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Hi,
True, unfortunately. A simple way to look at it is by counting the number of
combinations tested. For example, say I am optimizing on 2 variables, each
with 10 steps. If I optimize them together, I am testing 10 x 10 or 100
combinations. If I optimize them one at a time, I am testing 10 + 10 or 20
combinatins. The second way will certainly be faster, because I am only
testing 20% of the possible combinations. The true optimal results are
likely to lie somewhere in the 80% of combinations that I have not tested..
The more variables used, the % of possible combinations actually tested
continues to drop. For 3 variables, 30/1000 or only 3%. For 4 variables,
40/10,000 or only 0.4 %, etc...
Steve
----- Original Message -----
From: "DIMITRIS TSOKAKIS" <TSOKAKIS@xxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
Sent: Thursday, November 13, 2003 12:47 AM
Subject: [amibroker] Re: Help on automating optimization (genetic
algorithms)
> Gary,
> The procedure you describe does not make any sense.
> In the simple example
> x=Optimize("x",10,10,100,10);
> b=Optimize("b",10,10,50,10);
> s=Optimize("s",50,50,90,10);
> Buy=Cross(StochD(x),b);
> Sell=Cross(s,StochD(x));
> the optimal solution is [30,20,80]
> If I optimize first the x, ie
> x=Optimize("x",10,10,100,10);
> b=10;//Optimize("b",10,10,50,10);
> s=50;//Optimize("s",50,50,90,10);
> Buy=Cross(StochD(x),b);
> Sell=Cross(s,StochD(x));
> [optimal x=80]
> then the b, ie
> x=80;//Optimize("x",10,10,100,10);
> b=Optimize("b",10,10,50,10);
> s=50;//Optimize("s",50,50,90,10);
> Buy=Cross(StochD(x),b);
> Sell=Cross(s,StochD(x));
> [optimal b=10]
> and finally the s, ie
> x=80;//Optimize("x",10,10,100,10);
> b=10;//Optimize("b",10,10,50,10);
> s=Optimize("s",50,50,90,10);
> Buy=Cross(StochD(x),b);
> Sell=Cross(s,StochD(x));
> [optimal s=90]
> I will have the [80,10,90] solution, which is far from the actual
> optimal [30,20,80]
> Unfortunately, the optimal[x,b,s] *is not* the optimal[optimal[optimal
> [x],b],s], consequently this procedure is wrong from the beginning.
> There is no chain rule for composite optimizations and you will have
> very few probabilities to find the optimal.
> Another basic issue: You do not even have the
> optimal[optimal[x],y] equal to optimal[optimal[y],x]
> property, both will be far from the optimal[x,y] and you can not even
> interchange the priorities.
>
> Herman,
> The results of cascade optimizations will not give the optimal
> result, even if you save some time. As for this last property, I do
> not think you save any time, optimization is an internal loop, as far
> as I understand...
> Dimitris Tsokakis
>
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Herman vandenBergen" <psytek@xxxx>
> wrote:
> > You can optimize using for() loops and examples of this method have
> been
> > posted on the list. This would allow you to optimize one parameter
> first in
> > the first loop-optimization and then go on the the next loop-
> optimization
> > using the result of the first loop-optimization in your
> calculations. This
> > way you will save lots of time and you can optimize an unlimited
> number of
> > parameters without looking at billions of iterations.
> >
> > happy tinkering,
> > herman.
> >
> >
> > -----Original Message-----
> > From: Gary A. Serkhoshian [mailto:serkhoshian777@x...]
> > Sent: November 13, 2003 7:00 AM
> > To: amibroker@xxxxxxxxxxxxxxx
> > Subject: [amibroker] Help on automating optimization (genetic
> algorithms)
> >
> >
> > Hi all,
> >
> > I should preface this e-mail by saying that I'm not trying to
> create a
> > Rube Goldberg as I can go through the process ourlined below
> manually. So,
> > if what I'm suggesting requires a Rube Goldberg type solution let
> me know,
> > and I'll let it go.
> >
> > Essentially what I'm doing with optimizations over multiple
> variables is
> > prioritizing variables on importance, and optimizing one variable
> at a time
> > leaving the others static. I just keep iterating through all the
> variables
> > until things stabilize in terms of standard measures. The cocktail
> party
> > term is genetic algorithms, but between us it's necesary as
> optimizing over
> > multiple variables (4+) will either take too long or worse cause
> AmiBroker
> > to crash due to memory issues.
> >
> > Here's the punchline. Can you all give some input on ways to
> program this
> > in afl so as to automate the process outlined above rather than me
> manually
> > iterating through as it is labor intensive.
> >
> > Many thanks,
> > Gary
> >
> >
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