On Tue, Mar 13, 2012 at 9:20 PM, Michael <comtech.usa@gmail.com> wrote:
> on past performance using either grid search or Genetic Algo, you will
find
the overall out-of-sample in the each next period to be poor...

see comments below.

>Therefore, it seems that Genetic Algo is just a replacement of the
optimizer and it's going to be useful in high-dimensional search...

> But it doesn't give "staying power" to the selected model..


The "staying power", or rather stability, has nothing to do with the
optimization algo, but rather with the underlying problem space and your
space descriptor. If your problem space is unstable your space descriptor
should be able to cover this.

I wouldn't declare GA or any other optimization technique as a tool usable
for one type of problem only ..

As Enrico already said, it's not the fault of the optimization technique,
but rather the fault of the model.



[.. snipping 431 lines of quoted text ...]


-- 
Ulrich Staudinger

http://www.activequant.org
Connect online: https://www.xing.com/profile/Ulrich_Staudinger

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