Expost prediction for ARMA or GARCH
On Sun, 19 Dec 2010 01:34:25 +0100, <babel at centrum.sk> wrote:
Dear researchers I would like to ask, if there is a way how to make in R (fGarch,tseries,..) EXPOST prediction(quasi future). Correct me, if I am wrong, but the command predict(x,n.ahead) makes EXANTE predictions(true future prediction) only. In contrast with Eviews, where forecast
function
produces expost results. Another idea, is to divide the testing set into training and validation sets, estimate for example ARMA coefficients for training set and use them with validations set to produce expost predictions. In pseudocode it looks like this: testing_set (1:100) training_set(1:90) validation_set(91:100) arma_coef<-fit(training_set,~arma(1,1)) expost_prediction<- arma_coef * validation_set Is this a way how to produce EXPOST predictions, or my approach is completely wrong? I beleive, there is much easier way how to do it in R, but I just cant find the satysfying solution by myself. Thank you any
help. I believe what you are asking is: "How do I use a pre-set (trained) set of ARMA or GARCH coefficients on a new data set without changing the model?" This is not ex post 'prediction'. The model fitting is ex post. predict is *always* using the current model to predict future movements (ex ante) on observations in the time series that come in after the model is fit. In fGarch, at least, there is no way to do this. See a list post from me approximately one+ year ago asking about predict and pre-fitted values for fGarch, and Yohan's helpful reply on the modifications that would be necessary to fGarch. In any GARCH model, the conditional volatility may be (and usually is) displayed on the prior data. for arma(), I don't know the answer, but I suspect it will involve some coding on your part. Regards, - Brian
Brian G. Peterson http://braverock.com/brian/ Ph: 773-459-4973 IM: bgpbraverock