Message-ID: <476F8D6B.3080903@burns-stat.com>
Date: 2007-12-24T10:43:55Z
From: Patrick Burns
Subject: Non-gaussian (L-stable) Garch innovations
In-Reply-To: <f7ecaf330712231610x46dbe4earc2019553065d7bed@mail.gmail.com>
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")
Jos? Augusto M. de Andrade Junior wrote:
>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
>
> [[alternative HTML version deleted]]
>
>
>
>------------------------------------------------------------------------
>
>_______________________________________________
>R-SIG-Finance at stat.math.ethz.ch mailing list
>https://stat.ethz.ch/mailman/listinfo/r-sig-finance
>-- Subscriber-posting only.
>-- If you want to post, subscribe first.
>