rugarch only supports ARFIMA(p,d,q) models.
1. First try fitting the returns using the "forecast" package which
supports SARIMA.
2. If you are satisfied with the residuals, pass them to rugarch (with
armaOrder=c(0,0), include.mean=F and nothing else).
Alexios
On 30/09/2014 20:11, aschmid1 wrote:
Hi,
I'm working with a sample that has a strong weekly seasonality and
wonder if rugarch can handle a multiplicative ARIMA(p,d,q)P,D,Q)s. I
tried additive seasonal model for which I simply put 51 dummy variables
as external regressors into the mean but, alas, the model does not
converge (rugarch-->warning: failed to invert hessian) with or without
dummies.
Here is my script:
spec1111 = ugarchspec(variance.model = list(model = "sGARCH", garchOrder
= c(1,1)), mean.model = list(armaOrder = c(1,1), include.mean = T,
external.regressors = X), distribution.model = "sged")
fit1111<-ugarchfit(data=inp[,2], spec=spec1111, solver = "hybrid",
solver.control = list(trace = TRUE, tol=1e-4, delta=1e-6))
Thanks! Alec
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