The graph for figure 8.4 requires to be somehow careful about correctly lagging the CRP value when calculating the weights.


# fig 8.4 of Cover “Universal Portfolios”
require(logopt)
x <- nyse.cover.1962.1984
xik <- x[,c("iroqu","kinar")]
nDays <- dim(xik)[1]
Days <- 1:nDays
pik <- cumprod(xik)
alphas <- seq(0,1,by=0.05)
bk <- xik[,1] * 0
w <- xik[,1] * 0
for (i in 1:length(crps)) {
  # we calculate bk by weighting the b by the realized wealth lagged one
  weight <- lag(crp(xik, c(alphas[i], 1-alphas[i])), 1)
  bk <- bk + alphas[i] * weight
  w <- w + weight
}
bk <- bk / w
bk[1] <- 0.5
plot(Days, bk, col=”blue”, type=”l”, ylim = range(0.25, range(bk)), 
     main = ‘Mix of “iroqu” and “kinar” in Universal Portfolio’, 
     ylab=’Fraction of “iroqu”‘)
grid()

The porfolio $$ b ^ k

Figure 8.5, 8.6 and 8.7 share the same format, so we define a function to draw them.



# fig 8.5, 8.6 and 8.7 of Cover “Universal Portfolios”


require(logopt)
x <- nyse.cover.1962.1984


show_pair <- function (x,a,b) { 
  xab <- x[,c(a,b)]
  nDays <- dim(xab)[1]
  Days <- 1:nDays
  pab <- cumprod(xab)
  layout(matrix(c(1,3,4,2), 2, 2, byrow = TRUE))
  main_text <- sprintf("\"%s\" and \"%s\"",a,b)
  plot(Days, pab[,a], col=”blue”, type=”l”, ylim=range(pck), 
       main = main_text, ylab=””)
  lines(Days, pab[,b], col=”red”)
  grid() 
  legend(“topleft”,c(sprintf(“\”%s\””,a),
         sprintf(“\”%s\””,b)),col=c(“blue”,”red”),lty=c(1,1))


  alphas <- seq(0,1,by=0.05)
  crps <- alphas
  for (i in 1:length(crps)) {
    crps[i] <- crp(xab, c(alphas[i], 1-alphas[i]))[nDays]
  }
  main_text <- sprintf("20 Year Return vs. mix of \"%s\" and \"%s\"",a,b)
  xlab_text <- sprintf("Fraction of \"%s\" in Portfolio", a)
  plot(alphas, crps, col=”blue”, type=”l”, ylab=””, 
       main=main_text, xlab=xlab_text)
  points(alphas, crps, pch=19, cex=0.5, col=”red”)
  abline(h=mean(crps), col=”green”)
  text(0.4,mean(crps)*1.05,labels=”Return from Universal Portfolio”)
  grid()


  universal <- xab[,1] * 0
  for (i in 1:length(crps)) {
    universal <- universal + crp(xab, c(alphas[i], 1-alphas[i]))
  }
  universal <- universal / length(alphas)
  main_text <- sprintf("Universal Portfolio with \"%s\" and \"%s\"",a,b)
  plot(Days, pab[,a], col=”blue”, type=”l”, ylim=range(pab, universal), 
       main = main_text, ylab=””)
  lines(Days, pab[,b], col=”red”)
  lines(Days, universal, col=”green”,)
  legend(“topleft”,c(sprintf(“\”%s\””,a), sprintf(“\”%s\””,b),'”unversal”‘),
         col=c(“blue”,”red”,”green”),lty=c(1,1,1))
  grid()




  bk <- xab[,1] * 0
  w <- xab[,1] * 0
  for (i in 1:length(crps)) {
    # we calculate bk by weighting the b by the realized wealth lagged one
    weight <- lag(crp(xab, c(alphas[i], 1-alphas[i])), 1)
    bk <- bk + alphas[i] * weight
    w <- w + weight
  }
  bk <- bk / w
  bk[1] <- 0.5
  main_text <- sprintf("Mix of \"%s\" and \"%s\" in Universal Portfolio",a,b)
  ylab_text <- sprintf("Fraction of \"%s\"", a)
  plot(Days, bk, col=”blue”, type=”l”, ylim = range(range(bk)), 
       main=main_text, ylab=ylab_text)
  grid()
}


# fig 8.5
show_pair(x,”comme”,”kinar”)

Commercial Metals and Kin Ark

Commercial Metals and Mei Corp.

# fig 8.7
show_pair(x,”coke”,”ibm”)

IBM and Coca-Cola

All original figures are now reproduced.