Hello, Yuhan:
If I wanted to get something sensible today, I'd do ordinary least
squares using lm(y~x), the garchFit on the residuals. This will give
you a reasonable answer except that the confidence intervals from "lm"
will not be accurate. I'd want to do normal probability plots of
Hello -
Here's what I'm trying to do. I want to fit a time series y with
ARMA(1,1) + GARCH(1,1), there are also an exogeneous variable x which I
wish to include, so the whole equation looks like:
y_t - \phi y_{t-1} = \sigma_t \epsilon_t + \theta \sigma_{t-1}
\epsilon_{t-1} + c x_t where \
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