Hey Josh, Thanks for the quick response!
I guess I have to switch from the Java mindset to the matrix/vector mindset of R. Your code worked very well, but I just have one problem: Essentially I have a time series of stock A, followed by a time series of stock B, etc. So there are break points in the data (the points where it switches stocks have incorrect returns, and should be NA at t=0 for each stock) Is there an easy way to account for this in R? What I was thinking of is if there is a way to make a filter rule. Such as if the ID of the row matches Stock A, then perform this. >>"Hello Jeff, Try this: test <- data.frame(totret=rnorm(10^7)) #create some sample data test[-1,"dailyreturn"] <- test[-1,"totret"]/test[-nrow(test),"totret"] The general idea is to take the column "totret" excluding the first 1, dividided by "totret" exluding the last row. This gives in effect t+1 (since t is now shorter)/t I assigned the result to a new column "dailyreturn". For 10^7 rows, it tooks 1.92 seconds on my system." -- View this message in context: http://r.789695.n4.nabble.com/R-Newbie-please-help-tp2242633p2242703.html Sent from the R help mailing list archive at Nabble.com. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.
