The broadest descripion of the idea is early stopping, which is not new in the slightest, and in fact most NN literature mentions it. Early stopping attempts to address the problem with NNs that they are so good at learning that eventually they start to memorise individual data items, which is the familiar problem found in EA optimisation of curve fitting. Early stopping terminates the learning process at a point where hopefully the NN has only learnt patterns, rather than data.
So this is the hypothesis: a profitable NN EA can be developed ...
- If a NN can be trained using an early stopping technique to recognise forex patterns
- If patterns repeat in forex trading, and more importantly, come in clusters
This last point is another key: rather than discarding all technical analysis in favour of a magical NN black box, why not look first for a basic EA strategy which seems to support item 2 above? Its equity curve should show extended periods of profitability which could then be selected by a NN filter, in a similar way that the commonly used long term moving average is used to detect a trending market.
The whole idea is already in MQL5 code, with a number of coding errors which I need to find, which will take some time.
Here's the macro view