Hi,
Has anybody worked on portfolio optimization using Genetic Algorithm in R?
Could you please share the code and some references on this topic?
Really appreciate your help.
Thanks,
Abhinaba
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R-help@r-
Indeed.
Start here:
http://www.r-bloggers.com/three-tips-for-posting-good-questions-to-r-help-and-stack-overflow/
and then read this:
http://stackoverflow.com/questions/5963269/how-to-make-a-great-r-reproducible-example
Then put some comments into your code about what you think it should do. Oh
Dear Sir/Madam,
I am a PhD candidate and writing my dissertation about portfolio optimization
in R. However, I have some problems with the codes. It always give the
dimension error. Could you help me to fix it?
Yours sincerely,
Here are the codes:
optimization <- function(x) {
mean <- colMe
I would be biased towards using a heuristic, for instance Threshold
Accepting (TA), for solving such a problem. (TA is implemented in
package NMOF. Disclosure: I am the author of that package.) But you will
not find a ready-to-use solution there.
(1) you need an objective function, ie, a fun
Hi,
I'm an R newbie and I've been struggling with a optimization problem for
the past couple of days now.
Here's the problem - I have a matrix of expected payouts from different
stock option strategies. Each column in my matrix represents a different
stock and each row represents the return to th
You could try the fPortfolio package.
Wish helps.
jamaj
2008/7/21, fzp2008 <[EMAIL PROTECTED]>:
>
> How to use R to solve the optimisaton problem
>
> Minimize:
> ½*w^T*omega*w+mu^T*w+c^T(w-w0) for w>w0 long position
> ½*w^T*omega*w+mu^T*w-c^T(w-w0) for w
> W: is the update weight of portfolio
>
How to use R to solve the optimisaton problem
Minimize:
½*w^T*omega*w+mu^T*w+c^T(w-w0) for w>w0 long position
½*w^T*omega*w+mu^T*w-c^T(w-w0) for whttp://www.nabble.com/portfolio-optimization-problem---use-R-tp18570399p18570399.html
Sent from the R help mailing list archive at Nabble.com.
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Hello,
I would like to solve a portfolio optimization problem in R. As far as I
searched, I found the example of "solve.QP" &"portfolio.optim". In my
understanding, both of them are based on given expected return, finding the
minimum variance. Is there a way of doing this in an opposite way?i.e
m
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