Non-gaussian (L-stable) Garch innovations

Given the model parameters and the starting volatility state,
the procedure (which you can use a 'for' loop to do) is:

* select the next random innovation.

* multiply by the volatility at that time point to get the simulated
return for that period.

* use the return to get the next period's variance using the garch
equation.

So there are two series that are being produced: the return
series and the variance series.


I'm not exactly objecting, but I hope you realize that garch models
variances while stable distributions (except the Gaussian) have infinite
variance.  Hence a garch model with a stable distribution is at least
a bit nonsensical.

Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of S Poetry and "A Guide for the Unwilling S User")

Hi,

Could someone give an example on how to simulate paths (forecast) of a Garch
process with Levy stable innovations (by using rstable random deviates, for
example)?

Thanks in advance.

Jos? Augusto M de Andrade Jr

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