Asset price example example 103 prepare data set

#Asset Price Example
#Example 10.3
#prepare data set
library(quantmod)
SS36=getSymbols("600036.SS", auto.assign=F)
SS36=as.data.frame(SS36)
names(SS36)[1]=paste("open")
names(SS36)[2]=paste("high")
names(SS36)[3]=paste("low")
names(SS36)[4]=paste("close")
names(SS36)[5]=paste("vol")
SS36=cbind(SS36, date=as.Date(rownames(SS36)) )
SS36["code"]=600036
SS36=subset(SS36, date>="2012-10-01")
r=rotate(SS36, c("high", "low", "close") ,4)
coeff=4
sw=3
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$open-r$close1)/r$close1)/
sw ), sw)
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
#(rr$open-rr$close1)/(rr$close1*rr$lam)
x=data.frame(date=rr$date, x1=(rr$open-rr$close1)/(rr$close1*rr$lam))
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$close1-
r$close2)/r$close1)/sw ),sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
(rr$close1-rr$close2)/(rr$close1*rr$lam)
x=cbind(x, x2=(rr$close1-rr$close2)/(rr$close1*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$high1-
r$high2)/r$close1)/sw ), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x3=(rr$high1-rr$high2)/(rr$close1*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$low1-r$low2)/r$close1)/sw
), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x4=(rr$low1-rr$low2)/(rr$close1*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$close2-
r$close3)/r$close2)/sw ),sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x5=(rr$close2-rr$close3)/(rr$close2*rr$lam) )

rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$high2-
r$high3)/r$close2)/sw ), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x6=(rr$high2-rr$high3)/(rr$close2*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$low2-r$low3)/r$close2)/sw
), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x7=(rr$low2-rr$low3)/(rr$close2*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$close3-
r$close4)/r$close3)/sw ),sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x8=(rr$close3-rr$close4)/(rr$close3*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$high3-
r$high4)/r$close3)/sw ), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x9=(rr$high3-rr$high4)/(rr$close3*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$low3-r$low4)/r$close3)/sw
), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, x10=(rr$low3-rr$low4)/(rr$close3*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$high-
r$close)/r$close1)/sw ),sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, d1=(rr$high-rr$close)/(rr$close1*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$close-
r$close1)/r$close1)/sw ), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, d2=(rr$close-rr$close1)/(rr$close1*rr$lam) )
rr=NA
rr=rollingSum(r, data.frame(r$date, lam=(coeff*abs(r$close-r$low)/r$close1)/sw
), sw )
rr$lam=ifelse(rr$lam==0, 0.001, rr$lam)
x=cbind(x, d3=(rr$close-rr$low)/(rr$close1*rr$lam) )
require ("neuralnet")
net.out <- neuralnet(d1+d2+d3~x1+x2+x3+x4+x5+x6+x7+x8+x9+x10, data=x,
hidden=18, threshold=0.001,
stepmax=1e+6)
rollingSum=function(x, y, sw)
{
# c(date, colman=forumula)
y=data.frame(y)
y=y[order( y[,1], decreasing=T),]
y_colnames= colnames(y[2])
for (i in 1:(length(y[,1])-(sw-1)))

{
tmpSum=sum(y[i:(i+sw-1), 2])
tmpDate= y[i,1]
singleRow=data.frame(tmpDate, tmpSum )
if (i==1) retV=rbind(singleRow)
else retV=rbind(retV,singleRow)
}