[R-sig-finance] bayesian signal classifier

paul sorenson sourceforge at metrak.com
Sun Nov 27 08:22:56 CET 2005

The issue I am curious about is how to classify various signals (eg 
price, volume, MACD, etc) into to buy, sell, or hold?

Assuming I could "tokenize" various attributes of signals (value, 1st, 
2nd and 3rd derivatives, crossing, etc), would it be feasible to take 
these as inputs to a (trained) classifier which then outputs some number 
between 0 and 1 representing buy, hold, sell?  The analogy I am thinking 
of is a Bayesian spam classifier.

My background is in engineering and I have only basic statistics 
knowledge.  I have been using R for a couple of years now mostly for 
graphic output.  I have a reasonable grasp of the language but I'm not 
strong on the underlying theory of the statistical functions.

R has a number of packages which deal with Bayesian statistics but I 
don't have the knowledge to join the dots from there to a classifier.

Any pointers would be most welcome.


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