I have not used more than 20 signals so far, so I have no ready script for this. The general recipe is this. First examine closely the "neural" function framework in r.h until you have completely understood what it does. Then write your own "neural" function with different NEURAL_TRAIN and NEURAL_PREDICT parts. For NEURAL_TRAIN, collect the signals in an array, and write it to the CSV file instead of the signals from the Data parameter. Then do the same for NEURAL_PREDICT: send the current N signals over to R instead of the 20 signals from the Data parameter. For more than 20 signals you also must use the "Objective" parameter of the advise function, rather than the outcome of the next trade.
Do you think itīs worthless to put more than 20 signals? Because if we are using series like vol[1], vol[2], etc with four signals (ROCP,vol,range...) it seems very poor. I think that more than 20 signals can be interesting because allows us to use exogenous data like COT or sentiment indicators and series.
