I have a few questions regarding GARCH modelling and forecasting and it would be great if someone could help me. I am modelling the log return of oil spot prices using various GARCH models: GARCH, APARCH, EGARCH... and I am trying to forecast the prices. I found using ACF and PACF plots that the best model for the series is ARMA(0,1) and then the best model for the error term follows GARCH(1,1) or APARCH(1,1) etc

Here are my questions:

1) garch1<-garchFit(~arma(0,1)+garch(1,1),data=brentlog,trace=FALSE,include.mean=TRUE) predict(garch1,n.ahead=25) I have a doubt whether I am forecasting the volatility of the prices or the actual values of return?

2) Since I am not looking at options, there is no point forecasting the volatility right? because it won't tell me whether prices will go up or down

3) Since I have an ARMA(0,1) for my model, my forecasts will always be constant and if I don't include a mean in the model then the forecasts are the same using egarch, garch, aparch or any model: it is 0. So is there a point of using those different models in this case?

thanks a lot!

  • $\begingroup$ Anyone has any idea? lets exchange opinions $\endgroup$ Jun 2, 2015 at 22:31
  • 1
    $\begingroup$ Hi @user3384794! Which is the R package in R? I know fGarch in R but the piece of code you wrote above down seems coming another package up. $\endgroup$
    – Quantopik
    Jun 12, 2015 at 17:09


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