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Hi Fred,
I have seen you refer to "intelligent optimization" in previous messages.
Honestly, I can't claim to know very much about it, but I am guessing that
you have determined your PSO approach to be the most feasible method of
attacking this for the time being? I downloaded your original version when
you first posted it, but have not been able to look at it yet.
Unfortunately, with a full-time job and the need to concentrate on my trades
at night, I had to pretty much abandon the idea of exploring new approaches
a while back due to lack of time.
The good news (for me, anyway :-) is that within a month or two, I will
have moved on to warmer climes and full-time trading, at which point I will
be able to resume coding on a few ideas that I have.
I am actually very interested in optimization. You may recall that I wrote a
DLL a year or two ago which automatically returns the optimal value of
several built-in indicators for each individual stock. At the time, this
approach was roundly denounced by some of the more experienced traders, and
in fact, I actually tried it for a while, with only mediocre results. But
based on these results, I have some ideas/plans for refining and backtesting
this approach, which I have put on hold for now because it looks like a
major coding job. The results, of course, remain to be seen, but when the
time comes, I would be very interested in hearing your opinion and, if you
think you might be interested, possibly getting your feedback on ways to
improve it via these intelligent optimization and/or sensitivity testing
methods. OK, getting late now here, time to look at some charts. Thanks
again for the code below, and looking forward to your response!
Steve
----- Original Message -----
From: "Fred" <ftonetti@xxxxxxxxxxxxx>
To: <amibroker@xxxxxxxxxxxxxxx>
Sent: Tuesday, April 05, 2005 12:10 AM
Subject: [amibroker] Re: Optimizing & Robustness of single parameters
>
>
> The next for systems w/more then 2 parameters where exhaustive search
> is not feasible is to incorporate sensitivity testing of parameter
> values in the optimization process so that one winds up with a
> relatively insensitive group of parameter values. This IS doable
> using an intelligent optimization process.
>
> --- In amibroker@xxxxxxxxxxxxxxx, "Steve Dugas" <sjdugas@xxxx> wrote:
>> Thanks Fred - very nice idea!
>>
>> FWIW, I just realized that Herman sent the code for his graphs in a
>> follow-up message to the original. Here it is for anyone that might
> be
>> interested.
>>
>> Steve
>>
>> ----- Original Message -----
>> From: "Fred" <ftonetti@xxxx>
>> To: <amibroker@xxxxxxxxxxxxxxx>
>> Sent: Monday, April 04, 2005 9:22 PM
>> Subject: [amibroker] Re: Optimizing & Robustness of single
> parameters
>>
>>
>> >
>> >
>> > For systems with a single parameter this is of course fine ...
>> >
>> > For systems with more then 2 two parameters where the 3d plots
> are no
>> > longer of great use it's a simple matter to generate random data
>> > points in the +/- n% range of what appears to be the optimum
> value to
>> > see how sensitive or not the parameter values actually are i.e.
>> >
>> > Original System where the default values are assumed to be optimum
>> > but sensitivity is unknown ...
>> >
>> > X = Optimize("X", 10, 1, 20, 1);
>> > Y = Optimize("Y", 100, 1, 200, 1);
>> > Z = Optimize("Z", 1000, 1, 2000, 1);
>> >
>> > Sensitivity Tester for +/- 10%
>> >
>> > Senstivity = Optimize("Sensitivity", 1, 1, 5000, 1);
>> >
>> > X = Round((Random() - 0.5) * 2.99) + 10;
>> > Y = Round((Random() - 0.5) * 20.99) + 100;
>> > Z = Round((Random() - 0.5) * 200.99) + 1000;
>> >
>> > The results based on whatever fitness metric interests you can be
>> > observed and sorted in the output of optimization and/or can be
>> > exported for further statistical analysis (distribution) in Excel.
>> >
>> > --- In amibroker@xxxxxxxxxxxxxxx, "Steve Dugas" <sjdugas@xxxx>
> wrote:
>> >> Hi Natasha,
>> >>
>> >> Here is the entire message intact, with thanks to Herman.
>> >>
>> >> Steve
>> >>
>> >> -----------------------------------------------------------------
> --
>> >>
>> >> In addition to using 3D surface maps to evaluate the Robustness
> of
>> > two or more parameters you may consider assessing the Robustness
> and
>> > across-market dependency of single parameters over a Watch list.
>> >>
>> >> You can do this by superimposing equity lines for different
>> > parameter values to see whether they track over time (fan-out) .
> This
>> > is a far better method for evaluating systems and finding stocks
> than
>> > picking a high equity from the Optimization result table. If the
>> > equity ratios remain approximately constant your parameters are
> more
>> > Robust than if the Equities do not track.
>> >>
>> >> In my example I use Steve Karnish's CMO5 system (symmetrical
>> > triggers). To test this method on your own trading system you
> should
>> > substitute your own code inside the curly brackets of the System()
>> > function and substitute the variable named "TestParameter" for the
>> > parameter you like to evaluate. Here is a typical chart showing
>> > robust behavior:
>> >>
>> >>
>> >>
>> >> Here is a chart for a system that may be over optimized and lacks
>> > robustness:
>> >>
>> >>
>> >>
>> >>
>> >> Things to look for:
>> >>
>> >> 1) Over-optimization: High profits but Equity lines move all over
>> > the place.
>> >> 2) Robustness: Equity lines "fanout" keeping the system
> profitable
>> > under most TestParameter values
>> >> 3) Synchronized dips; if all equities dip you can create an
> Equity-
>> > composite and use it to qualify signals.
>> >> 4) Stepping through the stocks in you workspace you can observe
>> > stock-synchronization
>> >> 5) Is the optimum value optimum over time?
>> >> 6) Straight equity lines
>> >>
>> >> Happy trading,
>> >>
>> >> Herman
>> >>
>> >>
>> >> Yahoo! Groups Sponsor
>> >> ADVERTISEMENT
>> >>
>> >>
>> >>
>> >>
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>> >>
>> >> ----- Original Message -----
>> >> From: Natasha !!
>> >> To: amibroker@xxxxxxxxxxxxxxx
>> >> Sent: Monday, April 04, 2005 1:02 PM
>> >> Subject: [amibroker] Optimizing & Robustness of single
> parameters
>> >>
>> >>
>> >> Hi,
>> >> Just going over the archieves and i dug out a mail i
> didnt
>> > quite well understand:
>> >> Since the attachments are not stored in the usergoups any graph
>> > to illustrate the same would be much obliged;
>> >>
>> >> Thanks.
>> >>
>> >> -- N !!
>> >>
>> >>
>> >> In add From: "Herman van den Bergen" <psytek@>
>> >> Date: Thu Sep 4, 2003 9:44 am
>> >> Subject: Optimizing & Robustness of single parameters ition to
>> > using 3D surface maps to evaluate the Robustness of two or more
>> > parameters you may consider assessing the Robustness and across-
>> > market dependency of single parameters over a Watch list.
>> >>
>> >> You can do this by superimposing equity lines for different
>> > parameter values to see whether they track over time (fan-out) .
> This
>> > is a far better method for evaluating systems and finding stocks
> than
>> > picking a high equity from the Optimization result table. If the
>> > equity ratios remain approximately constant your parameters are
> more
>> > Robust than if the Equities do not track.
>> >>
>> >> In my example I use Steve Karnish's CMO5 system (symmetrical
>> > triggers). To test this method on your own trading system you
> should
>> > substitute your own code inside the curly brackets of the System()
>> > function and substitute the variable named "TestParameter" for the
>> > parameter you like to evaluate. Here is a typical chart showing
>> > robust behavior:
>> >>
>> >> Chart for the above and for the below
>> > explanation.Thanks ???
>> >>
>> >> Here is a chart for a system that may be over optimized and
> lacks
>> > robustness:
>> >>
>> >>
>> >>
>> >> Things to look for:
>> >>
>> >> 1) Over-optimization: High profits but Equity lines move all
> over
>> > the place.
>> >> 2) Robustness: Equity lines "fanout" keeping the system
>> > profitable under most TestParameter values
>> >> 3) Synchronized dips; if all equities dip you can create an
>> > Equity-composite and use it to qualify signals.
>> >> 4) Stepping through the stocks in you workspace you can observe
>> > stock-synchronization
>> >> 5) Is the optimum value optimum over time?
>> >> 6) Straight equity lines
>> >>
>> >> Happy trading,
>> >>
>> >> Herman
>> >>
>> >>
>> >>
>> >>
>> >> Warm regards,
>> >> Natasha !
>> >>
>> >>
>> >>
>> >>
>> >> -----------------------------------------------------------------
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>> >>
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>> >>
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>> >>
>> >>
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