[R] calibration of Garch models to historical data

[R. Michael Weylandt]

This might be more of a question for R-SIG-Finance and followup should
probably be there, but you might get a start with the rugarch package.

Michael

On Wed, May 2, 2012 at 4:13 AM, Ivette <iva_mihaylova at mail.ru> wrote:
> I have done the usual estimation of GARCH models, applied to my historical
> dataset (commodities futures) with a maximum likelihood function and
> selected the best model on the basis of information criteria such as Akaike
> and Bayes.
>
> Can somebody explain me please the calibration scheme for a GARCH model?
>
> I was not able to find a paper, dealing with exactly this algorithm for my
> case. I only understood that I have to compare the performance of the best
> GARCH model (from the estimation step), fitted to my historical dataset and
> a GARCH simulation (let's abbreviate this Squared Error difference to "E2").
> However, it is not clear to me:
> - with what parameters' values to start this simulation,
> - how many times it is normal to perform it, and
> - what to compare via E2 (maximum likelihood values, or parameter values)
> - how to construct&assess E2 for the GARCH case.
>
> Thank you in advance for your suggestions.
>
> Ivette
>
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