horizon plot examples

horizon plot applied.r

require(lattice)
require(latticeExtra)
require(directlabels)
require(reshape2)
require(quantmod)
require(PerformanceAnalytics)


data(managers)
managers[which(is.na(managers),arr.ind=TRUE)[,1],
                  unique(which(is.na(managers),arr.ind=TRUE)[,2])] = 0
testprice <- cumprod(1+managers)-1


testdf <- as.data.frame(cbind(index(testprice),coredata(testprice)),stringsAsFactors=FALSE)
testmelt <- melt(testdf,id.vars=1)
colnames(testmelt) <- c("date","series","growth")
testmelt[,"date"] <- as.Date(testmelt[,"date"])

#just plain old xyplot from xts package examples
direct.label(
  xyplot(testprice,
      lwd=2,
      screens=1,
      col = c(brewer.pal(n=8,"Dark2")[1:6],brewer.pal(n=9,"PuBu")[5:9]),
      panel = function(x, y, ...) {
       panel.xyplot(x, y, ...)
      },         
      scales = list(tck = c(1,0), y = list(draw = TRUE,relation = "same", alternating = FALSE)),
      xlab = NULL,
      main="Performance Since 1996 or Inception"),
  list(last.bumpup,hjust=0.75, cex=0.8))
#get panel in row 1 and column 1, since only one panel because screens = 1
trellis.focus("panel", 1, 1, highlight = FALSE)
panel.refline(h = pretty(coredata(testprice)), col = "gray70", lty = 3)

#does not even qualify but here as another example
xyplot(testprice,
       scales = list(tck = c(1,0), y = list(draw = TRUE,relation = "same", alternating = FALSE)),
  panel = function(x, y, ...) {
    panel.grid(col = "grey", lty = 3)
    panel.xyplot(x, y, ...)
  },
  layout= c(1,NCOL(testprice)))


xyplot(testprice,
       col = c(brewer.pal(n=8,"Dark2")[1:6],brewer.pal(n=9,"PuBu")[5:9]),
       screens = colnames(testprice),
       lwd = 3,
       strip = FALSE, strip.left = TRUE,
       scales = list(x = list(tck = c(1,0), alternating = FALSE),
                     y = list(tck = c(0,1), draw = TRUE, relation = "same", alternating = 2)),
       panel = function(x, y, ...) {
         panel.refline(h = pretty(coredata(testprice)), col = "gray70", lty = 3)
         panel.xyplot(x, y, ...)
       },
       main = "Performance Since 1996 or Inception")

#first horizonplot with little adjustment
horizonplot(testprice, horizonscale = 1,
            #turn off ticks on top and do not draw y ticks or axis
            scales = list(tck = c(1,0), y = list(draw = FALSE,relation = "same")),
            #draw strip on top
            strip=TRUE,
            #do not draw strip to left since we have strip = TRUE above
            strip.left=FALSE,
            #do standard horizon but also add horizontal white grid lines
            panel = function(x, ...) {
              panel.horizonplot(x, ...)
              #here we draw white horizontal grid
              #h = 3 means 3 lines so will divide into fourths
              #v = 0 will not draw any vertical grid lines
              panel.grid(h=3, v=0,col = "white", lwd=1,lty = 1)              
            },
            layout=c(1,ncol(testprice)),
            main = "Performance Since 1996 or Inception")

## amended from horizonplot example given in documentation
horizonplot(testprice,
            scales = list(tck = c(1,0), y = list(draw = FALSE,relation = "same")),
            origin = 0,
            horizonscale = 1,
            colorkey = FALSE,
            panel = function(x, ...) {
              panel.horizonplot(x, ...)
              panel.grid(h=3, v=0,col = "white", lwd=1,lty = 3)
            },
            ylab = list(rev(colnames(testprice)), rot = 0, cex = 0.8, pos = 3), 
            xlab = NULL,
            par.settings=theEconomist.theme(box = "gray70"),
            strip.left = FALSE,
            layout = c(1,ncol(testprice)),
            main = "Performance Since 1996 or Inception")


#horizon plot version of http://www.mebanefaber.com/timing-model/
#do horizon of percent above or below 10 month or 200 day moving average
tckrs <- c("VTI","VEU","IEF","VNQ","DBC")
getSymbols(tckrs, from = "2010-12-31")
#do horizon of percent above or below 10 month or 200 day moving average
prices <- get(tckrs[1])[,4]
for (i in 2:length(tckrs)) {
  prices <- merge(prices,get(tckrs[i])[,4])
}
colnames(prices) <- tckrs

n=200
#get percent above or below
pctdiff <- (prices / apply(prices, MARGIN = 2, FUN = runMean, n = n) - 1)[n:NROW(prices),]

horizonplot(pctdiff,
            scales = list(tck = c(1,0), y = list(draw = FALSE,relation = "same")),
            origin = 0,
            horizonscale = 0.05,
            colorkey = FALSE,
            panel = function(x, ...) {
              panel.horizonplot(x, ...)
              panel.grid(h=3, v=0,col = "white", lwd=1,lty = 3)
            },
            ylab = list(rev(colnames(prices)), rot = 0, cex = 0.8, pos = 3), 
            xlab = NULL,
            par.settings=theEconomist.theme(box = "gray70"),
            strip.left = FALSE,
            layout = c(1,ncol(prices)),
            main = "Percent Above or Below 200 Days Moving Average")

# for one more example, let's do a mirror horizon plot
horizonplot.offset <- function(x,horizon.type="offset",horizonscale=0.05,title=NA,alpha=0.4){
  #get the positive and negative plots for the offset chart
  #very similar to the mirror chart above
  #except the negative values will be moved to the top of y range
  #and inverted
  ppos<-
    xyplot(x,ylim=c(0,horizonscale),origin=0,
           par.settings=theEconomist.theme(box="transparent"),
           lattice.options=theEconomist.opts(),
           xlab=NULL,ylab=NULL,
           panel = function(x,y,...){
             #
             for (i in 0:round(max(y)/horizonscale,0))
               panel.xyarea(x,y=ifelse(y>0,y,NA)-(horizonscale * i),col="green",border="green",col.line="green",alpha=alpha,lwd=2,
                            scales = list(y=list(draw=FALSE)),...)
           },
           main=title)
  pneg <- 
    xyplot(x,ylim=c(0,horizonscale),origin=horizonscale,
           panel=function(x, y ,...){
             for (i in 0:round(min(y)/-horizonscale,0)) {
               panel.xyarea(x,y=horizonscale+ifelse(y<0,y,NA)+(horizonscale*i),col.line="red",border="red",col="red",lwd=2,alpha=alpha,...)
             }
           })
  
  return(ppos+pneg) 
}

horizonplot.offset(pctdiff, title = "Percent Difference from 200 Day Moving Average")