Have a look at the ugarchfilter method (also have a look at the underlying code for ugarchroll for some possible pointers).
Alexios > On 21 Sep 2014, at 07:56, Don Brady <dbr...@pobox.com> wrote: > > What would be the most efficient way to make iterated n-ahead Multistep > Out-of-Sample GARCH Forecasts using Rugarch? > > Let me explain what I mean. > > A number of papers on using GARCH describe such a method and call it the > "iterated" method. (They also say that it works very). > I am trying to use it. > > For example, from > "Multi-Period Forecasts of Volatility:Direct, Iterated, and Mixed-Data > Approaches" > by Eric Ghysels† Antonio Rubia‡ et al: > > "Long horizon volatility forecasts can be constructed in three fundamentally > different ways. > ....... The second approach is to estimate a daily autoregressive volatility > forecasting model and then > iterate over the daily forecasts for the necessary number of periods to > obtain weekly, monthly, or quarterly predictions > of the volatility. The forecasting literature refers to the first approach as > “direct” and > the second as “iterated” (Marcellino, Stock, and Watson (2006))." > http://www.unc.edu/~eghysels/papers/Var_9.pdf > > I am looking to use this "iterated" approach to make a long term forecast. > > The authors do not appear to be referring to a simulation, but rather are > making an out of sample iterative forecast that ends up cumulatively giving > them a forecast for up to 30 days ahead. > > I can see that this could be done in rugarch by using an R loop, stepping > forward out of sample one day at a time. At each step of the loop, one would > call ugarchfit, then call ugarchforecast with a one day horizon. Then for the > next iteration of the loop in R, one would augment the data by the result of > the just-performed forecast, and re-fit and re-forecast etc. > > However, this might be slow so I was just wondering if there is a > rugarch-built-in way of doing this without needing the outer loop in R. > > ugarchforecast does offer n.ahead forecasts, but states that n-step ahead > (n>1) forecasts are based on the unconditional expectation of the models, > which does not seem to be the same thing as these authors are suggesting. > > I just have the feeling that I am missing something. > > THANK YOU for any comments and also for providing this incredibly > comprehensive package! > > _______________________________________________ > R-SIG-Finance@r-project.org 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. > _______________________________________________ R-SIG-Finance@r-project.org 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.
