Archive for March, 2010

I want to find a simple example for which the NN (Neural Network) can prove that it works. For now to eliminate high frequency randomness I would go for weekly data instead of daily. Being simple means that the input to my NN should be simple. It should be 1 dimension input, or maximum 2 […]

Recently I turned to be pessimistic about daily stock market return prediction made with Neural Networks. There is so much randomness in that that it makes the problem very complex. Giving simple raw daily open/high/low/close/volume data to the technical analysts may give some results, because how the human mind can synthesize patters from the data […]

Other researchers point to the fact that they couldn’t find reliable technical indicators having ‘significant’ prediction power for the SP500 and the Dow, but they could find for less ‘optimal’ markets like the Nasdaq and the Russell 2000. So, I tried my NN testing with adjusted IWM instead of SPY. After 37 tests: (from 2000-2010) […]

Having no success with NN for forecasting next day close prices, I had an idea that I should train my NN based on an effect that is statistically significant. Like this effect: It says that when the 5 day ROC (Rate of Change) of the SPY is > 0, the chance of having an […]