[Returnanalytics-commits] r2724 - in pkg/FactorAnalytics: R man
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Aug 5 22:34:55 CEST 2013
Author: chenyian
Date: 2013-08-05 22:34:55 +0200 (Mon, 05 Aug 2013)
New Revision: 2724
Modified:
pkg/FactorAnalytics/R/factorModelMonteCarlo.R
pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r
pkg/FactorAnalytics/R/predict.StatFactorModel.r
pkg/FactorAnalytics/R/predict.TimeSeriesFactorModel.r
pkg/FactorAnalytics/R/print.FundamentalFactorModel.r
pkg/FactorAnalytics/R/print.TimeSeriesFactorModel.r
pkg/FactorAnalytics/R/summary.FundamentalFactorModel.r
pkg/FactorAnalytics/R/summary.StatFactorModel.r
pkg/FactorAnalytics/man/Stock.df.Rd
pkg/FactorAnalytics/man/factorModelMonteCarlo.Rd
pkg/FactorAnalytics/man/fitTimeseriesFactorModel.Rd
pkg/FactorAnalytics/man/predict.FundamentalFactorModel.Rd
pkg/FactorAnalytics/man/predict.StatFactorModel.Rd
pkg/FactorAnalytics/man/predict.TimeSeriesFactorModel.Rd
pkg/FactorAnalytics/man/print.FundamentalFactorModel.Rd
pkg/FactorAnalytics/man/print.TimeSeriesFactorModel.Rd
pkg/FactorAnalytics/man/summary.FundamentalFactorModel.Rd
pkg/FactorAnalytics/man/summary.StatFactorModel.Rd
Log:
debug examples.
Modified: pkg/FactorAnalytics/R/factorModelMonteCarlo.R
===================================================================
--- pkg/FactorAnalytics/R/factorModelMonteCarlo.R 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/factorModelMonteCarlo.R 2013-08-05 20:34:55 UTC (rev 2724)
@@ -51,12 +51,12 @@
#'
#' # load data from the database
#' data(managers.df)
-#' fit <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+#' fit <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
#' factors.names=c("EDHEC.LS.EQ","SP500.TR"),
#' data=managers.df,fit.method="OLS")
-#' factorData=factors
-#' Beta.mat=fit$beta.mat
-#' residualData=as.matrix(fit$residVars.vec,1,6)
+#' factorData= managers.df[,c("EDHEC.LS.EQ","SP500.TR")]
+#' Beta.mat=fit$beta
+#' residualData=as.matrix(fit$resid.variance,1,6)
#' n.boot=1000
#' # bootstrap returns data from factor model with residuals sample from normal distribution
#' bootData <- factorModelMonteCarlo(n.boot, factorData,Beta.mat, residual.dist="normal",
Modified: pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -21,13 +21,13 @@
#' wls = TRUE, regression = "classic",
#' covariance = "classic", full.resid.cov = FALSE)
#' # If not specify anything, predict() will give fitted value
-#' predict(fit.fund)
+#' pred.fund <- predict(fit.fund)
#'
#' # generate random data
-#' testdata <- data[,c("DATE","TICKER")]
+#' testdata <- stock[,c("DATE","TICKER")]
#' testdata$BOOK2MARKET <- rnorm(n=42465)
#' testdata$LOG.MARKETCAP <- rnorm(n=42465)
-#' predict(fit.fund,testdata,new.assetvar="TICKER",new.datevar="DATE")
+#' pred.fund2 <- predict(fit.fund,testdata,new.assetvar="TICKER",new.datevar="DATE")
#'
#'
predict.FundamentalFactorModel <- function(object,newdata,new.assetvar,new.datevar){
Modified: pkg/FactorAnalytics/R/predict.StatFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/predict.StatFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/predict.StatFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -7,16 +7,13 @@
#' @param newdata a vector, matrix, data.frame, xts, timeSeries or zoo object to be coerced.
#' @param ... Any other arguments used in \code{predict.lm}. For example like newdata and fit.se.
#' @author Yi-An Chen.
-#' '
+#' @method predict StatFactorModel
+#' @export
#' @examples
#' data(stat.fm.data)
-#'.fit <- fitStatisticalFactorModel(sfm.dat,k=2,
-# ckeckData.method="data.frame")
+#' fit <- fitStatisticalFactorModel(sfm.dat,k=2)
+#' pred.stat <- predict(fit)
#'
-#' predict(fit)
-#' @method predict StatFactorModel
-#' @export
-#'
predict.StatFactorModel <- function(object,newdata = NULL,...){
Modified: pkg/FactorAnalytics/R/predict.TimeSeriesFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/predict.TimeSeriesFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/predict.TimeSeriesFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -14,12 +14,14 @@
#' data(managers.df)
#' ret.assets = managers.df[,(1:6)]
#' # fit the factor model with OLS
-#' fit <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+#' fit <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
#' factors.names=c("EDHEC.LS.EQ","SP500.TR"),
#' data=managers.df,fit.method="OLS")
#'
-#' predict(fit)
-#' predict(fit,newdata,interval="confidence")
+#' pred.fit <- predict(fit)
+#' newdata <- data.frame(EDHEC.LS.EQ = rnorm(n=120), SP500.TR = rnorm(n=120) )
+#' rownames(newdata) <- rownames(fit$data)
+#' pred.fit2 <- predict(fit,newdata,interval="confidence")
#'
#' @method predict TimeSeriesFactorModel
#' @export
Modified: pkg/FactorAnalytics/R/print.FundamentalFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/print.FundamentalFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/print.FundamentalFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -7,12 +7,14 @@
#' @param digits integer indicating the number of decimal places. Default is 3.
#' @param ... Other arguments for print methods.
#' @author Yi-An Chen.
+#' @method print FundamentalFactorModel
+#' @export
#' @examples
#'
#' data(Stock.df)
#' # there are 447 assets
#' exposure.names <- c("BOOK2MARKET", "LOG.MARKETCAP")
-#' test.fit <- fitFundamentalFactorModel(data=data,exposure.names=exposure.names,
+#' test.fit <- fitFundamentalFactorModel(data=stock,exposure.names=exposure.names,
#' datevar = "DATE", returnsvar = "RETURN",
#' assetvar = "TICKER", wls = TRUE,
#' regression = "classic",
@@ -20,8 +22,7 @@
#' robust.scale = TRUE)
#'
#' print(test.fit)
-#' @method print FundamentalFactorModel
-#' @export
+#'
print.FundamentalFactorModel <-
function(x, digits = max(3, .Options$digits - 3), ...)
{
Modified: pkg/FactorAnalytics/R/print.TimeSeriesFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/print.TimeSeriesFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/print.TimeSeriesFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -7,16 +7,17 @@
#' @param digits integer indicating the number of decimal places. Default is 3.
#' @param ... arguments to be passed to print method.
#' @author Yi-An Chen.
+#' @method print TimeSeriesFactorModel
+#' @export
#' @examples
#'
#' # load data from the database
#' data(managers.df)
-#' fit.macro <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+#' fit.macro <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
#' factors.names=c("EDHEC.LS.EQ","SP500.TR"),
#' data=managers.df,fit.method="OLS")
#' print(fit.macro)
-#' @method print TimeSeriesFactorModel
-#' @export
+#'
print.TimeSeriesFactorModel <- function(x,digits=max(3, .Options$digits - 3),...){
if(!is.null(cl <- x$call)) {
cat("\nCall:\n")
Modified: pkg/FactorAnalytics/R/summary.FundamentalFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/summary.FundamentalFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/summary.FundamentalFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -7,12 +7,14 @@
#' @param digits integer indicating the number of decimal places. Default is 3.
#' @param ... Other arguments for print methods.
#' @author Yi-An Chen.
+#' @method summary FundamentalFactorModel
+#' @export
#' @examples
#'
#' data(Stock.df)
#' # there are 447 assets
#' exposure.names <- c("BOOK2MARKET", "LOG.MARKETCAP")
-#' test.fit <- fitFundamentalFactorModel(data=data,exposure.names=exposure.names,
+#' test.fit <- fitFundamentalFactorModel(data=stock,exposure.names=exposure.names,
#' datevar = "DATE", returnsvar = "RETURN",
#' assetvar = "TICKER", wls = TRUE,
#' regression = "classic",
@@ -20,8 +22,7 @@
#' robust.scale = TRUE)
#'
#' summary(test.fit)
-#' @method summary FundamentalFactorModel
-#' @export
+#'
summary.FundamentalFactorModel <-
function(object, digits = max(3, .Options$digits - 3), ...)
{
Modified: pkg/FactorAnalytics/R/summary.StatFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/summary.StatFactorModel.r 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/R/summary.StatFactorModel.r 2013-08-05 20:34:55 UTC (rev 2724)
@@ -7,17 +7,17 @@
#' @param digits Integer indicating the number of decimal places. Default is 3.
#' @param ... other option used in \code{summary.lm}
#' @author Yi-An Chen.
+#' @method summary StatFactorModel
+#' @export
#' @examples
#'
#' # load data from the database
-#' data(managers.df)
+#' data(stat.fm.data)
#' # fit the factor model with OLS
-#' fit <- fitStatisticalFactorModel(fitStatisticalFactorModel(sfm.dat,k=2,
-#' ckeckData.method="data.frame"))
+#' fit <- fitStatisticalFactorModel(sfm.dat,k=2)
#' summary(fit)
-#' @method summary StatFactorModel
-#' @export
#'
+#'
summary.StatFactorModel <- function(object,digits=3){
if(!is.null(cl <- object$call)) {
cat("\nCall:\n")
Modified: pkg/FactorAnalytics/man/Stock.df.Rd
===================================================================
--- pkg/FactorAnalytics/man/Stock.df.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/Stock.df.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -1,7 +1,6 @@
\docType{data}
\name{Stock.df}
\alias{Stock.df}
-\alias{stock}
\title{constructed NYSE 447 assets from 1996-01-01 through 2003-12-31.}
\description{
constructed NYSE 447 assets from 1996-01-01 through
Modified: pkg/FactorAnalytics/man/factorModelMonteCarlo.Rd
===================================================================
--- pkg/FactorAnalytics/man/factorModelMonteCarlo.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/factorModelMonteCarlo.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -79,12 +79,12 @@
\examples{
# load data from the database
data(managers.df)
-fit <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+fit <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
factors.names=c("EDHEC.LS.EQ","SP500.TR"),
data=managers.df,fit.method="OLS")
-factorData=factors
-Beta.mat=fit$beta.mat
-residualData=as.matrix(fit$residVars.vec,1,6)
+factorData= managers.df[,c("EDHEC.LS.EQ","SP500.TR")]
+Beta.mat=fit$beta
+residualData=as.matrix(fit$resid.variance,1,6)
n.boot=1000
# bootstrap returns data from factor model with residuals sample from normal distribution
bootData <- factorModelMonteCarlo(n.boot, factorData,Beta.mat, residual.dist="normal",
Modified: pkg/FactorAnalytics/man/fitTimeseriesFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/fitTimeseriesFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/fitTimeseriesFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -105,7 +105,7 @@
\dontrun{
# load data from the database
data(managers.df)
-fit <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+fit <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
factors.names=c("EDHEC.LS.EQ","SP500.TR"),
data=managers.df,fit.method="OLS")
# summary of HAM1
Modified: pkg/FactorAnalytics/man/predict.FundamentalFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/predict.FundamentalFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/predict.FundamentalFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -35,13 +35,13 @@
wls = TRUE, regression = "classic",
covariance = "classic", full.resid.cov = FALSE)
# If not specify anything, predict() will give fitted value
-predict(fit.fund)
+pred.fund <- predict(fit.fund)
# generate random data
-testdata <- data[,c("DATE","TICKER")]
+testdata <- stock[,c("DATE","TICKER")]
testdata$BOOK2MARKET <- rnorm(n=42465)
testdata$LOG.MARKETCAP <- rnorm(n=42465)
-predict(fit.fund,testdata,new.assetvar="TICKER",new.datevar="DATE")
+pred.fund2 <- predict(fit.fund,testdata,new.assetvar="TICKER",new.datevar="DATE")
}
\author{
Yi-An Chen
Modified: pkg/FactorAnalytics/man/predict.StatFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/predict.StatFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/predict.StatFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -22,11 +22,10 @@
}
\examples{
data(stat.fm.data)
-.fit <- fitStatisticalFactorModel(sfm.dat,k=2,
-
-predict(fit)
+fit <- fitStatisticalFactorModel(sfm.dat,k=2)
+pred.stat <- predict(fit)
}
\author{
- Yi-An Chen. '
+ Yi-An Chen.
}
Modified: pkg/FactorAnalytics/man/predict.TimeSeriesFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/predict.TimeSeriesFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/predict.TimeSeriesFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -25,12 +25,14 @@
data(managers.df)
ret.assets = managers.df[,(1:6)]
# fit the factor model with OLS
-fit <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+fit <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
factors.names=c("EDHEC.LS.EQ","SP500.TR"),
data=managers.df,fit.method="OLS")
-predict(fit)
-predict(fit,newdata,interval="confidence")
+pred.fit <- predict(fit)
+newdata <- data.frame(EDHEC.LS.EQ = rnorm(n=120), SP500.TR = rnorm(n=120) )
+rownames(newdata) <- rownames(fit$data)
+pred.fit2 <- predict(fit,newdata,interval="confidence")
}
\author{
Yi-An Chen.
Modified: pkg/FactorAnalytics/man/print.FundamentalFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/print.FundamentalFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/print.FundamentalFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -22,7 +22,7 @@
data(Stock.df)
# there are 447 assets
exposure.names <- c("BOOK2MARKET", "LOG.MARKETCAP")
-test.fit <- fitFundamentalFactorModel(data=data,exposure.names=exposure.names,
+test.fit <- fitFundamentalFactorModel(data=stock,exposure.names=exposure.names,
datevar = "DATE", returnsvar = "RETURN",
assetvar = "TICKER", wls = TRUE,
regression = "classic",
Modified: pkg/FactorAnalytics/man/print.TimeSeriesFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/print.TimeSeriesFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/print.TimeSeriesFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -20,7 +20,7 @@
\examples{
# load data from the database
data(managers.df)
-fit.macro <- fitTimeseriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
+fit.macro <- fitTimeSeriesFactorModel(assets.names=colnames(managers.df[,(1:6)]),
factors.names=c("EDHEC.LS.EQ","SP500.TR"),
data=managers.df,fit.method="OLS")
print(fit.macro)
Modified: pkg/FactorAnalytics/man/summary.FundamentalFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/summary.FundamentalFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/summary.FundamentalFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -22,7 +22,7 @@
data(Stock.df)
# there are 447 assets
exposure.names <- c("BOOK2MARKET", "LOG.MARKETCAP")
-test.fit <- fitFundamentalFactorModel(data=data,exposure.names=exposure.names,
+test.fit <- fitFundamentalFactorModel(data=stock,exposure.names=exposure.names,
datevar = "DATE", returnsvar = "RETURN",
assetvar = "TICKER", wls = TRUE,
regression = "classic",
Modified: pkg/FactorAnalytics/man/summary.StatFactorModel.Rd
===================================================================
--- pkg/FactorAnalytics/man/summary.StatFactorModel.Rd 2013-08-05 19:22:22 UTC (rev 2723)
+++ pkg/FactorAnalytics/man/summary.StatFactorModel.Rd 2013-08-05 20:34:55 UTC (rev 2724)
@@ -19,10 +19,9 @@
}
\examples{
# load data from the database
-data(managers.df)
+data(stat.fm.data)
# fit the factor model with OLS
-fit <- fitStatisticalFactorModel(fitStatisticalFactorModel(sfm.dat,k=2,
- ckeckData.method="data.frame"))
+fit <- fitStatisticalFactorModel(sfm.dat,k=2)
summary(fit)
}
\author{
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