Hi

1. meanForecast holds predicted values of 'ret'
2. on top of having the predicted values of 'ret' (see 1), you can compute confidence intervals as you suggested
3. meanError is standard deviation of the mean prediction as computed by the underlying predict.Arima function, which does not take into account the volatility structure (i.e. the garch part) of your model. It just takes the estimated coefficients for the mean equation from your model, computes their standard errors (i.e. it disregards standard errors from your estimated arma garch model) and then computes the standard deviation of the mean prediction. Summing up, you can forget about meanError.

In forecasting the mean of a series, garch models provide you with a more efficient estimates of the mean parameters and with consistent estimates of the covariance matrix. However, the garch parameters does not enter into the mean prediction.

Regards,

Michal


----- Original Message ----
From: "babel@centrum.sk" <babel@centrum.sk>
To: R-SIG-Finance <r-sig-finance@stat.math.ethz.ch>
Sent: Saturday, February 16, 2008 11:55:13 AM
Subject: [R-SIG-Finance] fGarch predict

Hello
I want to predict the future values of time series with Garch
When I specified my model like this:
library(fGarch)
ret <- diff(log(x))*100
fit = garchFit(~arma(1,0,0)+garch(1, 1), data =ret)
predict(fit, n.ahead = 10)

 meanForecast  meanError standardDeviation
1    0.01371299 0.03086350        0.03305819
2    0.01211893 0.03094519        0.03350248
....................................................................................

I know that if I use fit = garchFit(~garch(1, 1), data =ret) I  got constant mean, so trherefore I include amra term to move with mean

Iam not sure what values are hiding in this output. 
1. Does menForecast hold my future predicted values?
2.Or I am able to just compute the confidence intervals for my prediction like meanForecast +-2*standardDeviation  ??
3Or I need to compute the future values like yt=meanForecast+meanError*sqrt(standardDeviation)  ???
My return looks like standard return series with plus and minus values, 
[748,]  0.008184311  
[749,]  0.024548914  
[750,] -0.008182302

so I hope I would get similar prediction to this return, not just a postive mean constant.Sorry,  I know that Garch models are for volatility modelling, but I still doesnt find how to use that volatility for forecasting future values. Short example with 5 step ahead prediction will surely help.
Thank you

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