[R-SIG-Finance] help with egarch prediction

[alexios]

The ugarchdistribution function gives the econometric
intuition in terms of parameter distribution and sqrt(N)
consistency by simulation. You choose a set of "true parameters"
to simulate from, for different data lengths, fit the garch model,
and observe the simulated parameter distribution and change in
root mean squared error (of true versus fitted) as the length of
the data increases.


On 23/11/2011 10:29, Patrick Burns wrote:
> 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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>>
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>