48 Industries Since 1963

Please see http://timelyportfolio.blogspot.com/search/label/horizonplot for all horizon plot posts.

Once more thanks to Ken French for his data, we can accomplish something I think is fairly amazing.  In 640x800, we can see 250 day rollling returns for 48 U.S. industries since 1963.

From TimelyPortfolio

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

	#get very helpful Ken French data
	#for this project we will look at Industry Portfolios
	#http://mba.tuck.dartmouth.edu/pages/faculty/ken.french/ftp/48_Industry_Portfolios_daily.zip
	require(latticeExtra)
	require(PerformanceAnalytics)
	require(quantmod)
	#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
	#do a horizon plot of all 48 industries with horizonscale of 0.25
	horizonplot(roc,
	layout=c(1,48),
	horizonscale=0.25, #feel free to change to whatever you would like
	scales = list(tck = c(1,0), y = list(draw = FALSE,relation = "same")),
	origin = 0,
	colorkey = FALSE,
	#since so many industries, we will comment out grid
	# panel = function(x, ...) {
	# panel.horizonplot(x, ...)
	# panel.grid(h=3, v=0,col = "white", lwd=1,lty = 3)
	# },
	ylab = list(rev(colnames(roc)), 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 1963-2011\n source: http://mba.tuck.dartmouth.edu/pages/faculty/ken.french")

view raw horizon plot of french 48 industry portfolio.r hosted with ❤ by GitHub