[R-sig-finance] bayesian signal classifier

Guy Yollin gyollin at insightful.com
Mon Nov 28 19:24:19 CET 2005


I did some research in this area back in grad school and tested a variety of
classical technical analysis indicators and their ability to forecast
in-the-market or out-of-the-market periods based on classification.  Its an
interesting topic.

Implementing a basic classification system is quite straight-forward.  I
would suggest looking at the following sections of V&R (4th edition):
9.1-9.3 Classification Trees
7.2 GLM with binomial data
8.10 Neural Networks

If you're interested in our research report, drop me an email and I'll be
happy to forward it to you.

-- Guy

Guy Yollin
Senior Financial Engineer
Insightful Corporation
gyollin at insightful.com

paul sorenson wrote:

>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.
>R-sig-finance at stat.math.ethz.ch mailing list

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