Hi Spirit and thanks for your answer, can we discuss it?

If you have Workshop7 in mind I would agree with you. Fixed patterns are searched first (Step 1) and in Step 2 the best matching parameters to catch the learned patterns. A subsequent change of the parameters does NOT change the patterns found here.

In NEURAL training the "next Trade Return / Result" or custom objectives that looks different (to me). Maybe I'm wrong but I think it does not make sense to train an ML model first on certain rules - if you then change these rules after training again. I'll post some code parts, let's see what you (or others) think about this approach.

PEEK is used and DataHorizon = 30...

Code:
while(asset(loop(ASSETS))) 
while(algo(loop(ALGOS))) {

   TakeProfit = optimize(1,1,4,1) * ATR(100);
   Stop       = TakeProfit / 2.0;

   vars dat = series(price());
   vars rsi = series(RSI(dat,5));

   int pos = 0;            // future bar pos
   var fhv = priceHigh(0); // future highest high value
   var flv = priceLow(0);  // future lowest low value
   var obL = -1.0;         // custom objective long, never 0
   var obS = -1.0;         // custom objective short, never 0
		
   if(Train && !is(LOOKBACK)) {

      for(pos=1; pos <= DataHorizon; pos++) {

         fhv = max(fhv,priceHigh(-pos));
         flv = min(flv,priceLow(-pos));		
					
      }

      if(valley(rsi) && flv > (priceClose(0) - Stop) && fhv > (priceClose(0) + TakeProfit)) obL=1.0;
      if(peak(rsi)   && fhv < (priceClose(0) + Stop) && flv < (priceClose(0) - TakeProfit)) obS=1.0;

   }

   var avL = adviseLong(NEURAL+BALANCED,obL,INP,12);
   var avS = adviseShort(NEURAL+BALANCED,obS,INP,12);

}

Starting from the current position (Bar) I'm scanning the next 30 bars for it's lowest and highest values. After that i create a custom objective, if price starts from valley/peak and hits the Takeprofit but not the Stoploss, take this trade / objective = 1 else -1.

Question 1: Changing the TP/SL after i have trained the model with a custom objective makes no sense here?

Question 2: If you use Objective = 0, you will train your model for every positive trade. These often win only by chance, not because a rule is behind these entry's. I have never achieved meaningful results with this method (open a trade on every bar + learning all positive trade returns). What should an ML model generalize here?

Last edited by laz; 01/28/19 02:09.