# How to fit a SARIMA + GARCH in R?

I'd like to fit a non stationary time series using a SARIMA + GARCH model. I have not found any package that allow me to fit this model. I'm using rugarch:

model=ugarchspec( variance.model = list(model = "sGARCH", garchOrder = c(1, 1)), mean.model = list(armaOrder = c(2, 2), include.mean = T), distribution.model = "sstd") modelfit=ugarchfit(spec=model,data=y)

but it allow me only to fit an ARMA + GARCH model. Can you help me? Thank you

• I'd settle for an ARIMA + GARCH – Manuel Mar 27 '15 at 10:26

While SARIMA-GARCH is not currently (October 2016) implemented in R as far as I am aware, you can deal with seasonality by including some dummy variables or Fourier terms in the conditional mean model. If you are using the "rugarch" package in R, you can include these terms via the argument external.regressors within the argument mean.model in the ugarchspec function.