[R-SIG-Finance] modeling using the derivative or underlying

[Stephen Choularton]

Hi

I am working on using AI to build models to decide whether or not you 
should be long/short/out of the market.  I am playing with logistic 
models and neural networks at this time, but there are a number of other 
tree based or Bayesian models I could try in due course.

However, I was just wondering if anyone had any comments on which data 
you are best using to build your models on.  Say one is interested in 
the SPI (or SPY): are you better using the index data even though you 
will end up dealing in the future or some other derivative?  What I have 
in mind is that these things don't move in lock-step so there may be 
different information in the data concerning the index and that 
concerning the future of CFD, etc.

If anyone is interested in making a comment I would love to hear it.
-- 
Stephen Choularton Ph.D., FIoD