[R] TSeries GARCH Estimates accuracy

[Patrick Burns]

GARCH models are notoriously hard to optimize, so I'm not terribly
surprised.

The first thing is to make sure that your reference results are really 
better
than what you are getting in R.  Perhaps they have improved it, but the
last time I looked at garch in S-PLUS, it did not necessarily give good
results.  I don't know anything about the SAS routine.

The first-aid approach to getting better estimates is to start the 
optimization
at various locations and pick the best one you get.  One starting point 
might
be near to (.05, .9) -- that is, .9 times the lagging conditional 
variance. 
Another would be to restart from where the routine ended.  From the help
file for 'garch' it says that the default starting point is with values 
close to
zero -- that is not a very good starting point.

A more involved approach would be to change the routine so that the 
intercept
is derived from the desired asymptotic variance (usually the unconditional
variance) and the other parameter estimates.  Optimizers tend to be much
happier with this problem.

The R-sig-finance list is a more likely spot for a discussion like this.

Patrick Burns

Burns Statistics
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")


Sanjay Kumar Singh wrote:

>Hi,
>
>I am trying to fit a GARCH(1,1) model to a financial timeseries using the 'garch' function in the tseries package. However the parameter estimates obtained sometimes match with those obtained using SAS or S-Plus (Finmetrics) and sometimes show a completely different result. I understand that this could be due to the way optimization of MLEs are done, however, I would appreciate any help to obtain consistent results using R. 
>
>Also is there any garch simulation function available other than garchSim from fseries package?
>
>Thanks in advance,
>Sanjay
>
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