There is a new blog post that is pertinent to this question:
http://www.portfolioprobe.com/2012/07/23/a-comparison-of-some-heuristic-optimization-methods/
Pat
On 18/07/2012 21:00, Cren wrote:
# Hi all,
# consider the following code (please, run it:
# it's fully working and requires just few m
Roger Koenker-3 wrote
>
> 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.uiu
Hans W Borchers wrote
>
> The most robust solver for non-smooth functions I know of in R is
> Nelder-Mead
> in the 'dfoptim' package (that also allows for box constraints).
>
> First throw out the equality constraint by using c(w1, w1, 1-w1-w2) as
> input.
> This will enlarge the domain a bit,
Roger Koenker-3 wrote
>
> 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.uiu
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
Cren bancaakros.it> writes:
>
The most robust solver for non-smooth functions I know of in R is Nelder-Mead
in the 'dfoptim' package (that also allows for box constraints).
First throw out the equality constraint by using c(w1, w1, 1-w1-w2) as input.
This will enlarge the domain a bit, but com
# 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) {
# Hi all,
# consider the following code (please, run it:
# it's fully working and requires just few minutes
# to finish):
require(CreditMetrics)
require(clusterGeneration)
install.packages("Rdonlp2", repos= c("http://R-Forge.R-project.org";,
getOption("repos")))
install.packages("Rsolnp2", repos=
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