# What is the optimal sample size for fitting a GARCH model?

I tried fitting an ARMA(1,1)/GARCH(1,1) model to my data consisting of around 5000 data points but I got significant results in Ljung Box test on standardized residuals and squared residuals. However when I used only the last 3000 data points the model showed much better results with non-significant standardized residuals and squared residuals.

My question is why is this the case?Isn't more data supposed to give better models?If not what is the optimal sample size?

Also please see my unanswered question: Procedure for fitting an ARMA/GARCH Model

• "optimal" with respect to what criterion? – Glen_b Nov 29 '13 at 7:20
• I mean to get a good fit, basically I want to get a good model for my data and might need to adjust my sample size for that. – ankc Nov 29 '13 at 7:33
• Uh, 'good' and 'optimal' are quite different things. Okay, what, for you, constitutes 'good' in this context? – Glen_b Nov 29 '13 at 8:24
• hmm as long as I can get the standardized squared residuals to exhibit no correlation I would consider it a good model. – ankc Nov 29 '13 at 8:54
• @ankc: Reducing the sample size doesn't fix any deficiencies in your model, but only hides them. Why would you want to do that? – Scortchi Nov 29 '13 at 9:33

• @ankc: At a wild guess it's outliers. This is a different question, & one probably better suited to Stack Overflow, R-help, or a more specific software support site. You need to explain the software you're using, including packages (rugarch?), the call, & if possible a reproducible example. – Scortchi Nov 29 '13 at 9:30