I have residuals that I got from an ARMA-GARCH model via
ug_spec <- ugarchspec(distribution.model="std", mean.model=list(armaOrder=c(1,0)),variance.model=list(garchOrder=c(1,1))) ugfit=ugarchfit(spec = ug_spec, data =x) residue=as.numeric(unlist(residuals(ugfit)))
as.numeric(unlist()) is just to get the part of the result I want. First off, was that the correct way to get the residuals off a data that has been fitted to the ARMA(1,0)GARCH(1,1) model?
I have to now check the residuals for any serial dependence, and decided to use
Box.test with the Ljung-Box type:
Box.test(residue, lag=5, type="Ljung", fitdf=1)
fitdf=1 as per the instruction in the vignette to place p+q as the fitdf. The result is this:
Box-Ljung test data: residue X-squared = 15.548, df = 4, p-value = 0.00369
The p-value < 0.05, which doesn't make sense since I've previously detrended and de-seasonalized the data before fitting it to the ARMA-GARCH model (best fit by BIC).
Does this mean that there is, indeed, serial autocorrelation even though I've done all I was supposed to in pursuit to get rid of it, or did I make a mistake in the usage of