Momentum-dispersion-concentration governor (risk-overlay)

The question

The research methodology itself — the pre-registration rigor protocol applied to every hypothesis below.

How it was tested

The hypothesis, its exact trigger, the outcome it predicts, and the pass/fail bar were written down and cryptographically hash-locked before any data was tested, then held through a mandatory cooling-off period. The backfill ran exactly once against those frozen parameters — no re-tuning, no curve-fitting — using adversarial statistics (stationary-bootstrap confidence intervals, multiple-testing correction, purged cross-validation with an embargo, and walk-forward out-of-sample splits). The specific trigger thresholds are proprietary and omitted here.

The outcome

RAN 2026-07-06 (attended) → INFO_GRADE / DO-NOT-PROMOTE. Arm A (per-axis de-gross): C1 PASSES (CMCGB lo 0.0273>0, 5/5 purged folds, 187 episodes — the per-axis scalar genuinely cuts the modeled momentum-crash tail per unit gross vs uniform) + alpha retention 0.868≥0.85 PASSES, BUT C2 FAILS — the DYNAMIC trigger does not beat a STATIC 0.70x constant de-gross on tail legs (the gain-protection subsumption class again: the mechanism is real, the dynamism isn't paid for). Arm B rotation: only 3 triggers (corpus-bound 2021+, the pre-reg's own power caveat). 2009-Q2 window unreachable (MTUM inception 2013 — disclosed, not spliced); positions-level book reconstruction per the gain-protection precedent (PASS would have been survivorship-discounted). GAIN_PROTECTION/dispersion overlays stay shadow. data/backfill/momentum_dispersion_governor_2026-07-06.json. Rule #10: no iterate.

The backfill ran and concluded — the hypothesis did not fail, but the result is informational rather than a clean strategy-grade pass. See the outcome below.