I am working on building a Neural network for technical analysis of stocks. The input I have is the open price and two (so far) technical indicators : RSI and William's R - for the past 2 years. I can include more data points and features going ahead but as of now I just need to test the concept. I have the following questions on this:
I had decided to classify stocks into 3 categories : BUY, SELL and HOLD using this model. Is this formulation appropriate ? If yes, is there a way to generate these target labels for training ? If no, what should be the appropriate target ?
The neurons fire after a certain threshold but many indicators require a different interpretations than just a threshold limit. Does this need to be corrected for in the model or will it not have any impact ? If yes, what approach should be used to correct for it ?
Any help would be much appreciated.