Is it possible to optimize (make it much faster) this piece of code:
out <- do.call(rbind,
lapply(split(Cl(cumulativeBars), "days"),
function(x) {
previousFullBars <- barsEndptCl[as.Date(index(barsEndptCl), tz=indexTZ(barsEndptCl)) < as.Date(last(index(x)), tz=indexTZ(x)), ]
if (NROW(previousFullBars) >= 4) {
last(SMA(last(rbind(previousFullBars, x), n=6), n=5))
} else {
xts(NA, order.by=index(x))
}
}))
Below you can find my original question with all the code example that runs but a bit to slow for my needs.
ORIGINAL QUESTION:
After I was able to transform xts to lower frequency in cumulative way How to transform xts to lower frequency in a cumulative way thanks to people reading this list.
Now I am trying to calculate "evolution" of moving averages using code below. It is to slow for me. Can tis code (from # TODO: How to compute moving average?, the part starting with out <- do.call(rbind,lapply(split(Cl(cumulativeBars)...) be optimized in any way?
to.weekly.cumulative <- function(xts.obj, name="") {
out <- do.call(rbind,
lapply(split(xts.obj, 'weeks'),
function(x) cbind(rep(first(x[,1]), NROW(x[,1])),
cummax(x[,2]), cummin(x[,3]), x[,4])))
colnames(out) <- paste(name, c("Open", "High", "Low", "Close"), sep=".")
out
}
library(quantmod)
data(sample_matrix)
myxts <- as.xts(sample_matrix)
head(to.weekly.cumulative(myxts), 15)
# TODO: How to compute moving average?
# This SMA(Cl(to.weekly.cumulative(myxts)), n=5) would obviously be wrong
cumulativeBars <- to.weekly.cumulative(myxts)
barsEndptCl <- Cl(cumulativeBars[endpoints(cumulativeBars, 'weeks')])
barsEndptCl <- Cl(to.weekly(myxts))
#all.equal(cumulativeBars[endpoints(cumulativeBars, 'weeks')], to.weekly(myxts))
out <- do.call(rbind,
lapply(split(Cl(cumulativeBars), "days"),
function(x) {
previousFullBars <- barsEndptCl[as.Date(index(barsEndptCl), tz=indexTZ(barsEndptCl)) < as.Date(last(index(x)), tz=indexTZ(x)), ]
if (NROW(previousFullBars) >= 4) {
last(SMA(last(rbind(previousFullBars, x), n=6), n=5))
} else {
xts(NA, order.by=index(x))
}
}))
colnames(out) <- "SMA5"
out <- lag.xts(out, k=7)
chart_Series(to.weekly(myxts))
add_TA(SMA(to.weekly(myxts), 5), on=1, col="red")
add_TA(out, on=1, col="green")
