french industry animated gif of correlation

french industry animated correlation gif.r

#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(animation)
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 a vector of the end of years
evaldates <- endpoints(french_industry_xts,"years")

saveGIF(
  for(i in 2:length(evaldates)) {  
    #do correlation table
    ca <- cor(french_industry_xts[evaldates[i-1]:evaldates[i],])
    
    #replace na with 0
    ca[which(is.na(ca),arr.ind=TRUE)[,]] <- 0
    
    #get colors to use for heat map
    brew <- brewer.pal(name="RdBu",n=5)
    #get color ramp
    cc.brew <- colorRampPalette(brew)
    #apply color ramp
    cc <- cc.brew(nrow(ca))
    #do heatmap and sort by degree of correlation to VFINX (Vanguard S&P 500)
    #heatmap(ca,symm=TRUE,Rowv=NA,Colv=NA,col=cc,RowSideColors=cc,main="")
    #title(main=paste("Correlation Table\n",index(french_industry_xts)[evaldates[i]],sep=""),font.main=1,outer=TRUE,line=-2,cex.main=1.3)
    #do with dendrogram ordering
    heatmap(ca,symm=TRUE,col=cc,RowSideColors=cc,main="")
    title(main=paste("Correlation Table (Dendrogram Ordered)\n",index(french_industry_xts)[evaldates[i]],sep=""),font.main=1,outer=TRUE,line=-3,cex.main=1.3,adj=0)  
  }
)