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setting persistence upper limit in garchFit()

3 messages · wc90024-email at yahoo.com, Patrick Burns, Brian G. Peterson

#
I don't know the answer to your question,
but I have a guess of what your data are
like.  The sum of the two parameters in
garch(1,1) is essentially telling you the
time it takes for the volatility from a
shock to damp down.  If there is a trend
in the volatility over the time frame of
the data, then the estimation is likely
to "think" that it hasn't seen the volatility
damp down -- hence an infinite waiting
time and a sum of the parameters more than 1.

More data can often help the problem.

Another piece of software whose existence
I'm doubtful of would be a Bayesian estimate
of the model.


Patrick Burns
patrick at burns-stat.com
+44 (0)20 8525 0696
http://www.burns-stat.com
(home of "The R Inferno" and "A Guide for the Unwilling S User")
wc90024-email at yahoo.com wrote:
#
Patrick Burns wrote:
http://cran.r-project.org/web/packages/bayesGARCH/index.html

perhaps?

   - Brian