Hi Samir, to me, autocorrelation is the cross-correlation of a signal with itself. Which is why I don't really understand the meaning of your question. Are you looking for cross-correlation, for example the ccf function documented in the same help page as acf ?
JC 2011/9/16 Samir Benzerfa <benze...@gmx.ch>: > Below you can see a sample of my data. > > I learned that I can calculate the autocorrelation of such time series by > using the function acf(Stock A) or pacf(Stock A) and the same for the other > stocks. What I would like to do, is to calculate the overall autocorrelation > in the whole set (so for all stocks together). > > Any ideas? > > Thanks, > SB > > > Date Stock A Stock B > 01.01.1980 0 0 > 02.01.1980 0 0 > 03.01.1980 0.002149977 0 > 04.01.1980 -0.002149977 0.003966489 > 07.01.1980 0 0 > 08.01.1980 0.007478811 0 > 09.01.1980 0.007352198 0.00393059 > 10.01.1980 0.003113235 0.009673601 > 11.01.1980 -0.008352074 -0.003843623 > 14.01.1980 0 0 > 15.01.1980 -0.006371182 -0.009760568 > 16.01.1980 0.007424018 0.00393059 > 17.01.1980 0.007299239 0.001952035 > 18.01.1980 -0.008352074 -0.001952035 > > > > -----Ursprüngliche Nachricht----- > Von: Jean-Christophe BOUËTTÉ [mailto:jcboue...@gmail.com] > Gesendet: Freitag, 16. September 2011 15:20 > An: Samir Benzerfa > Cc: r-help@r-project.org > Betreff: Re: [R] question concerning the acf function > > Hi, > you did not supply a reproducible example. We do not know what your > data nor your code looks like. > Please follow the recommandations found at the bottom of this email! > You're more likely to get a quick and meaningful reply. > JC > > 2011/9/16 Samir Benzerfa <benze...@gmx.ch>: >> Hi everyone, >> >> >> >> I've got a question concerning the function acf(.) in R for calculating > the >> autocorrelation in my data. >> >> >> >> I have a table with daily returns of several stocks over time and I would >> like to calculate the autocorrelation for all the series (not only for one >> time series). How can I do this? >> >> After that I want to apply an autoregressive model based on the estimated >> lag in the data and finally extract the residuals for further > calculations. >> >> >> >> Many thanks & best regards >> >> Benzerfa >> >> >> [[alternative HTML version deleted]] >> >> ______________________________________________ >> 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. > > ______________________________________________ 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.
