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.
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| From TimelyPortfolio |
R code in GIST (do raw for copy/paste):
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| #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") |
