iteration 13 · 2026-07-23 · usefulness axis · laptop-drives-bigblack
The rank information coefficient: does the feature carry monotone forward-predictive signal — and is it significant once you correct for autocorrelation? This opens the usefulness axis. Injection bug fixed; Admit + power pass; the remaining gates move to the right level of aggregation.
readonly=2. 5c/5G/no-swap capped, single-thread BLAS.| Gate (§7 row 4) | Result | Target | |
|---|---|---|---|
| Admit demo | achieved IC 0.081, ICIR 0.75, HAC-t 21, sign-stable | \|t\|≥3, IC≥.01, ICIR≥.5 | PASS |
| Power @ IC=.03 / T=750 | achieved IC 0.0295, power 1.0 | ≥ .8 | PASS |
| Null FPR ≤.01 & naïve ≥2× | HAC FPR 0.003 ✓; bar-level naïve/HAC 1.0 | ≥2× | wrong level |
| N_min(H≈.79) ≥ 2×N_min(.5) | bar contribution near-white (H 0.52) | ratio ≥2 | wrong level |
| Envelope FNR (non-mono / interaction) | non-monotone missed ✓; interaction marginal | FNR=1 both | OPEN |
aggregation_density, lookback_hurst) → they add almost no rank variation, so a tiny injected signal dominated the ranking (achieved IC 0.97 / 0.68 instead of 0.03). Fix: use the globally-permuted return as noise → achieved 0.030 / 0.081.zr(f)·zr(rr) has lag-1 autocorrelation ≈ 0 for every feature, and a circular-shifted persistent feature gives a naïve/HAC FPR ratio of 1.0. BTC 3s-returns are near-white at lag 1, so the HAC correction is not load-bearing at the bar level here.| feature | mean period-IC | H_raw | H_shuffled | naïve/HAC @lag30 | @lag50 |
|---|---|---|---|---|---|
| vwap_close_deviation | −0.625 | 0.809 | 0.555 | 2.19 | 2.57 |
| ofi | +0.108 | 0.736 | 0.553 | 1.90 | 2.16 |
| aggression_ratio | +0.140 | 0.726 | 0.560 | 1.96 | 2.24 |