I'm still testing it, but I can not come to a reasonable conclusion. The hit ratio is quite impressive, but the many small trades with little profit do not compensate for the losses? That was also the reason why I wondered, why every trade return > 0 is to be considered as positive. The NN/ANN is trained to execute also the small trades.

If we cast TradeReturns into 1/0 we get the direction but we lose any information about the expected movement?

I have been searching for long time for the topic "trade returns and/or classification machine learning etc.", but I did not find anything that works profitable with this approach. Fitting a classification model on the binary (0/1) trade results makes sense, because you do not need a trainer and your classes are more balanced. But how do I get that profitable? That's why i switched to forecasting/predicting the next x values, before I discovered Zorro.

But this is not the way how Zorro or all of your examples work.

Maybe I was on the wrong track, what did I misunderstand?