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<SPAN
class=531292304-29102003>interesting, do keep us posted. <FONT
face="Courier New" color=#0000ff size=2>thought
theoretically the only thing we gain from more efficient optimization is the
ability to scan a wider parameter value space more quickly, in practice that
might be the difference between things we can do and things we
can't.
<SPAN
class=531292304-29102003>
<SPAN
class=531292304-29102003>I'm still most interested in ways to evaluate the
results of a trading system that predict future return better than equity
growth. keep us posted on any breakthroughs in that area too
(:-)
<SPAN
class=531292304-29102003>
<SPAN
class=531292304-29102003>dave
<BLOCKQUOTE
>
<SPAN
>Hi Ed and Dave
–
<SPAN
>
<SPAN
>I don’t think the
simplex method is applicable in this case. Its use is to solve linear
programming problems by moving along the edge of the convex space defined by
the constraining inequalities. If we had a well formed set of
inequalities, and if we knew the space they defined was convex, and if we knew
the optimal solution was at one of the vertices, then we might try to simplify
the parameter search using the simplex method or something similar.
Unfortunately, none of those three ifs are satisfied for our model development
problem.
<SPAN
>
<SPAN
>I am in the process
of designing and programming a genetic search routine (as a dll plugin) that
will look throughout the search space by itself and keep track of the best
solutions found. It avoids the problem of setting up a x by y by z
optimization that steps through all the possibilities in order. I plan
to be able to specify any optimization complexity, start the processing using
any reasonable values for the optimization variables, and let the search run
by itself. When it times out, counts out, or is interrupted, a list of
the best solutions is available for further testing.
<SPAN
>
<SPAN
>When I get it
working, and if it looks promising, I’ll share the code. But don’t hold
your breath.
<SPAN
>
<SPAN
>Howard
<SPAN
>
<SPAN
>
<SPAN
>
<DIV
>
<SPAN
>-----Original
Message-----From: Dave
Merrill [mailto:dmerrill@xxxxxxx] <SPAN
>Sent: Friday, October 24, 2003 1:29
PMTo:
amibroker@xxxxxxxxxxxxxxx<SPAN
>Subject: RE: [amibroker]
optimization
<SPAN
>
<SPAN
>hadn't heard
of it before, but found some articles describing it. sounds like you're more
familiar than I am with this kind of thing, but if it's helpful,
try:
<SPAN
>
<SPAN
><A
href="">http://flash.lakeheadu.ca/~kliu/simplex.htm
<SPAN
>
<SPAN
>clearly
you're right that reducing the number of combinations tried would improve
processing time. I'm particularly interested in this because my
auto-optimization framework needs to do this independently for each
ticker.
<SPAN
>
<SPAN
>I don't have
the time to code this reference up in AFL, and probably not the math expertise
either. if you do it, please let me know, and I'll look into adding it to the
auto-optimize thing.
<SPAN
>
<SPAN
>dave
<SPAN
>
<BLOCKQUOTE
>
<SPAN
>Since I am playing with the Optimization function
right now I was <SPAN
><FONT
face="Courier New">wondering the following. If you optimize a set op
parameters simultaneously than
the Optimization procedure calculates all <FONT
face="Courier New">possible combinations of variables. There are a number of
techniques that avoid this e.g.
the simplex method. Did
anyone work on such a function?<FONT
face="Courier New">regards, Ed
<SPAN
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