[R-SIG-Finance] Changing (seasonal) conditional distribution in a fGarch model

[PoddyOne]

Hi Alexios 

After having (somewhat) digested the link you sent me to the seasonal
variance models in your package, I'm under the impression that the
conditional distribution is still restricted to being normally distributed
(with varying variance)? I was hoping to use a skewed-normal as the
conditional distribution at certain times of day.

Another thing is that at the bottom of the page you say:

" Another possible direction for expansion would be to treat the diurnal
effect separately for each day of the week."

This is an interesting idea, and is something I thought about, but was a
little uneasy about the ideas that popped into my head about how to go about
this. For example, one simple approach might be (at least in my case) to
transform each hour of the diurnal cycle separately to try and match the
conditional distributions as closely as possible. However, this seems like
it would leave to an overly complicated model.

Cheers



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