start experiment 44 (exp/44-q12-long-horizon-22d-label-paired-with-w)

queue/designs/q19_martingale_vr.md

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+# QUEUE-19 — Martingale / variance-ratio study close-out (no qrun)
+
+**Status:** QUEUED · **Priority:** P2 · **Effort:** ad-hoc script under `book/data/`
+
+## Hypothesis (settle)
+Assets are submartingales long-horizon / mean-reverting short-horizon
+(`VR < 1` at 5–20d). CLAIMS.md marks this HYPOTHESIS (chat-derived martingale
+study; exp 19 was opened but never closed). It is a market-structure claim, not a
+trading claim — settle it with a clean-lake script, then close exp 19 or open a
+scripted EVIDENCE entry.
+
+## Method (persist everything under `book/data/evidence/q19-vr/`)
+1. Load the 50-ETF panel 1d bars from the lake for 2015-01-01..2026-08-19.
+2. Compute the Lo–MacKinlay variance ratio at horizons 5 / 10 / 20d per symbol,
+   with heteroskedasticity-robust z-stats.
+3. Report: per-horizon VR distribution, fraction of symbols with VR < 1 and the
+   z-significance, pooled drift vs daily variance (submartingale check).
+4. Cross-check the pooled `sp_trend_slope_5` regression beta claim (β ≈ −0.53,
+   t ≈ −24) on the clean lake.
+5. Write `VR_stats.csv` + a one-page summary into the evidence dir.
+
+## Acceptance
+- VR < 1 at 5–20d for a material fraction of the panel with |z| > 2 → supports
+  the mean-reversion HYPOTHESIS; else mark REFUTED or REFERENCED.
+- The result updates CLAIMS.md's "Assets are submartingales…" row and closes the
+  exp-19 open thread.

queue/designs/q20_effective_names.md

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+# QUEUE-20 — Effective independent names in the 50-ETF book (no qrun)
+
+**Status:** QUEUED · **Priority:** P2 · **Effort:** ad-hoc script under `book/data/`
+
+## Hypothesis (settle)
+The 50-ETF book has only ~4 effective independent names (CLAIMS.md HYPOTHESIS,
+chat-derived eigenvalue analysis, pre-reset). This is a concentration/diversification
+claim with direct sizing relevance; verify it on the clean lake.
+
+## Method (persist everything under `book/data/evidence/q20-effective-names/`)
+1. Load the 50-ETF panel 1d returns from the lake for the test window 2026-01-04..2026-08-10.
+2. Standardize returns; compute the correlation matrix and its eigendecomposition.
+3. Count eigenvalues above the Marchenko–Pastur bound (N=50, T≈150) and report the
+   cumulative-variance share of the top k components.
+4. Effective-rank measures: participation ratio `(Σλ)² / Σλ²` and cumulative 80%
+   variance count.
+5. Write `eigenanalysis.csv` + a one-page summary.
+
+## Acceptance
+- If effective rank ≈ 4 (top-4 explain ~80%+ variance), the concentration claim is
+  PROVEN and feeds chapter 08 sizing guidance (why topk 10→20 adds no breadth).
+- If effective rank is much larger, mark the claim REFUTED.