From noreply at r-forge.r-project.org  Fri May  6 16:14:25 2016
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Fri,  6 May 2016 16:14:25 +0200 (CEST)
Subject: [Returnanalytics-commits] r4019 - pkg/FactorAnalytics/R
Message-ID: <20160506141425.A590E187696@r-forge.r-project.org>

Author: pragnya
Date: 2016-05-06 16:14:25 +0200 (Fri, 06 May 2016)
New Revision: 4019

Modified:
   pkg/FactorAnalytics/R/fitFfm.R
Log:
Fixed typo in fitted.ffm

Modified: pkg/FactorAnalytics/R/fitFfm.R
===================================================================
--- pkg/FactorAnalytics/R/fitFfm.R	2016-04-29 17:21:48 UTC (rev 4018)
+++ pkg/FactorAnalytics/R/fitFfm.R	2016-05-06 14:14:25 UTC (rev 4019)
@@ -408,7 +408,7 @@
 fitted.ffm <- function(object, ...) {  
   # get fitted values for all assets in each time period
   # transpose and convert into xts/zoo objects
-  fitted.xts <- checkData(t(sapply(object$asset.fit, fitted)))
+  fitted.xts <- checkData(t(sapply(object$factor.fit, fitted)))
   names(fitted.xts) <- object$asset.names
   return(fitted.xts)
 }


From noreply at r-forge.r-project.org  Mon May  9 11:00:27 2016
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Mon,  9 May 2016 11:00:27 +0200 (CEST)
Subject: [Returnanalytics-commits] r4020 - in pkg/FactorAnalytics: . R
Message-ID: <20160509090027.4250E1877F7@r-forge.r-project.org>

Author: pragnya
Date: 2016-05-09 11:00:26 +0200 (Mon, 09 May 2016)
New Revision: 4020

Modified:
   pkg/FactorAnalytics/DESCRIPTION
   pkg/FactorAnalytics/R/fitFfm.R
Log:
Renamed zScore function in fitFfm

Modified: pkg/FactorAnalytics/DESCRIPTION
===================================================================
--- pkg/FactorAnalytics/DESCRIPTION	2016-05-06 14:14:25 UTC (rev 4019)
+++ pkg/FactorAnalytics/DESCRIPTION	2016-05-09 09:00:26 UTC (rev 4020)
@@ -1,8 +1,8 @@
 Package: factorAnalytics
 Type: Package
 Title: Factor Analytics
-Version: 2.0.30
-Date: 2016-03-17
+Version: 2.0.31
+Date: 2016-05-09
 Author: Eric Zivot, Sangeetha Srinivasan and Yi-An Chen
 Maintainer: Sangeetha Srinivasan <sangee at uw.edu>
 Description: Linear factor model fitting for asset returns (three major types-

Modified: pkg/FactorAnalytics/R/fitFfm.R
===================================================================
--- pkg/FactorAnalytics/R/fitFfm.R	2016-05-06 14:14:25 UTC (rev 4019)
+++ pkg/FactorAnalytics/R/fitFfm.R	2016-05-09 09:00:26 UTC (rev 4020)
@@ -231,7 +231,7 @@
     }
     # calculate z-scores looping through all numeric exposures
     for (i in exposures.num) {
-      std.expo.num <- by(data=data, INDICES=data[[date.var]], FUN=z.score,
+      std.expo.num <- by(data=data, INDICES=data[[date.var]], FUN=zScore,
                          i=i, w=w, rob.stats=rob.stats)
       data[[i]] <- unlist(std.expo.num)
     }
@@ -375,7 +375,7 @@
 ## x is a data.frame object, i is a character string and w has same length as x 
 # rob.stats is a logical argument to compute robust location and scale
 
-z.score <- function (x, i, w, rob.stats) {
+zScore <- function (x, i, w, rob.stats) {
   if (rob.stats) {
     x_bar <- median(w*x[[i]])
     (x[[i]] - x_bar)/mad(x[[i]], center=x_bar)


From noreply at r-forge.r-project.org  Mon May  9 14:31:39 2016
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Mon,  9 May 2016 14:31:39 +0200 (CEST)
Subject: [Returnanalytics-commits] r4021 - in pkg/FactorAnalytics: . R man
Message-ID: <20160509123139.BE90A188168@r-forge.r-project.org>

Author: pragnya
Date: 2016-05-09 14:31:39 +0200 (Mon, 09 May 2016)
New Revision: 4021

Added:
   pkg/FactorAnalytics/R/predict.ffm.R
   pkg/FactorAnalytics/man/predict.ffm.Rd
Modified:
   pkg/FactorAnalytics/NAMESPACE
   pkg/FactorAnalytics/R/predict.tsfm.r
   pkg/FactorAnalytics/man/predict.tsfm.Rd
Log:
Updated predict methods for fitFfm and fitTsfm

Modified: pkg/FactorAnalytics/NAMESPACE
===================================================================
--- pkg/FactorAnalytics/NAMESPACE	2016-05-09 09:00:26 UTC (rev 4020)
+++ pkg/FactorAnalytics/NAMESPACE	2016-05-09 12:31:39 UTC (rev 4021)
@@ -21,6 +21,7 @@
 S3method(plot,sfm)
 S3method(plot,tsfm)
 S3method(plot,tsfmUpDn)
+S3method(predict,ffm)
 S3method(predict,sfm)
 S3method(predict,tsfm)
 S3method(predict,tsfmUpDn)

Added: pkg/FactorAnalytics/R/predict.ffm.R
===================================================================
--- pkg/FactorAnalytics/R/predict.ffm.R	                        (rev 0)
+++ pkg/FactorAnalytics/R/predict.ffm.R	2016-05-09 12:31:39 UTC (rev 4021)
@@ -0,0 +1,67 @@
+#' @title Predicts asset returns based on a fitted fundamental factor model
+#' 
+#' @description S3 \code{predict} method for object of class \code{ffm}.
+#' 
+#' @details The estimated factor returns and potentially new factor exposures 
+#' are used to predict the asset returns during all dates from the fitted 
+#' \code{ffm} object. For predictions based on estimated factor returns from a 
+#' specific period use the \code{pred.date} argument.
+#' 
+#' @param object an object of class \code{ffm} produced by \code{fitFfm}.
+#' @param newdata data.frame containing the variables \code{asset.var}, 
+#' \code{date.var} and the same exact \code{exposure.vars} used in the fitted
+#' \code{ffm} object. If omitted, the predictions are based on the data used 
+#' for the fit.
+#' @param pred.date character; unique date used to base the predictions. Should 
+#' be coercible to class \code{Date} and match one of the dates in the data used
+#' in the fiited \code{object}.
+#' @param ... optional arguments passed to \code{predict.lm} or 
+#' \code{predict.lmRob}.
+#' 
+#' @return 
+#' \code{predict.ffm} produces a N x T matrix of predicted asset returns, where 
+#' T is the number of time periods and N is the number of assets. T=1 if 
+#' \code{pred.date} is specified.
+#' 
+#' @author Sangeetha Srinivasan
+#' 
+#' @seealso \code{\link{fitFfm}}, \code{\link{summary.ffm}}, 
+#' \code{\link[stats]{predict.lm}}, \code{\link[robust]{predict.lmRob}}
+#' 
+#' @examples
+#' 
+#' # Load fundamental and return data
+#' data(Stock.df)
+#' 
+#' # fit a fundamental factor model
+#' exposure.vars <- c("BOOK2MARKET", "LOG.MARKETCAP")
+#' fit <- fitFfm(data=stock, asset.var="TICKER", ret.var="RETURN", 
+#'               date.var="DATE", exposure.vars=exposure.vars)
+#' 
+#' # generate random data
+#' newdata <- as.data.frame(unique(stock$TICKER))
+#' newdata$BOOK2MARKET <- rnorm(nrow(newdata))
+#' newdata$LOG.MARKETCAP <- rnorm(nrow(newdata))
+#' pred.fund <- predict(fit, newdata)
+#' 
+#' @method predict ffm
+#' @export
+#' 
+
+predict.ffm <- function(object, newdata=NULL, pred.date=NULL, ...){
+  
+  if (!is.null(pred.date) && !(pred.date %in% names(object$factor.fit))) {
+    stop("Invalid args: pred.date must be a character string that matches one 
+         of the dates used in the fit")
+  }
+  
+  if (!is.null(newdata)) {
+    newdata <- checkData(newdata, method="data.frame")
+  }
+  
+  if (!is.null(pred.date)) {
+    as.matrix(predict(object$factor.fit[[pred.date]], newdata, ...))
+  } else {
+    sapply(object$factor.fit, predict, newdata, ...)
+  }
+}

Modified: pkg/FactorAnalytics/R/predict.tsfm.r
===================================================================
--- pkg/FactorAnalytics/R/predict.tsfm.r	2016-05-09 09:00:26 UTC (rev 4020)
+++ pkg/FactorAnalytics/R/predict.tsfm.r	2016-05-09 12:31:39 UTC (rev 4021)
@@ -12,7 +12,9 @@
 #' \code{\link[lars]{predict.lars}} such as \code{mode}.
 #' 
 #' @return 
-#' \code{predict.tsfm} produces a vector or a matrix of predictions.
+#' \code{predict.tsfm} produces a matrix of return predictions, if all assets 
+#' have equal history. If not, a list of predicted return vectors of unequal 
+#' length is produced.
 #' 
 #' @author Yi-An Chen and Sangeetha Srinivasan
 #' 
@@ -34,12 +36,10 @@
 #' @export
 #' 
 
-predict.tsfm <- function(object, newdata = NULL, ...){
+predict.tsfm <- function(object, newdata=NULL, ...){
   
   if (missing(newdata) || is.null(newdata)) {
-    lapply(object$asset.fit, predict, ...)
-  } else {
-    newdata <- checkData(newdata, method = "data.frame")
-    lapply(object$asset.fit, predict, newdata, ...)
-  } 
+    newdata <- checkData(newdata, method="data.frame")
+  }
+  sapply(object$asset.fit, predict, newdata, ...)
 }

Added: pkg/FactorAnalytics/man/predict.ffm.Rd
===================================================================
--- pkg/FactorAnalytics/man/predict.ffm.Rd	                        (rev 0)
+++ pkg/FactorAnalytics/man/predict.ffm.Rd	2016-05-09 12:31:39 UTC (rev 4021)
@@ -0,0 +1,62 @@
+% Generated by roxygen2: do not edit by hand
+% Please edit documentation in R/predict.ffm.R
+\name{predict.ffm}
+\alias{predict.ffm}
+\title{Predicts asset returns based on a fitted fundamental factor model}
+\usage{
+\method{predict}{ffm}(object, newdata = NULL, pred.date = NULL, ...)
+}
+\arguments{
+\item{object}{an object of class \code{ffm} produced by \code{fitFfm}.}
+
+\item{newdata}{data.frame containing the variables \code{asset.var}, 
+\code{date.var} and the same exact \code{exposure.vars} used in the fitted
+\code{ffm} object. If omitted, the predictions are based on the data used 
+for the fit.}
+
+\item{pred.date}{character; unique date used to base the predictions. Should 
+be coercible to class \code{Date} and match one of the dates in the data used
+in the fiited \code{object}.}
+
+\item{...}{optional arguments passed to \code{predict.lm} or 
+\code{predict.lmRob}.}
+}
+\value{
+\code{predict.ffm} produces a N x T matrix of predicted asset returns, where 
+T is the number of time periods and N is the number of assets. T=1 if 
+\code{pred.date} is specified.
+}
+\description{
+S3 \code{predict} method for object of class \code{ffm}.
+}
+\details{
+The estimated factor returns and potentially new factor exposures 
+are used to predict the asset returns during all dates from the fitted 
+\code{ffm} object. For predictions based on estimated factor returns from a 
+specific period use the \code{pred.date} argument.
+}
+\examples{
+
+# Load fundamental and return data
+data(Stock.df)
+
+# fit a fundamental factor model
+exposure.vars <- c("BOOK2MARKET", "LOG.MARKETCAP")
+fit <- fitFfm(data=stock, asset.var="TICKER", ret.var="RETURN", 
+              date.var="DATE", exposure.vars=exposure.vars)
+
+# generate random data
+newdata <- as.data.frame(unique(stock$TICKER))
+newdata$BOOK2MARKET <- rnorm(nrow(newdata))
+newdata$LOG.MARKETCAP <- rnorm(nrow(newdata))
+pred.fund <- predict(fit, newdata)
+
+}
+\author{
+Sangeetha Srinivasan
+}
+\seealso{
+\code{\link{fitFfm}}, \code{\link{summary.ffm}}, 
+\code{\link[stats]{predict.lm}}, \code{\link[robust]{predict.lmRob}}
+}
+

Modified: pkg/FactorAnalytics/man/predict.tsfm.Rd
===================================================================
--- pkg/FactorAnalytics/man/predict.tsfm.Rd	2016-05-09 09:00:26 UTC (rev 4020)
+++ pkg/FactorAnalytics/man/predict.tsfm.Rd	2016-05-09 12:31:39 UTC (rev 4021)
@@ -17,7 +17,9 @@
 \code{\link[lars]{predict.lars}} such as \code{mode}.}
 }
 \value{
-\code{predict.tsfm} produces a vector or a matrix of predictions.
+\code{predict.tsfm} produces a matrix of return predictions, if all assets 
+have equal history. If not, a list of predicted return vectors of unequal 
+length is produced.
 }
 \description{
 S3 \code{predict} method for object of class \code{tsfm}. It 


From noreply at r-forge.r-project.org  Wed May 11 02:46:53 2016
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Wed, 11 May 2016 02:46:53 +0200 (CEST)
Subject: [Returnanalytics-commits] r4022 - in pkg/FactorAnalytics: . R
Message-ID: <20160511004653.339C71800AD@r-forge.r-project.org>

Author: pragnya
Date: 2016-05-11 02:46:52 +0200 (Wed, 11 May 2016)
New Revision: 4022

Modified:
   pkg/FactorAnalytics/DESCRIPTION
   pkg/FactorAnalytics/R/predict.ffm.R
   pkg/FactorAnalytics/R/predict.tsfm.r
Log:
Fixed bug in predict methods

Modified: pkg/FactorAnalytics/DESCRIPTION
===================================================================
--- pkg/FactorAnalytics/DESCRIPTION	2016-05-09 12:31:39 UTC (rev 4021)
+++ pkg/FactorAnalytics/DESCRIPTION	2016-05-11 00:46:52 UTC (rev 4022)
@@ -1,8 +1,8 @@
 Package: factorAnalytics
 Type: Package
 Title: Factor Analytics
-Version: 2.0.31
-Date: 2016-05-09
+Version: 2.0.32
+Date: 2016-05-10
 Author: Eric Zivot, Sangeetha Srinivasan and Yi-An Chen
 Maintainer: Sangeetha Srinivasan <sangee at uw.edu>
 Description: Linear factor model fitting for asset returns (three major types-

Modified: pkg/FactorAnalytics/R/predict.ffm.R
===================================================================
--- pkg/FactorAnalytics/R/predict.ffm.R	2016-05-09 12:31:39 UTC (rev 4021)
+++ pkg/FactorAnalytics/R/predict.ffm.R	2016-05-11 00:46:52 UTC (rev 4022)
@@ -55,13 +55,14 @@
          of the dates used in the fit")
   }
   
-  if (!is.null(newdata)) {
+  if (is.null(newdata)) {
+    sapply(object$factor.fit, predict, ...)
+  } else {
     newdata <- checkData(newdata, method="data.frame")
+    if (is.null(pred.date)) {
+      sapply(object$factor.fit, predict, newdata, ...)
+    } else {
+      as.matrix(predict(object$factor.fit[[pred.date]], newdata, ...))
+    }
   }
-  
-  if (!is.null(pred.date)) {
-    as.matrix(predict(object$factor.fit[[pred.date]], newdata, ...))
-  } else {
-    sapply(object$factor.fit, predict, newdata, ...)
-  }
 }

Modified: pkg/FactorAnalytics/R/predict.tsfm.r
===================================================================
--- pkg/FactorAnalytics/R/predict.tsfm.r	2016-05-09 12:31:39 UTC (rev 4021)
+++ pkg/FactorAnalytics/R/predict.tsfm.r	2016-05-11 00:46:52 UTC (rev 4022)
@@ -38,8 +38,10 @@
 
 predict.tsfm <- function(object, newdata=NULL, ...){
   
-  if (missing(newdata) || is.null(newdata)) {
+  if (is.null(newdata)) {
+    sapply(object$asset.fit, predict, ...)
+  } else {
     newdata <- checkData(newdata, method="data.frame")
+    sapply(object$asset.fit, predict, newdata, ...)
   }
-  sapply(object$asset.fit, predict, newdata, ...)
 }


From noreply at r-forge.r-project.org  Mon May 23 16:17:41 2016
From: noreply at r-forge.r-project.org (noreply at r-forge.r-project.org)
Date: Mon, 23 May 2016 16:17:41 +0200 (CEST)
Subject: [Returnanalytics-commits] r4023 - in pkg/FactorAnalytics: . R
Message-ID: <20160523141741.9BC84183B48@r-forge.r-project.org>

Author: pragnya
Date: 2016-05-23 16:17:41 +0200 (Mon, 23 May 2016)
New Revision: 4023

Modified:
   pkg/FactorAnalytics/DESCRIPTION
   pkg/FactorAnalytics/R/fitFfm.R
Log:
Fixed bug in z.score functionality in fitFfm

Modified: pkg/FactorAnalytics/DESCRIPTION
===================================================================
--- pkg/FactorAnalytics/DESCRIPTION	2016-05-11 00:46:52 UTC (rev 4022)
+++ pkg/FactorAnalytics/DESCRIPTION	2016-05-23 14:17:41 UTC (rev 4023)
@@ -1,8 +1,8 @@
 Package: factorAnalytics
 Type: Package
 Title: Factor Analytics
-Version: 2.0.32
-Date: 2016-05-10
+Version: 2.0.33
+Date: 2016-05-23
 Author: Eric Zivot, Sangeetha Srinivasan and Yi-An Chen
 Maintainer: Sangeetha Srinivasan <sangee at uw.edu>
 Description: Linear factor model fitting for asset returns (three major types-

Modified: pkg/FactorAnalytics/R/fitFfm.R
===================================================================
--- pkg/FactorAnalytics/R/fitFfm.R	2016-05-11 00:46:52 UTC (rev 4022)
+++ pkg/FactorAnalytics/R/fitFfm.R	2016-05-23 14:17:41 UTC (rev 4023)
@@ -383,7 +383,7 @@
     x_bar <- mean(w*x[[i]]) 
     n <- length(x[[i]])
     # use equal weighted squared deviation about the weighted mean
-    (x[[i]] - x_bar)/sqrt((x[[i]]-x_bar)^2/(n-1))
+    (x[[i]] - x_bar)/sqrt(sum((x[[i]]-x_bar)^2)/(n-1))
   }
 }