data = read.csv("bovespa-2010-2012.csv",header=TRUE)

attach(data)

ind = names(data)[2:126]

price = data[,2:126]

r = 100*(exp(apply(log(price),2,diff))-1)

p = ncol(r)

pdf(file="returns0.pdf",width=24,height=12)
par(mfrow=c(4,8))
for (i in 1:p)
  ts.plot(r[,i],ylab="",main=paste(i," - ",ind[i],sep=""))
dev.off()


r = r[,-c(6,67,70,88,115,116,119)]
ind = ind[-c(6,67,70,88,115,116,119)]
p = ncol(r)

pdf(file="returns1.pdf",width=24,height=12)
par(mfrow=c(4,8))
for (i in 1:p)
  ts.plot(r[,i],ylab="",main=ind[i])
dev.off()

pdf(file="returns2.pdf",width=24,height=12)
par(mfrow=c(4,8))
for (i in 1:p)
  ts.plot(r[,i],ylab="",main=ind[i],ylim=range(r))
dev.off()



t0=c(1,seq(1,495,by=22))
t1=c(495,seq(23,495,by=22),495)
corrs1 = NULL
pdf(file="correlations.pdf",width=15,height=10)
par(mfrow=c(3,4))
for (k in 1:24){
corr = cor(r[t0[k]:t1[k],])
corrs = NULL
for (i in 1:(p-1))
  for (j in (i+1):p){
    corrs = c(corrs,corr[i,j])
  }
pcor = round(100*mean(corr>=0.5),2)
corrs1 = cbind(corrs1,corrs)
hist(corrs,xlab="Correlations",prob=TRUE,main="",
breaks=seq(min(corrs),max(corrs),length=20),xlim=c(-1,1),ylim=c(0,4))
title(paste(data[t0[k],1],"-",data[t1[k],1],"\n%corr > 0.5 = ",pcor,sep=""))
}
dev.off()


boxplot(corrs1,outline=FALSE,ylim=c(-1,1),names=1:length(t0))