Solved – the difference between GAS ( Generalized Autoregressive Score) model and a GARCH


I am trying to analyze some data about Brent Oil volatility. So far I have managed to fit a GARCH(1,1) model and an EGARCH. However, someone has recommended to use a GAS model, Generalized Autoregressive Score model, GAS Model webpage. But the problem is that I don't see clear when I should use this model, why and what's the difference with a GARCH.

I'd really appreciate if you could give some insight about it!!

Best Answer

A GARCH model is a special case of a GAS volatility model when the measurement density is normal. When the measurement density is non-normal, the corresponding score that drives the model will be different. For example, using a t-distribution leads to 'trimming' of heavy-tailed observations, whereas using a GED distribution leads to 'Winsorization'. The normal score - aka the GARCH score- reacts linearly with respect to the residuals so does not have a similar robustness property.