[R] alpha_1 + beta_1 >1 in GARCH(1,1)

Patrick Burns pburns at pburns.seanet.com
Sun Nov 20 16:24:24 CET 2011

This would have been a more appropriate
question on r-sig-finance.

The short answer is: no, you can't trust
the coefficients.

You don't say how much data you have, but
this situation is common when you don't
have much data (meaning fewer than 2000
daily observations).  The sum of those
two parameters is saying how fast shocks
dissipate (in the variance).  If it looks
like there is a trend in volatility over
the in-sample period, then a reasonable
answer given that information is that the
shocks do not dissipate -- meaning the sum
of the parameters is greater than 1.

On 20/11/2011 10:25, user84 wrote:
> Hi,
> as i suppose to know in a stationary GARCH(1,1) model the sum of alpha and
> beta has to be smaller than 1.
> But if i use the garchfit() function from the package fGarch for my
> timeseries the sum is bigger than 1.
> The adf.test tells me a p-value smaller than 0.01 instead.
> What does this mean for me?
> Can i trust in the coefficients in this case?
> mfg user84
> --
> View this message in context: http://r.789695.n4.nabble.com/alpha-1-beta-1-1-in-GARCH-1-1-tp4088342p4088342.html
> Sent from the R help mailing list archive at Nabble.com.
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Patrick Burns
pburns at pburns.seanet.com
twitter: @portfolioprobe
(home of 'Some hints for the R beginner'
and 'The R Inferno')

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