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

[PoddyOne]

Hi there, 

I'm working with a time series that has a clear seasonal component in it's
conditional distribution. Not only does the variance increase at certain
parts of the seasonal cycle, but also the distribution becomes skewed.

I would like to fit an fGarch model to this time series, but with a
conditional distribution which depends on a dummy variable. I was wondering
if anyone knew if this was possible in fGarch or any of the similar
packages?

/(As an aside, I recognise that this may not be the easiest way to go about
modelling this. For a little more detail: This is a time series with a
strong diurnal cycle in it. The series has been 'detrended' and is
stationary at least under the usual metrics. However, still clearly during
the midnight hours, the residuals are strongly positively skewed. I have
tried transforming the series, but the large disparity in both the skew and
scale see to prohibit this working nicely.

Any other suggestions are welcome)/



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