User request: NNs predicting pivots (fractals for label density). Run on
the offline stack that demonstrably CAN learn (+2.6pp XAUUSD meta), free
of every historical in-EA training bug: pooled 4-symbol training,
per-symbol norm, scale-free causal features, target = side of current
price the next confirmed Bill Williams fractal lands on, real M1
ask/bid fills, threshold fitted on calib only, pre-registered 2-sigma
net-expectancy gate.
Result: train CE 0.682 (a whisper below the 0.693 coin), and on test no
symbol passes - EURUSD/USDJPY net zero, XAUUSD gross +0.22 pts vs a
larger spread (net -0.30), SP500 net +0.05 +/- 0.45. The gross-positive
tails are index drift plus sub-spread micro-reversion - the tick-flow
decay shape at swing scale. Seventh independent measurement of the same
fact: entry-time direction information is not in these features.
Co-Authored-By: Claude Fable 5 <noreply@anthropic.com>
