Predict Stock Market Values
- by mrlinx
I'm building a web semantic project that gathers the maximum ammount of historic data about a certain company and tries to predict its future market stock values.
For data I have the historic stock values (not normalized), news (0 to 1 polarity) and subjective content (also a 0 to 1 polarity).
What is the best AI system to train and use for this kind of objective?
Is a simple NN with back-propagation training the best I can hope for?
update: Everyone is concerned about the quality of this system. Although I'm pretty sure the system is as good as a random prediction (or even worse), this is a school project around artificial intelligence and web semantics. Therefore I'm only concerned in picking the best kind of train method for the data I have (NN, RBF, SVM, Bayes, neuro-fuzzy, etc). Its not about making money.