Faster Way of Calculating Rolling Realized Volatility in R
r, xts
Solution
You can use `runSD` in the TTR package (which is loaded by quantmod), but you will need to apply `runSD` to each column, convert the result of `apply` back to an xts object, and manually annualize the result.
realized.vol <- xts(apply(index.ret,2,runSD,n=20), index(index.ret))*sqrt(252)
Problem
I want to calculate the rolling 20 day realized volatility for a collection of indices. Here is the code I use to download the index prices, calculate the daily returns and the 20 day realized volatility. ``` library(quantmod) library(PerformanceAnalytics) tickers = c("^RUT","^STOXX50E","^HSI", "^N225", "^KS11") myEnv <- new.env() getSymbols(tickers, src='yahoo', from = "2003-01-01", env = myEnv) index <- do.call(merge, c(eapply(myEnv, Ad), all=FALSE)) #Calculate daily returns for all indices and convert to arithmetic returns index.ret <- exp(CalculateReturns(index,method="compound")) - 1 index.ret[1,] <- 0 #Calculate realized volatility realizedvol <- rollapply(index.ret, width = 20, FUN=sd.annualized) ``` Everything works pretty quick until the final line. I haven't timed it but it is on the scale of minutes whereas I would expect it to take only seconds. Is there a faster way to calculate the realized volatility? Thank you.