "sstd": skew-student distribution
+# "ged": generalized error distribution
+# "sged": skew-generalized error distribution
+# "nig": normal inverse gaussian distribution
+# "ghyp": Generalized Hyperbolic distribution
+# "jsu": Johnson's SU distribution.
-# Here we specify and fit the MSFT returns to a standard ARMA(0,0)-GARCH(1,1)
+# Here we specify and fit the MSFT returns to a standard ARMA(0,0)-GARCH(1,1)
# model with student-t innovations
model0.std <- uvGARCH(R, armaOrder=c(0,0), distribution="std")
# The default arguments for uvGARCH are to specify and fit a standard
-# ARMA(1,1)-GARCH(1,1) model
+# ARMA(1,1)-GARCH(1,1)model
model11 <- uvGARCH(R)
# In addition to specifyin the model with different ar and ma orders, the
# ARCH(q) and GARCH(p) orders can also be specified. Here we fit a standard
-# ARMA(1,1)-GARCH(2,10 model
+# ARMA(1,1)-GARCH(2,1) model
model21 <- uvGARCH(R, garchOrder=c(2,1))
getSpec(model21)
getFit(model21)
Modified: pkg/GARPFRM/man/GARP_FRM-package.Rd
===================================================================
--- pkg/GARPFRM/man/GARP_FRM-package.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/GARP_FRM-package.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -45,8 +45,7 @@
xts
GARP books
}
-GARP,
-FRM
+
\keyword{ package }
\seealso{
% Optional links to other man pages, e.g.
Modified: pkg/GARPFRM/man/backTestVaR.Rd
===================================================================
--- pkg/GARPFRM/man/backTestVaR.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/backTestVaR.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -21,6 +21,8 @@
\item{bootstrap}{TRUE/FALSE use the bootstrap estimate
for the VaR calculation, (default FALSE).}
+ \item{replications}{number of bootstrap replications.}
+
\item{bootParallel}{TRUE/FALSE run the bootstrap in
parallel, (default FALSE).}
}
Modified: pkg/GARPFRM/man/forecast.uvEWMAvol.Rd
===================================================================
--- pkg/GARPFRM/man/forecast.uvEWMAvol.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/forecast.uvEWMAvol.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -11,11 +11,6 @@
= 1 only supported)}
\item{\dots}{additional passthrough parameters}
-
- \item{nRoll}{number of rolling forecasts}
-
- \item{externalForecasts}{named list of external
- regressors in the mean and/or variance equations}
}
\value{
one period ahead EWMA volatility forecast
Deleted: pkg/GARPFRM/man/garch11.Rd
===================================================================
--- pkg/GARPFRM/man/garch11.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/garch11.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -1,41 +0,0 @@
-\name{garch11}
-\alias{garch11}
-\title{GARCH Models}
-\usage{
- garch11(R, model = "sGARCH", distribution.model = "norm")
-}
-\arguments{
- \item{R}{xts object of asset returns}
-
- \item{model}{“sGARCH”, “fGARCH”, “eGARCH”, “gjrGARCH”,
- “apARCH” and “iGARCH” and “csGARCH”}
-
- \item{distribution.model.}{Valid choices are “norm” for
- the normal distibution, “snorm” for the skew-normal
- distribution, “std” for the student-t, “sstd” for the
- skew-student, “ged” for the generalized error
- distribution, “sged” for the skew-generalized error
- distribution, “nig” for the normal inverse gaussian
- distribution, “ghyp” for the Generalized Hyperbolic, and
- “jsu” for Johnson's SU distribution.}
-}
-\description{
- This function is a basic wrapper of functions in the
- rugarch and rmgarch packages to specify and fit GARCH
- models. The rugarch and rmgarch packages provide
- functions to specify and fit a rich set of GARCH models.
- The purpose of this function is to specify and fit a
- GARCH model while abstracting away some complexities.
-}
-\details{
- The rugarch package implements univariate garch models
- and the rmgarch package implements multivariate garch
- models. Univariate or multivariate data is automatically
- detected and the appropriate GARCH model will be
- specified and fit.
-
- For complete functionality of GARCH models, it is
- recommended to directly use functions in the rugarch and
- rmgarch packages.
-}
-
Modified: pkg/GARPFRM/man/getCor.Rd
===================================================================
--- pkg/GARPFRM/man/getCor.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/getCor.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -5,8 +5,7 @@
getCor(EWMA, assets)
}
\arguments{
- \item{object}{an EWMA object created by
- \code{\link{EWMA}}}
+ \item{EWMA}{an EWMA object created by \code{\link{EWMA}}}
\item{assets}{character vector or numeric vector. The
assets can be specified by name or index.}
Modified: pkg/GARPFRM/man/getCov.Rd
===================================================================
--- pkg/GARPFRM/man/getCov.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/getCov.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -5,8 +5,7 @@
getCov(EWMA, assets)
}
\arguments{
- \item{object}{an EWMA object created by
- \code{\link{EWMA}}}
+ \item{EWMA}{an EWMA object created by \code{\link{EWMA}}}
\item{assets}{character vector or numeric vector. The
assets can be specified by name or index.}
Modified: pkg/GARPFRM/man/hypTest.Rd
===================================================================
--- pkg/GARPFRM/man/hypTest.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/hypTest.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -7,6 +7,8 @@
\arguments{
\item{object}{a capm object created by
\code{\link{CAPM}}}
+
+ \item{CI}{confidence level}
}
\description{
Description of CAPM beta/alpha hypothesis test TODO: We
Modified: pkg/GARPFRM/man/monteCarlo.Rd
===================================================================
--- pkg/GARPFRM/man/monteCarlo.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/monteCarlo.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -12,7 +12,7 @@
\item{N}{number of simulations}
- \item{Time}{length of simulation (in years)}
+ \item{time}{length of simulation (in years)}
\item{steps}{number of time steps}
Modified: pkg/GARPFRM/man/plot.EWMA.Rd
===================================================================
--- pkg/GARPFRM/man/plot.EWMA.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/plot.EWMA.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -4,14 +4,14 @@
\usage{
\method{plot}{EWMA} (x, y = NULL, ..., assets = c(1, 2),
legendLoc = NULL, main = "EWMA Estimate",
- cexLegend = 0.8)
+ legendCex = 0.8)
}
\arguments{
- \item{x}{an EWMA object created via \code{\link{EWMA}}}
+ \item{x}{an EWMA object created via \code{\link{EWMA}}.}
- \item{y}{not used}
+ \item{y}{not used.}
- \item{\dots}{passthrough parameters to \code{plot.xts}}
+ \item{\dots}{passthrough parameters to \code{plot.xts}.}
\item{assets}{character vector or numeric vector of
assets to extract from the covariance or correlation
@@ -20,9 +20,12 @@
of a covariance or correlation matrix.}
\item{legendLoc}{location of legend. If NULL, the legend
- will be omitted from the plot}
+ will be omitted from the plot.}
- \item{main}{main title for the plot}
+ \item{main}{main title for the plot.}
+
+ \item{legendCex}{numerical value giving the amount by
+ which the legend.}
}
\description{
Plot method for EWMA objects.
Modified: pkg/GARPFRM/man/plot.capm_mlm.Rd
===================================================================
--- pkg/GARPFRM/man/plot.capm_mlm.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/plot.capm_mlm.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -2,7 +2,7 @@
\alias{plot.capm_mlm}
\title{Plotting method for CAPM}
\usage{
- plot.capm_mlm(x, y, ..., main = "CAPM")
+ \method{plot}{capm_mlm} (x, y, ..., main = "CAPM")
}
\arguments{
\item{x}{a capm object created by \code{\link{CAPM}}.}
@@ -17,4 +17,7 @@
\description{
Plot a fitted CAPM object
}
+\author{
+ Thomas Fillebeen
+}
Modified: pkg/GARPFRM/man/plot.capm_uv.Rd
===================================================================
--- pkg/GARPFRM/man/plot.capm_uv.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/plot.capm_uv.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -2,7 +2,7 @@
\alias{plot.capm_uv}
\title{Plotting method for CAPM}
\usage{
- plot.capm_uv(x, y, ..., main = "CAPM")
+ \method{plot}{capm_uv} (x, y, ..., main = "CAPM")
}
\arguments{
\item{x}{a capm object created by \code{\link{CAPM}}.}
@@ -17,4 +17,7 @@
\description{
Plot a fitted CAPM object
}
+\author{
+ Thomas Fillebeen
+}
Modified: pkg/GARPFRM/man/plotEndingPrices.Rd
===================================================================
--- pkg/GARPFRM/man/plotEndingPrices.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/plotEndingPrices.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -7,9 +7,15 @@
}
\arguments{
\item{mc}{monte carlo object created with
- \code{monteCarlo}}
+ \code{monteCarlo}.}
- \item{\dots}{additional arguments passed to \code{hist}}
+ \item{\dots}{additional arguments passed to \code{hist}.}
+
+ \item{main}{a main title for the plot.}
+
+ \item{xlab}{x-axis label, same as in \code{\link{plot}}.}
+
+ \item{ylab}{y-axis label, same as in \code{\link{plot}}.}
}
\description{
Plot the kernel density estimate and histogram of the
Modified: pkg/GARPFRM/man/uvGARCH.Rd
===================================================================
--- pkg/GARPFRM/man/uvGARCH.Rd 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/man/uvGARCH.Rd 2014-03-27 05:01:48 UTC (rev 139)
@@ -11,8 +11,8 @@
\item{R}{xts object of asset returns.}
\item{model}{GARCH Model to specify and fit. Valid GARCH
- models are “sGARCH”, “fGARCH”, “eGARCH”, “gjrGARCH”,
- “apARCH”, “iGARCH” and “csGARCH”.}
+ models are "sGARCH", "fGARCH", "eGARCH", "gjrGARCH",
+ "apARCH", "iGARCH", and "csGARCH".}
\item{garchOrder}{the ARCH(q) and GARCH(p) orders.}
@@ -20,21 +20,21 @@
orders.}
\item{distribution}{conditional density to use for the
- innovations. Valid distributions are “norm” for the
- normal distibution, “snorm” for the skew-normal
- distribution, “std” for the student-t, “sstd” for the
- skew-student, “ged” for the generalized error
- distribution, “sged” for the skew-generalized error
- distribution, “nig” for the normal inverse gaussian
- distribution, “ghyp” for the Generalized Hyperbolic, and
- “jsu” for Johnson's SU distribution.}
+ innovations. Valid distributions are "norm" for the
+ normal distibution, "snorm" for the skew-normal
+ distribution, "std" for the student-t, "sstd for the
+ skew-student, "ged" for the generalized error
+ distribution, "sged" for the skew-generalized error
+ distribution, "nig" for the normal inverse gaussian
+ distribution, "ghyp" for the Generalized Hyperbolic, and
+ "jsu" for Johnson's SU distribution.}
\item{fixedParams}{named list of parameters to keep
fixed.}
\item{solver}{the solver to use to fit the GARCH model.
- Valid solvers are “nlminb”, “solnp”, “lbfgs”, “gosolnp”,
- “nloptr” or “hybrid”}
+ Valid solvers are "nlminb", "solnp", "lbfgs", "gosolnp",
+ "nloptr", or "hybrid".}
\item{outSample}{number of periods of data used to fit
the model. \code{nrow(R) - outSample} number of periods
Modified: pkg/GARPFRM/vignettes/DelineatingEfficientPortfolios.Rnw
===================================================================
--- pkg/GARPFRM/vignettes/DelineatingEfficientPortfolios.Rnw 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/vignettes/DelineatingEfficientPortfolios.Rnw 2014-03-27 05:01:48 UTC (rev 139)
@@ -6,6 +6,7 @@
\begin{document}
<<echo=FALSE>>=
+library(knitr)
opts_chunk$set(tidy=FALSE, warning=FALSE, fig.width=5, fig.height=5)
@
Modified: pkg/GARPFRM/vignettes/EstimatingVolatilitiesCorrelation.Rnw
===================================================================
--- pkg/GARPFRM/vignettes/EstimatingVolatilitiesCorrelation.Rnw 2014-03-27 04:06:42 UTC (rev 138)
+++ pkg/GARPFRM/vignettes/EstimatingVolatilitiesCorrelation.Rnw 2014-03-27 05:01:48 UTC (rev 139)
@@ -6,6 +6,7 @@
\begin{document}
<<echo=FALSE>>=
+library(knitr)
opts_chunk$set(cache=TRUE, tidy=FALSE, warning=FALSE, fig.width=5, fig.height=5)
@
Modified: pkg/GARPFRM/vignettes/QuantifyingVolatilityVaRModels.Rnw
===================================================================
[TRUNCATED]
To get the complete diff run:
svnlook diff /svnroot/uwgarp -r 139
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