repExposures: Portfolio Exposures Report

In AvinashAcharya/Test_factorAnalytics: Development of factorAnalytics package as a part of GSoC-2016

Description

Calculate k factor time series based on fundamental factor model. This method takes fundamental factor model fit, "ffm" object, and portfolio weight as inputs and generates numeric summary and plot visualization.

Usage

repExposures(ffmObj, weights = NULL, isPlot = TRUE, isPrint = TRUE,
  scaleType = "free", stripLeft = TRUE, layout = NULL, digits = 1,
  titleText = TRUE, which = NULL, ...)

Arguments

ffmObj	an object of class ffm returned by fitFfm.
weights	a vector of weights of the assets in the portfolio. Default is NULL.
isPlot	logical variable to generate plot or not.
isPrint	logical variable to print numeric summary or not.
scaleType	scaleType controls if use a same scale of y-axis, choose from c('same', 'free')
stripLeft	logical variable to choose the position of strip, "TRUE" for drawing strips on the left of each panel, "FALSE" for drawing strips on the top of each panel. Used only when isPlot = 'TRUE'
layout	layout is a numeric vector of length 2 or 3 giving the number of columns, rows, and pages (optional) in a multipanel display. Used only when isPlot = 'TRUE'
digits	digits of printout numeric summary. Used only when isPrint = 'TRUE'
titleText	logical varible to choose display plot title or not. Default is 'TRUE', and used only when isPlot = 'TRUE'.
which	a number to indicate the type of plot. If a subset of the plots is required, specify a subset of the numbers 1:3 for plots. If which=NULL (default), the following menu appears: For plots of a group of assets: 1 = Time series plot of style factor exposures, 2 = Boxplot of style factor exposures, 3 = Barplot of means and vols of style factor exposures, and means of sector exposures (which have no vol).
...	other graphics parameters available in tsPlotMP(time series plot only) can be passed in through the ellipses

Value

A K x 2 matrix containing mean and standard deviation of K factors

Author(s)

Douglas Martin, Lingjie Yi

Examples

#Load fundamental and return data 
data("stocks145scores6")
dat = stocks145scores6
dat$DATE = as.yearmon(dat$DATE)
dat = dat[dat$DATE >=as.yearmon("2008-01-01") & dat$DATE <= as.yearmon("2012-12-31"),]

#Load long-only GMV weights for the return data
data("wtsStocks145GmvLo")
wtsStocks145GmvLo = round(wtsStocks145GmvLo,5)  

# fit a fundamental factor model
fit.cross <- fitFfm(data = dat, 
              exposure.vars = c("SECTOR","ROE","BP","MOM121","SIZE","VOL121",
              "EP"),date.var = "DATE", ret.var = "RETURN", asset.var = "TICKER", 
              fit.method="WLS", z.score = TRUE)

repExposures(fit.cross, wtsStocks145GmvLo, isPlot = FALSE, digits = 4)
repExposures(fit.cross, wtsStocks145GmvLo, isPrint = FALSE, isPlot = TRUE, which = 2,
             add.grid = TRUE, scaleType = 'same')
repExposures(fit.cross, wtsStocks145GmvLo, isPlot = TRUE, which = 1,
             add.grid = FALSE, zeroLine = TRUE, color = 'Blue')
repExposures(fit.cross, wtsStocks145GmvLo, isPrint = FALSE, isPlot = TRUE, which = 3,
             add.grid = FALSE, zeroLine = FALSE, color = 'Blue', layout = c(1,3))

AvinashAcharya/Test_factorAnalytics documentation built on May 5, 2019, 9:22 a.m.