An ideal trading model would not only generate trading signals before a large change in price, but also be able to generate profits during sideways markets.  However, it's a rare model that can excel in both types of markets.  That's where an ensemble system can bridge the gap.

Since ChaosHunter generates a variety of models during optimization, you can select several that work under different conditions and build an ensemble system in NeuroShell Trader.  

First create a model in ChaosHunter.  Once optimization is stopped, go to the apply screen and click on different models and apply them to the training data.  If you see a model you want to keep, give it a unique name.  To create this example, I chose three different ChaosHunter models and named them Signal A, B, and C. 

I displayed these models on the Trader chart by using  an indicator in the External Program and Library Calls category called ChaosHunter Trading Signal.  The chart below shows how the trading signals are different for each model.

The NeuroShell Trader optimizer decided which ChaosHunter signals to use in the trading rules.

Note that this ensemble system differs from others we have featured in our newsletters where two or more trading signals had to be true in order to enter a trade.  For this example, the optimizer in the Trader was set to rule selection and only one rule had to be true in order to enter a trade.  The idea behind this set up was that the Trader's optimizer would select from several diverse models the one trading system that would work in current market conditions.  Optimization should be repeated on a regular basis to select the best model for existing conditions.