Modified Cornish-Fisher VaR

Has anyone done any work on Modified Cornish-Fisher VaR calculations in R?
 

The limitations of VaR in modeling of risk for non-normal distributions 
have been known for quite some time, and this approach seems to hold some 
value over other approaches already implemented in RMetrics like 
Conditional VaR.

I'm trying to replicate the calculation as laid out in: 
Favre, Laurent, and Jose-Antonio Galeano. ?Mean-Modified
Value at Risk Optimization with Hedge Funds.? The Journal
of Alternative Investments, 5 (2002), pp. 21-25.

and presented in a different form in an earlier paper:
Fallon, William. "Calculating Value-at-Risk" 
Working Paper, Wharton, 1996.

Both of these papers rely on calculating traditional VaR (as is done with 
fPortfolio.VaR() from the RMetrics package) and then using a 
Cornish-Fisher Expansion for skew (both papers) or skew and kurtosis 
(Favre 2002) (as is done using the fBasics.skewness() and 
fBasics.kurtosis() functions from RMetrics)

I'm wondering if anyone has already replicated this work in R, and could 
provide a pointer, or alternately if some of the more experienced people 
on this list could render an opinion on which of the Cornish-Fisher 
functions in the core R stats package might be appropriate for this kind 
of analysis.

I would like to implement and share a function for Modified Cornish-Fisher 
VaR, so any assistance would be greatly appreciated.

Regards,

  - Brian