48 Industries (Dendrogram Ordered) Over 50 Years

Thanks to reader AHWest for the comment on post 48 Industries Since 1963.

“I think it would be interesting to see the industries ordered by some sort of similarity of returns.”

I think this is a great suggestion, and I would like to see it also.  I tried the dendrogram plot technique from Inspirational Stack Overflow Dendrogram Applied to Currencies, but then I spotted the dendrogramGrob in the latticeExtra documentation.  This was much easier, and in a couple of lines, we are able to order and connect the 48 industries.

From TimelyPortfolio

R code from GIST (do raw for copy/paste):

	require(fAssets)
	require(latticeExtra)
	require(quantmod)
	require(PerformanceAnalytics)
	#my.url will be the location of the zip file with the data
	my.url="http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/48_Industry_Portfolios_daily.zip"
	#this will be the temp file set up for the zip file
	my.tempfile<-paste(tempdir(),"\\frenchindustry.zip",sep="")
	#my.usefile is the name of the txt file with the data
	my.usefile<-paste(tempdir(),"\\48_Industry_Portfolios_daily.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_industry <- read.table(file=my.usefile,
	header = TRUE, sep = "",
	as.is = TRUE,
	skip = 9, nrows=12211)
	#get dates ready for xts index
	datestoformat <- rownames(french_industry)
	datestoformat <- paste(substr(datestoformat,1,4),
	substr(datestoformat,5,6),substr(datestoformat,7,8),sep="-")
	#get xts for analysis
	french_industry_xts <- as.xts(french_industry[,1:NCOL(french_industry)],
	order.by=as.Date(datestoformat))
	#divide by 100 to get percent
	french_industry_xts <- french_industry_xts/100
	#delete missing data which is denoted by -0.9999
	french_industry_xts[which(french_industry_xts < -0.99,arr.ind=TRUE)[,1],
	unique(which(french_industry_xts < -0.99,arr.ind=TRUE)[,2])] <- 0
	#get price series or cumulative growth of 1
	french_industry_price <- cumprod(french_industry_xts+1)
	#get 250 day rate of change or feel free to change to something other than 250
	roc <- french_industry_price
	#split into groups so do not run out of memory
	for (i in seq(12,48,by=12)) {
	roc[,((i-11):(i))] <- ROC(french_industry_price[,((i-11):(i))],n=250,type="discrete")
	}
	roc[1:250,] <- 0
	# try to do http://stackoverflow.com/questions/9747426/how-can-i-produce-plots-like-this
	# was much easier to use latticeExtra
	# get dendrogram data from hclust
	# backward and repetitive but it works
	t <- assetsDendrogramPlot(as.timeSeries(french_industry_xts))
	# thanks to the latticeExtra example
	dd.row <- as.dendrogram(t$hclust)
	row.ord <- order.dendrogram(dd.row)
	xyplot(roc[,row.ord],
	layout=c(1,48), ylim=c(0,0.25),
	scales = list(tck = c(1,0), y = list(draw = FALSE,relation = "same")),
	horizonscale=0.25,
	origin = 0,
	colorkey = TRUE,
	#since so many industries, we will comment out grid
	panel = function(x,y,...) {
	panel.horizonplot(x,y,...) #feel free to change to whatever you would like)
	# panel.grid(h=3, v=0,col = "white", lwd=1,lty = 3)
	},
	ylab = list(rev(colnames(roc[,row.ord])), rot = 0, cex = 0.7, pos = 3),
	xlab = NULL,
	par.settings=theEconomist.theme(box = "gray70"),
	#use ylab above for labelling so we can specify FALSE for strip and strip.left
	strip = FALSE,
	strip.left = FALSE,
	main = "French Daily 48 Industry (Dendrogram Ordered) 1963-2011\n source: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french",
	legend =
	list(right =
	list(fun = dendrogramGrob,
	args =
	list(x = dd.row, ord = row.ord,
	side = "right",
	size = 10))))

view raw horizon plot of 48 industries with dendrogram order.r hosted with ❤ by GitHub