fmTstats | R Documentation |
Calculate and plot the time series of t-statistic values and the
number of risk indices with significant t-stats for a fundamental factor
model of class ffm
produced by fitFfm
or fitFfmDT
fmTstats(ffmObj, ...)
## S3 method for class 'ffm'
fmTstats(
ffmObj,
isPlot = TRUE,
isPrint = FALSE,
whichPlot = "tStats",
color = c("black", "cyan"),
lwd = 2,
digits = 2,
z.alpha = 1.96,
layout = c(2, 3),
type = "h",
scale = "free",
stripText.cex = 1,
axis.cex = 1,
title = TRUE,
...
)
ffmObj |
an object of class |
... |
potentially further arguments passed. |
isPlot |
logical. If |
isPrint |
logical. if |
whichPlot |
string indicating the plot(s) to be plotted. Choose from
("all", "tStats", "significantTstatsV", "significantTstatsH", "significantTstatsLikert").
Three variants of significantTstats stand for vertical, horizontal and likert barplots.
Default is |
color |
length 2 vector specifying the plotting color for t-stats plot
and for barplot respectively. default is |
lwd |
line width relative to the default. default is 2. |
digits |
an integer indicating the number of decimal places to be used for rounding. default is 2. |
z.alpha |
critical value corresponding to the confidence interval. Default is 1.96 i.e 95% C.I |
layout |
numeric vector of length 2 or 3 giving the number of columns, rows, and pages (optional) in the xyplot of t-statistics. default is c(2,3). |
type |
type character. Type of the xyplot of t-statistics; |
scale |
character. It determines how axis limits are calculated for each panel. Possible values are "same" , "free" (default) and "sliced". |
stripText.cex |
a number indicating the amount by which strip text in the plot(s) should be scaled relative to the default. 1=default, 1.5 is 50% larger, 0.5 is 50% smaller, etc. |
axis.cex |
a number indicating the amount by which axis in the plot(s) should be scaled relative to the default. Default = 1. 1.5 is 50% larger, 0.5 is 50% smaller, etc. |
title |
logical. if |
fmTstats
plots the t-stats and significant t-stats values
if isPlot
is TRUE
and returns a list with following components:
tstats |
an xts object of t-stats values. |
z.alpha |
critical value corresponding to the confidence interval. |
Avinash Acharya and Doug Martin
data("factorDataSetDjia5Yrs")
#Fit a Ffm with style factors only
fit <- fitFfm(data = factorDataSetDjia5Yrs,
exposure.vars = c("MKTCAP","ENTVAL","P2B","EV2S"),
date.var = "DATE",
ret.var = "RETURN",
asset.var = "TICKER",
fit.method = "WLS",
z.score = "crossSection")
#Compute time series of t-stats and number of significant t-stats
stats = fmTstats(fit, isPlot = TRUE, lwd = 2, color = c("blue", "blue"),
z.alpha = 1.96)
fit1 <- fitFfm(data = factorDataSetDjia5Yrs, asset.var = "TICKER",
exposure.vars = c("SECTOR","MKTCAP","ENTVAL","P2B"),
ret.var = "RETURN",
date.var = "DATE",
addIntercept = TRUE)
#Compute time series of t-stats and number of significant t-stats
stats = fmTstats(fit1, isPlot = TRUE, z.alpha = 1.96)
# Fit a SECTOR+COUNTRY+Style model with Intercept
# Create a COUNTRY column with just 3 countries
#
# factorDataSetDjia5Yrs$COUNTRY = rep(rep(c(rep("US", 1 ), rep("GERMANY", 1 )), 11), 60)
#
# fit.MICM <- fitFfm(data = factorDataSetDjia5Yrs,
# asset.var = "TICKER",
# exposure.vars = c("SECTOR", "COUNTRY","P2B", "MKTCAP"),
# ret.var = "RETURN",
# date.var = "DATE",
# addIntercept = FALSE)
#
# Load library 'HH' to access the Likert option
# library("HH")
# stats = fmTstats(fit.MICM, isPlot = TRUE, z.alpha =1.96,
# whichPlot = "significantTstatsLikert")
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