[R-SIG-Finance] fGarch predict

[Spencer Graves]

Hi, Yohan: 

      I want to thank you again for working to improve 'garchFit' and 
the documentation. 

      I wonder if you have time to also improve the documentation for 
'predict.garchFit', including the following example: 

           x <- garchSim()
           fit <- garchFit(~arma(1,0)+garch(1,1), data=x)
           predict(fit)

      Secondarily, I get error messages from garch(1, 0) and garch(0, 1): 

fit01 <- garchFit(~garch(0,1), data=x)
Error in .garchInitParameters(formula.mean = formula.mean, formula.var = 
formula.var,  :
  object "alpha" not found

fit10 <- garchFit(~garch(1,0), data=x)
Error in sum(beta) : invalid 'type' (closure) of argument

      Best Wishes,
      Spencer

babel at centrum.sk wrote:
> 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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