[Returnanalytics-commits] r2669 - pkg/FactorAnalytics/R
noreply at r-forge.r-project.org
noreply at r-forge.r-project.org
Mon Jul 29 18:52:01 CEST 2013
Author: chenyian
Date: 2013-07-29 18:52:00 +0200 (Mon, 29 Jul 2013)
New Revision: 2669
Modified:
pkg/FactorAnalytics/R/plot.FundamentalFactorModel.r
pkg/FactorAnalytics/R/plot.StatFactorModel.r
pkg/FactorAnalytics/R/plot.TimeSeriesFactorModel.r
pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r
Log:
change bar plot colors.
Modified: pkg/FactorAnalytics/R/plot.FundamentalFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/plot.FundamentalFactorModel.r 2013-07-29 16:49:31 UTC (rev 2668)
+++ pkg/FactorAnalytics/R/plot.FundamentalFactorModel.r 2013-07-29 16:52:00 UTC (rev 2669)
@@ -91,9 +91,9 @@
# "time series plot of actual and fitted values",
plot(actual.z[,asset.name], main=asset.name, ylab="Monthly performance", lwd=2, col="black")
- lines(fitted.z[,asset.name], lwd=2, col="blue")
+ lines(fitted.z[,asset.name], lwd=2, col="red")
abline(h=0)
- legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","blue"))
+ legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","red"))
},
"2L"={
# "time series plot of residuals with standard error bands"
@@ -164,12 +164,12 @@
switch(which.plot,
"1L" = {
- factor.names <- colnames(fit.fund$factors)
+ factor.names <- colnames(fit.fund$factor.returns)
# nn <- length(factor.names)
par(mfrow=c(n,1))
options(show.error.messages=FALSE)
for (i in factor.names[1:n]) {
- plot(fit.fund$factors[,i],main=paste(i," Factor Returns",sep="") )
+ plot(fit.fund$factor.returns[,i],main=paste(i," Factor Returns",sep="") )
}
par(mfrow=c(1,1))
},
@@ -193,7 +193,7 @@
plotcorr(ordered.cor.fm[c(1:n),c(1:n)], col=cm.colors(11)[5*ordered.cor.fm + 6])
},
"5L" = {
- cov.factors = var(fit.fund$factors)
+ cov.factors = var(fit.fund$factor.returns)
names = fit.fund$asset.names
factor.sd.decomp.list = list()
for (i in names) {
@@ -207,11 +207,11 @@
}
# extract contributions to SD from list
cr.sd = sapply(factor.sd.decomp.list, getCSD)
- rownames(cr.sd) = c(colnames(fit.fund$factors), "residual")
- # create stacked barchart
- barplot(cr.sd[,(1:max.show)], main="Factor Contributions to SD",
- legend.text=legend.txt, args.legend=list(x="topleft"),
- col=c(1:50),...)
+ rownames(cr.sd) = c(colnames(fit.fund$factor.returns), "residual")
+ # create stacked barchart
+ # discard intercept
+ barplot(cr.sd[-1,(1:max.show)], main="Factor Contributions to SD",
+ legend.text=legend.txt, args.legend=list(x="topleft"),...)
} ,
"6L" = {
factor.es.decomp.list = list()
@@ -221,7 +221,7 @@
# idx = which(!is.na(fit.fund$data[,i]))
idx <- fit.fund$data[,fit.fund$assetvar] == i
asset.ret <- fit.fund$data[idx,fit.fund$returnsvar]
- tmpData = cbind(asset.ret, fit.fund$factors,
+ tmpData = cbind(asset.ret, fit.fund$factor.returns,
fit.fund$residuals[,i]/sqrt(fit.fund$resid.variance[i]) )
colnames(tmpData)[c(1,length(tmpData[1,]))] = c(i, "residual")
factor.es.decomp.list[[i]] =
@@ -236,10 +236,9 @@
}
# report as positive number
cr.etl = sapply(factor.es.decomp.list, getCETL)
- rownames(cr.etl) = c(colnames(fit.fund$factors), "residual")
- barplot(cr.etl[,(1:max.show)], main="Factor Contributions to ES",
- legend.text=legend.txt, args.legend=list(x="topleft"),
- col=c(1:50),...)
+ rownames(cr.etl) = c(colnames(fit.fund$factor.returns), "residual")
+ barplot(cr.etl[-1,(1:max.show)], main="Factor Contributions to ES",
+ legend.text=legend.txt, args.legend=list(x="topleft"),...)
},
"7L" = {
factor.VaR.decomp.list = list()
@@ -249,7 +248,7 @@
# idx = which(!is.na(fit.fund$data[,i]))
idx <- fit.fund$data[,fit.fund$assetvar] == i
asset.ret <- fit.fund$data[idx,fit.fund$returnsvar]
- tmpData = cbind(asset.ret, fit.fund$factors,
+ tmpData = cbind(asset.ret, fit.fund$factor.returns,
fit.fund$residuals[,i]/sqrt(fit.fund$resid.variance[i]) )
colnames(tmpData)[c(1,length(tmpData[1,]))] = c(i, "residual")
factor.VaR.decomp.list[[i]] =
@@ -265,10 +264,9 @@
}
# report as positive number
cr.var = sapply(factor.VaR.decomp.list, getCVaR)
- rownames(cr.var) = c(colnames(fit.fund$factors), "residual")
- barplot(cr.var[,(1:max.show)], main="Factor Contributions to VaR",
- legend.text=legend.txt, args.legend=list(x="topleft"),
- col=c(1:50),...)
+ rownames(cr.var) = c(colnames(fit.fund$factor.returns), "residual")
+ barplot(cr.var[-1,(1:max.show)], main="Factor Contributions to VaR",
+ legend.text=legend.txt, args.legend=list(x="topleft"),...)
},
invisible()
)
Modified: pkg/FactorAnalytics/R/plot.StatFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/plot.StatFactorModel.r 2013-07-29 16:49:31 UTC (rev 2668)
+++ pkg/FactorAnalytics/R/plot.StatFactorModel.r 2013-07-29 16:52:00 UTC (rev 2669)
@@ -166,9 +166,9 @@
"1L" = {
## time series plot of actual and fitted values
plot(actual.z, main=asset.name, ylab="Monthly performance", lwd=2, col="black")
- lines(fitted.z, lwd=2, col="blue")
+ lines(fitted.z, lwd=2, col="red")
abline(h=0)
- legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","blue"))
+ legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","red"))
},
"2L" = {
@@ -270,9 +270,9 @@
# "time series plot of actual and fitted values",
plot(actual.z[,asset.name], main=asset.name, ylab="Monthly performance", lwd=2, col="black")
- lines(fitted.z[,asset.name], lwd=2, col="blue")
+ lines(fitted.z[,asset.name], lwd=2, col="red")
abline(h=0)
- legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","blue"))
+ legend(x="bottomleft", legend=c("Actual", "Fitted"), lwd=2, col=c("black","red"))
},
"2L"={
# "time series plot of residuals with standard error bands"
@@ -397,8 +397,7 @@
rownames(cr.sd) = c(colnames(fit.stat$factors), "residual")
# create stacked barchart
barplot(cr.sd[,(1:max.show)], main="Factor Contributions to SD",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft"))
} ,
"7L" ={
factor.es.decomp.list = list()
@@ -424,8 +423,7 @@
cr.etl = sapply(factor.es.decomp.list, getCETL)
rownames(cr.etl) = c(colnames(fit.stat$factors), "residual")
barplot(cr.etl[,(1:max.show)], main="Factor Contributions to ES",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft") )
},
"8L" = {
factor.VaR.decomp.list = list()
@@ -451,8 +449,7 @@
cr.var = sapply(factor.VaR.decomp.list, getCVaR)
rownames(cr.var) = c(colnames(fit.stat$factors), "residual")
barplot(cr.var[,(1:max.show)], main="Factor Contributions to VaR",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft"))
}, invisible()
)
Modified: pkg/FactorAnalytics/R/plot.TimeSeriesFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/plot.TimeSeriesFactorModel.r 2013-07-29 16:49:31 UTC (rev 2668)
+++ pkg/FactorAnalytics/R/plot.TimeSeriesFactorModel.r 2013-07-29 16:52:00 UTC (rev 2669)
@@ -370,8 +370,7 @@
rownames(cr.sd) = c(factor.names, "residual")
# create stacked barchart
barplot(cr.sd, main="Factor Contributions to SD",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft"))
},
"6L"={
@@ -416,8 +415,7 @@
cr.etl = sapply(factor.es.decomp.list, getCETL)
rownames(cr.etl) = c(factor.names, "residual")
barplot(cr.etl, main="Factor Contributions to ES",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft"))
},
"7L" ={
@@ -463,8 +461,7 @@
cr.VaR = sapply(factor.VaR.decomp.list, getCVaR)
rownames(cr.VaR) = c(factor.names, "residual")
barplot(cr.VaR, main="Factor Contributions to VaR",
- legend.text=T, args.legend=list(x="topleft"),
- col=c(1:50) )
+ legend.text=T, args.legend=list(x="topleft"))
},
invisible()
)
Modified: pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r
===================================================================
--- pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r 2013-07-29 16:49:31 UTC (rev 2668)
+++ pkg/FactorAnalytics/R/predict.FundamentalFactorModel.r 2013-07-29 16:52:00 UTC (rev 2669)
@@ -27,7 +27,7 @@
numExposures <- length(exposure.names)
numAssets <- length(assets)
- f <- fit.fund$factors # T X 3
+ f <- fit.fund$factor.returns # T X 3
predictor <- function(data) {
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