[R-SIG-Finance] "ugarchfit" function of "rugarch" package needs at least 100 data points.

[Patrick Burns]

I agree with Eric.  His suggestion is simple
and likely to give about as good of an answer
as possible.

On 09/10/2012 21:22, Eric Zivot wrote:
> While GARCH parameter estimates can be quite variable (as Pat has nicely
> shown), the resulting volatility forecasts tend to be much more stable (at
> least in the short term). If the goal is short-term vol forecasting then one
> doesn't really care too much about the GARCH point estimates. The important
> long-term parameters are the unconditional vol and the persistence of the
> GARCH process as these dictate where and how fast the vol forecasts evolve.
> For the short term, most GARCH forecasts look a lot like simple EWMAs. So if
> you only have 100 obvs and want to get a simple short-term forecast, use an
> EWMA. That's the riskMetrics approach.
>
> -----Original Message-----
> From: r-sig-finance-bounces at r-project.org
> [mailto:r-sig-finance-bounces at r-project.org] On Behalf Of Patrick Burns
> Sent: Tuesday, October 09, 2012 1:05 PM
> To: r-sig-finance at r-project.org
> Subject: Re: [R-SIG-Finance] "ugarchfit" function of "rugarch" package needs
> at least 100 data points.
>
> The blog post:
>
> http://www.portfolioprobe.com/2012/09/17/variability-of-garch-estimates/
>
> shows how variable garch results are using
> 2000 daily observations.
>
> Even if there is a way to get your model fit, I doubt that it would mean
> very much.
>
> If you do find a way, I would suggest that you create multiple datasets that
> are simulations of the model the same size as your data.  Then estimate the
> model on the simulations and see how variable those model estimates are.
> They will be very variable, I predict.
>
> Pat
>
> On 09/10/2012 19:58, Tanvir Khan wrote:
>> Right now I'm trying to fit a GJR Garch model on the inflation rate of
>> my country, Bangladesh, but the problem is the function "ugarchfit" of
>> the "rugarch" package requires at least 100 data points to run. I have
>> yearly
>> (12 months average) data and my country is not even 50 years old! So,
>> is there any way to use this function to fit a data with less than 100
>> observations? Any type of suggestion will be extremely helpful.
>>
>
> --
> Patrick Burns
> patrick at burns-stat.com
> http://www.burns-stat.com
> http://www.portfolioprobe.com/blog
> twitter: @portfolioprobe
>
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-- 
Patrick Burns
patrick at burns-stat.com
http://www.burns-stat.com
http://www.portfolioprobe.com/blog
twitter: @portfolioprobe