There are obviously a large variety of non-smooth problems;
for CVAR problems, if by this you mean conditional value at
risk portfolio problems, you can use modern interior point
linear programming methods. Further details are here:
http://www.econ.uiuc.edu/~roger/research/risk/risk.html
Roger Koenker
rkoen...@illinois.edu
On Jul 18, 2012, at 3:09 PM, Cren wrote:
> # Whoops! I have just seen there's a little mistake
> # in the 'sharpe' function, because I had to use
> # 'w' array instead of 'ead' in the cm.CVaR function!
> # This does not change the main features of my,
> # but you should be aware of it
>
> ---
>
> # The function to be minimized
>
> sharpe <- function(w) {
> - (t(w) %*% y) / cm.CVaR(M, lgd, ead, N, n, r, rho, alpha, rating)
> }
>
> # This becomes...
>
> sharpe <- function(w) {
> - (t(w) %*% y) / cm.CVaR(M, lgd, w, N, n, r, rho, alpha, rating)
> }
>
> # ...substituting 'ead' with 'w'.
>
> --
> View this message in context:
> http://r.789695.n4.nabble.com/The-best-solver-for-non-smooth-functions-tp4636934p4636936.html
> Sent from the R help mailing list archive at Nabble.com.
>
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