french be-me breakpoints as valuation tool.r

require(latticeExtra)
require(xts)

loadfrench <- function(zipfile, txtfile, skip, nrows) {
  
  #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 = FALSE, sep = "", fill=TRUE,  #add fill = true to handle bad data
                       as.is = FALSE ,
                       skip = skip, nrows=nrows)
  
  #get dates ready for xts index
  datestoformat <- french[,1]
  datestoformat <- paste(substr(datestoformat,1,4),
                         "12","31",sep="-")
  
  #get xts for analysis
  #unfortunately the last percentile in 1942 is not separated by a space so we will delete last two columns
  french_xts <- as.xts(french[,1:(NCOL(french)-2)],
                       order.by=as.Date(datestoformat))
  
  #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

  
  #divide by 100 to get percent
  french_xts <- french_xts/100  
  
  return(french_xts)
}

filenames <- c("BE-ME_Breakpoints")

BE_ME = loadfrench(zipfile=filenames[1],txtfile=filenames[1],skip=3,nrows=87)
#first column is year which we can remove
#columns 2 and 3 are counts for positive and negative which we will remove
BE_ME = BE_ME[,4:NCOL(BE_ME)]

colnames(BE_ME) <- paste(5*0:(NCOL(BE_ME)-1),"pctile",sep="")

#do horizon plot of absolute BE_ME breakpoints
horizonplot(BE_ME,
            layout=c(1,NCOL(BE_ME)),
            strip.left=FALSE,
            xlab = NULL,
            ylab = list(rev(colnames(BE_ME)), rot = 0, cex = 0.7),
            scales = list(x=list(tck=c(1,0))),
            main="Analysis of Historical BE_ME Breakpoints \n(data courtesy http://mba.tuck.dartmouth.edu/pages/faculty/ken.french)")

#do horizon plot of relative to historical mean breakpoints
horizonplot(BE_ME/matrix(rep(apply(BE_ME,MARGIN=2,FUN=mean),times=NROW(BE_ME)),ncol=NCOL(BE_ME),byrow=TRUE)-1,
            layout=c(1,NCOL(BE_ME)),
            horizonscale=0.25,
            origin = 0,
            scales = list(y = list(relation = "same"), x=list(tck=c(1,0))),
            strip.left=FALSE,
            xlab = NULL,
            ylab = list(rev(colnames(BE_ME)), rot = 0, cex = 0.7),          
            main="Analysis of Historical BE_ME Breakpoints - Mean \n(data courtesy http://mba.tuck.dartmouth.edu/pages/faculty/ken.french)")

require(RColorBrewer)
xyplot(BE_ME,col=c(brewer.pal(9,"Reds"),brewer.pal(9,"Blues")),
       screens=1,
       scales = list(x=list(tck=c(1,0))),
       xlab = NULL,
       ylab = "ME-BE Breakpoints",
       main="Analysis of Historical BE_ME Breakpoints\n(data courtesy http://mba.tuck.dartmouth.edu/pages/faculty/ken.french)")