48 Industries Since 1963
[This article was first published on Timely Portfolio, and kindly contributed to R-bloggers]. (You can report issue about the content on this page here)
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.
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 640×800, 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):
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
#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") |
To leave a comment for the author, please follow the link and comment on their blog: Timely Portfolio.
R-bloggers.com offers daily e-mail updates about R news and tutorials about learning R and many other topics. Click here if you're looking to post or find an R/data-science job.
Want to share your content on R-bloggers? click here if you have a blog, or here if you don't.