[R-SIG-Finance] help with egarch prediction

[Patrick Burns]

Alexios has given a computational reason
for needing more data, but there is an
economic reason as well -- 30 months is
not enough data to estimate a garch model.

For daily data I regard 1000 observations
as the absolute minimum to get any sort of
reasonable estimate.

I think it would be better to avoid the
estimation step.  Here's what I would do
in this situation:

1.  Get a "standard" set of parameters for
the garch model.  I'm not sure what those
would be for monthly data.  (You can think
of this as a Bayesian estimate with a very
narrow prior.)

2.  Given the fixed parameters and the
variance of the known data, solve for the
intercept.

3.  Do the prediction with these parameters.
It is just a bit of arithmetic.

On 23/11/2011 09:33, alexios wrote:
> As far as rugarch is concerned, the restriction is there for a reason:
> It is highly unlikely that the solver will converge with anything less
> than 100 points, and even then, what inference you expect to make with
> so little data, let alone confidence to perform a forecast is beyond me
> (the ugarchdistribution function which simulates and fits GARCH models
> given a parameter set, for different window sizes, can be used to better
> understand this point).
> Having said that, the software is open source...open it up, see the
> source and make the changes you want (hint: the 15th line of code in the
> file 'rugarch-egarch.R' can be commented out to remove the restriction).
>
> Regards,
> Alexios
>
>
> On 23/11/2011 07:16, hemsam wrote:
>> Hi,
>>
>> Problem : Need to predict the subsequent month vol using the past 30
>> month
>> observations
>>
>> Tried the rugarch package but there is a limitation which says that
>> you need
>> to have atleast 100 observations
>>
>> In the fGarch package, one has to use OX interface which does not come
>> free
>>
>> In the egarch package, one can fit an egarch model with less than 100
>> data
>> points but then there is no predict function which helps in
>> forecasting the
>> one-step ahead forecast
>>
>> Appreciate your help and guidance in coming up with a solution for the
>> problem
>>
>> Regards
>>
>> --
>> View this message in context:
>> http://r.789695.n4.nabble.com/help-with-egarch-prediction-tp4098716p4098716.html
>>
>> Sent from the Rmetrics mailing list archive at Nabble.com.
>>
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-- 
Patrick Burns
patrick at burns-stat.com
http://www.burns-stat.com
http://www.portfolioprobe.com/blog
twitter: @portfolioprobe