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Pierre:
The standard chart patterns are based largely on visual observations
dating back many decades.
I doubt there is little new that can be learned from backtesting the
old gems, but if your student wishes to look into this, start with
Thomas Bulkowski's "Encyclopedia of Chart Patterns." Pattern
testing and highlighting (not the detection of new patterns) software
includes Nava Patterns
( http://www.marketsonline.com/software/patterns.htm ) and
PatternSmasher ( http://www.kasanjianresearch.com/ ).
Truly ground-breaking research in this area would, I expect,
involve neural networks and other tools requiring a great deal of
time to master. I believe Mark Jurik ( http://www.jurikres.com/ )
monitors this list. He would be an excellent source for information
to point your student in the right direction for developing algorithms
to detect patterns.
Keep us posted on your progress.
----- Original Message -----
From: "Pierre A. von Kaenel" <pierre@xxxxxxxxxxxxx>
To: <metastock-digest@xxxxxxxxxxxxxxxxxx>
Sent: Tuesday, November 27, 2001 11:27 AM
Subject: Pattern recognition using EOD quotes
> I've got a student who'll be doing an undergraduate senior thesis this
> spring and have been passing on ideas for thesis topics. One that crossed
> my mind recently is applying basic pattern recognition concepts to
> end-of-day quotes (open-hi-lo-end-volume) to find chart patterns such as
> trend lines, head & shoulders, double/triple tops and bottoms, etc. Would
> anyone know whether the algorithms used in some charting software to find
> some of these basic patterns were developed by trial-and-error methods or
> whether there are known theories or concepts used to devise algorithms? I
> would prefer that the work be based on some known principles of pattern
> recognition rather than based on intuition. Of course, if there isn't any
> applicable theory to use as a foundation, perhaps the student can try to
> develop some basic principles.
>
> Thanks for any input.
>
>
> ***************************************************************
> Pierre A. von Kaenel
> Assoc. Prof., Math & Computer Science Dept.
> Skidmore College
> Saratoga Springs, NY 12866
>
> pierre@xxxxxxxxxxxxx
>
> "Simplify, simplify, simplify" - Thoreau
> ***************************************************************
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