Created
October 16, 2012 19:02
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international frontier for big cap
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loadfrench <- function(zipfile, txtfile, skip, nrows) { | |
require(xts) | |
#my.url will be the location of the zip file with the data | |
my.url=paste("http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/",zipfile,".zip",sep="") | |
#this will be the temp file set up for the zip file | |
my.tempfile<-paste(tempdir(),"\\frenchzip.zip",sep="") | |
#my.usefile is the name of the txt file with the data | |
my.usefile<-paste(tempdir(),"\\",txtfile,".txt",sep="") | |
download.file(my.url, my.tempfile, method="auto", | |
quiet = FALSE, mode = "wb",cacheOK = TRUE) | |
unzip(my.tempfile,exdir=tempdir(),junkpath=TRUE) | |
#read space delimited text file extracted from zip | |
french <- read.table(file=my.usefile, | |
header = TRUE, sep = "", | |
as.is = TRUE, | |
skip = skip, nrows=nrows) | |
#get dates ready for xts index | |
datestoformat <- rownames(french) | |
datestoformat <- paste(substr(datestoformat,1,4), | |
substr(datestoformat,5,6),"01",sep="-") | |
#get xts for analysis | |
french_xts <- as.xts(french[,1:NCOL(french)], | |
order.by=as.Date(datestoformat)) | |
#divide by 100 to get percent | |
french_xts <- french_xts/100 | |
#delete missing data which is denoted by -0.9999 | |
french_xts[which(french_xts < -0.99,arr.ind=TRUE)[,1], | |
unique(which(french_xts < -0.99,arr.ind=TRUE)[,2])] <- 0 | |
return(french_xts) | |
} | |
filenames <- c("Global_25_Portfolios_ME_BE-ME","Europe_25_Portfolios_ME_BE-ME","Japan_25_Portfolios_ME_BE-ME","Asia_Pacific_ex_Japan_25_Portfolios_ME_BE-ME","North_America_25_Portfolios_ME_BE-ME") | |
#loop through the filenames to load the file for each region | |
for (i in 1:length(filenames)) { | |
assign(substr(filenames[i],1,4), loadfrench(zipfile=filenames[i],txtfile=filenames[i],skip=21,nrows=266)) | |
} | |
#merge the data into one xts object for ease of reference and use | |
big <- get(substr(filenames[1],1,4))[,21:25] | |
colnames(big) <- paste(substr(filenames[1],1,4),".",c("expensive",2:4,"cheap"),sep="") | |
#also set up equal weight to just explore the regions bigcap without valuation | |
big.ew <- as.xts(apply(big,MARGIN=1,FUN=mean),order.by=index(big)) | |
colnames(big.ew) <- substr(filenames[1],1,4) | |
for (i in 2:length(filenames)) { | |
temp <- get(substr(filenames[i],1,4))[,21:25] | |
colnames(temp) <- paste(substr(filenames[i],1,4),".",c("expensive",2:4,"cheap"),sep="") | |
big <- merge(big,temp) | |
temp.ew <- as.xts(apply(temp,MARGIN=1,FUN=mean),order.by=index(temp)) | |
colnames(temp.ew) <- substr(filenames[i],1,4) | |
big.ew <- merge(big.ew,temp.ew) | |
} | |
#use the equal weighted big cap | |
portfolio <- big.ew #change to big if you want to see the full 5x5 | |
require(fPortfolio) | |
#do a frontier plot full series and then 1990-1999 and 2000-current | |
#sloppy but it will work | |
frontier <- list(portfolioFrontier(as.timeSeries(portfolio["::1999",])), | |
portfolioFrontier(as.timeSeries(portfolio["2000::",])), | |
portfolioFrontier(as.timeSeries(portfolio))) | |
datelabels<-c("1990-1999","2000-2012","1990-2012") | |
#get colors with topo.colors for the three frontiers | |
#we will use the first 3 of the 4 supplied | |
colors <- topo.colors(4)[3:1] | |
for(i in 1:3) { | |
frontierPlot(frontier[[i]], pch=19, xlim=c(0,0.10), ylim=c(0,0.015), title=FALSE, col=c(colors[i],colors[i]), add=as.logical(i-1)) | |
minvariancePoints(frontier[[i]],pch=19,col="red") | |
#tangencyPoints(frontier,pch=19,col="blue") | |
#tangencyLines(frontier,pch=19,col="blue") | |
#equalWeightsPoints(frontier[[i]],pch=15,col="grey") | |
singleAssetPoints(frontier[[i]],pch=19,cex=1,col=colors[i]) | |
#twoAssetsLines(frontier,lty=3,col="grey") | |
#sharpeRatioLines(frontier,col="orange",lwd=2) | |
#legend("topleft",legend=colnames(portfolio),pch=19,col=topo.colors(10), | |
# cex=0.65) | |
#label assets | |
stats <- getStatistics(frontier[[i]]) | |
text(y=stats$mean,x=sqrt(diag(stats$Cov)),labels=names(stats$mean),pos=4,col=colors[i],cex=0.7) | |
#set up function from equalWeightsPoints to also label the point | |
equalLabel <- function (object, return = c("mean", "mu"), risk = c("Cov", "Sigma", | |
"CVaR", "VaR"), auto = TRUE, ...) | |
{ | |
return = match.arg(return) | |
risk = match.arg(risk) | |
data = getSeries(object) | |
spec = getSpec(object) | |
constraints = getConstraints(object) | |
numberOfAssets = getNAssets(object) | |
setWeights(spec) = rep(1/numberOfAssets, times = numberOfAssets) | |
ewPortfolio = feasiblePortfolio(data, spec, constraints) | |
assets = frontierPoints(ewPortfolio, return = return, risk = risk, | |
auto = auto) | |
text(assets, labels = "Equal-Weight", pos=4,...) | |
invisible(assets) | |
} | |
#equalLabel(frontier,cex=0.7,col="grey") | |
#label the frontier dates at minvariance point; again very sloppy but it works | |
#text(x=min(frontierPoints(frontier[[i]])[,1]), | |
# y=frontierPoints(frontier[[i]])[which(frontierPoints(frontier[[i]])[,1]==min(frontierPoints(frontier[[i]])[,1]))[1],2], | |
# labels=datelabels[i],col=colors[i],pos=2) | |
text(x=(minvariancePoints(frontier[[i]])[,1]), | |
y=(minvariancePoints(frontier[[i]])[,2]), | |
labels=datelabels[i],col=colors[i],pos=2) | |
} | |
title(main="Global Biggest Cap Efficient Frontier",xlab="Risk(cov)",ylab="Monthly Return") | |
mtext(side=3, text="source: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/data_library.html",font=3,cex=0.8) | |
#also parallel coordinates of each of the minvariance might be interesting | |
minvar <- as.data.frame(rbind((minvariancePoints(frontier[[1]])),(minvariancePoints(frontier[[2]])),(minvariancePoints(frontier[[3]])))) | |
rownames(minvar) <- datelabels | |
parcoord(minvar,col=colors) | |
#might be nice to do animated gif or parallel coordinates of weights or risk/return | |
weightsPlot(frontier[[3]])(frontier[[3]])) |
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