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Basically the experiment is way too accurate so I think data from the "future" might be being used to train the SVM. I've looked to see if the data is in the correct order and I think it is. I think the problem may be that I am using windowing incorrectly but it's hard to verify since the attributes' are hard to scrutinize (especially since they have unhelpful labels and after normalization the values themselves are inscrutable). .991 correlation seems like it should be impossible for 10-day stock market forecasting so I'm sure there is an error somewhere.
My experiment is basically a very simple SVR experiment on stock market data, following the basic guidelines for such a system recommended in the thread "Prediction (Forecasting ) with RM" and the LIBSVM "practical guide to SVM classification".