# Value-at-Risk formula when using skewed-t distribution

I am trying to find a formula for the skewed-t VaR. For example the VaR formula for a t-distribution is

$$\sqrt{\frac{df-2}{df}} \times \Sigma{t} \times \mbox{quantitle}(t-\mbox{dist}, 0.01) + \mu$$

(Please excuse the messy formula & the sigma(t) denotes a GARCH model)

However I am struggling to do the same for a skewed-t distribution

I am using the rugarch package in R and I am struggling to find out which version of the skewed-t distribution is being used. I went to the fGarch pdf and downloaded the reference ON BAYESIAN MODELLING OF FAT TAILS AND SKEWNESS by C. Fernandez et al., but my lack of Bayesian knowledge means the pdf it says is the Skew-Student is not helping perhaps as much as it should.

Any help would be much appreciated.

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I have $\LaTeX$-ified your formula. Please make sure it is correct. –  chrisaycock Jul 21 '13 at 20:21
Which Skewed-t Distribution are you using? there are many representations.... –  pyCthon Jul 21 '13 at 23:12