Neural networks for Stock analysis

Neural Network vs. Cycle Analysis to Predict the Stock Market

The purpose of this research was to compare two statistical methods: one that based on Cycle Analysis, another – on a simple Neural Network. Price and volume data were used to train this particular Neural Network. These statistical forecasts were built using historical data of S&P-500 index for six months (from June 2009 to January 2010).

The charts below shows how actual 5-day performance (yellow line) differ from predicted performances by these two methods. The top half is the comparison of Neural Network prediction, bottom half – Cycle Analysis. Green bars mean buy signals, red – sell*.

Neural Network vs. Cycle Analysis to Predict the Stock Market

Three major conclusions for this particular historical period:

  1. Cycle Analysis prediction gives signals too early, Neural Network prediction – too late.
  2. In average, the prediction by Cycle Analysis showed slightly better accuracy than the one by Neural Network.
  3. It seems logical to combine these two methods to improve the accuracy.

* ) The calculations have been performed by an integrated experimental system that combined two applications: Cycle Analysis predictor SMAP-3 and Neural Network predictor NNSTP-2

Source: Stock Market Forecast and Trading

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