Hi,

Although my doubt is pretty,as i m not from stats background i am not sure
how to proceed on this.

Currently i am doing a forecasting.I used ARIMA to forecast and time series
was volatile i used garchFit for residuals.
How to use the output of Garch to correct the forecasted values from ARIMA.

Here is my code:

###delta is the data

fit<-arima(delta,order=c(2,,0,1))

fit.res <- resid(fit)
##Check for Residuals
acf((fit.res-mean(fit.res))/sd(fit.res))
acf(((fit.res-mean(fit.res))/sd(fit.res))^2)
fit.fore = predict(fit, n.ahead=test)

##Use ARIMA GARCH To fit residuals from ARIMA Model
1.
fitted.gar<-garchFit(formula =~arma(2,1)+garch(1,1),data=*fit.res*,cond.dist
= "std",trace=FALSE)
sresi=fitted.gar@residuals/fitted.gar@sigma.t   ###Standardised Residuals
acf(sresi)
acf(sresi^2)
fore.res<-predict(fitted.ga, n.ahead=test)

OR
2.
fitted.gar<-garchFit(formula =~arma(2,1)+garch(1,1),data=*delta*,cond.dist =
"std",trace=FALSE)
sresi=fitted.gar@residuals/fitted.gar@sigma.t   ###Standardised Residuals
acf(sresi)
acf(sresi^2)
fore.res<-predict(fitted.ga, n.ahead=test)

My Question is
1. How to use fore.res(Result from Garch Model) to change fit.fore
(Forecasted values from ARIMA)
2.Out of 1 and 2 for GARCH which one is correct.Pretty confused.Shud we need
to use the residuals got from ARIMA Model or the series directly ?

Regards,
Raghav

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