[R-sig-finance] bayesian signal classifier
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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