Hi, I'm looking at about 20 assets returns for the past 50 periods. They returns are correlated (some more than others.)
I'm interested in trying some monte carlo techniques for determining an optimal portfolio. The "usual" method I seen uses a multivariate norm to sample possible data (rmvnorm function in R.) The returns are definitely not normally distributed. So, my goal is to duplicate the same functionality of using a rmvnorm, but for unknown distributions that are partially correlated. It was suggested to me that I might look at the boot function in R, however this appears to generate a summary statistic which isn't what I want. What I'd really like to do is simulate possible "alternate paths" for the assets based on their historical data. The paths are random, but follow the same distribution as the real assets and the same correlation. I can't seem to find a way to do this. Does anyone have any suggestions? Thanks, -- Noah _______________________________________________ [email protected] mailing list https://stat.ethz.ch/mailman/listinfo/r-sig-finance -- Subscriber-posting only. If you want to post, subscribe first. -- Also note that this is not the r-help list where general R questions should go.
