I try to estimate a component sGarch model with the rugarch package in R. My goal is to extract the short-run and long-run volatility components of any time series. I am not interested in the coefficients.
Does someone here know how I get such an output?
I know that
sigma(fitted model) is giving me $\sigma^2_t$ but I cannot get an output for $q_t$. If I use
uncvariance(fitted model), it is just giving a single number.
Thanks in advance!
Here is some code:
# With an arbitrary data input, here I used some spot rate data garchspec <- ugarchspec(variance.model = list(model = "csGARCH", garchOrder = c(1,1))) garchfit <- ugarchfit(garchspec, SpotRates) print(garchfit) sig <- sigma(garchfit) sig2 <- uncvariance(garchfit)
And a description of the model (taken from 'Introduction to the rugarch_package'):