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# PHASE 7 — Inference, calibration, subgroups, falsification, economics (2026-11-03)

# Runs (M3U96b, rest_chain, 23:06 → ~02:50 ET; all exit 0)

Run Config / flags Origins Wall
Held-out 2024 main.yaml --heldout (baselines refit on the 60 instruments' own training histories; neural checkpoints from the main study, zero-shot) 250 322 ≈ 15 min
Ablations 2024 ablations.yaml (15 Small variants × 4 000 steps + reference + 2 seeds + copula) 986 468 ≈ 6 h 10
Final 2025 pooled final.yaml --eval-split final --models-from results/metrics/main 1 008 425 ≈ 1 h 25
Final 2025 held-out final.yaml --eval-split final --heldout --models-from … 254 334 ≈ 25 min
Post-processing on the laptop: scripts/pairwise.py (DM-HAC, day-cluster bootstrap, Holm/BH, subgroups, stress-day
calibration) for main/test, main/test_heldout, final/final, final/final_heldout, ablations/test;
scripts/economic.py on the node (H5); scripts/evaluate.py, make_figures.py, make_static_tables.py.

# Hypothesis verdicts (relative CRPS of the cumulative return; Holm-adjusted DM p-values)

Hypothesis Evidence Verdict
H1 multi-resolution > 1m-only (equal params) 2024 dev: −0.04 % (H5) … −0.10 % (H60), t −4.5 to −5.3; 4k-step ablation: −0.12 … −0.16 %; 2025 final: +0.01 … +0.03 %, p ≥ 0.36; 2025 held-out: p = 1 statistically detectable in sample, economically nil, absent out of sample → rejected in substance
H2 transfer to unseen instruments held-out vs random walk −4.1 … −4.3 % (pooled −4.05 … −4.27 %); beats GARCH-t (−0.9 … −1.6 %), EWMA, TCN, MLP; ties HAR/ridge/LightGBM from 30 min (p = 1); 2025 held-out identical supported (no transfer penalty; parity with refitted HAR beyond 15 min)
H3 regime conditioning improves stress calibration no-regime vs stats-regime: +0.02 … +0.03 % CRPS, p > 0.3 at 30/60; stress-day coverage identical (0.57/0.85/0.97 vs 0.57/0.85/0.97) rejected (learned codebook: −0.03 … −0.15 %, small)
H4 coherent paths > independent marginals copula NLL → 0 (independence); energy −0.003 %, variogram −0.002 %, MDD CRPS −0.01 %, RV CRPS +0.10 %, all CIs contain 0 rejected
H5 economic content median–realised correlation 0.003–0.025; net return at 1 bp cost 0.0 bp [−1.7, +1.8]; traded share < 4 % above 2.5 bp rejected
Supplementary findings: model size irrelevant (Base vs Small p ≥ 0.1 everywhere); neural best at H = 5 (−1.2 … −1.9 % vs HAR),
HAR/ridge/LightGBM best at H ≥ 15 (+0.2 … +0.7 % against MRPT-S, 2024 and 2025); time-only inputs recover ≈ 90 % of the gain
over the random walk; shuffled minutes cost +0.13 … +0.21 %; ticker identity hurts (+0.05 … +0.31 %); Gaussian head worse than Student-t by +0.20 … +0.32 % (re-scored after a sampling fix for ν = ∞).

# Calibration

Neural + GARCH/EWMA: nominal at 95 %, over-dispersed centre (50 % coverage 0.55–0.59). HAR/ridge/LightGBM: nominal from 15 min, under-dispersed at 5 min (50 % coverage 0.37). 2025 stress days: HAR 0.46/0.77/0.95 vs MRPT-S 0.55/0.84/0.95.

# Multiplicity and dependence

All intervals are day-cluster bootstraps (251–252 clusters per year); DM lags = overlap × instruments (240 … 960); Holm and BH columns in every pairwise_*.csv. Overlapping origins are never counted as independent.

# Artifacts

results/metrics/{main,final,ablations}/pairwise_*.csv, subgroups_*.csv, stress_calibration_*.csv, economic_test.csv, path_scores_mrpt_small_copula_test.json, leaderboards and comparisons per split; paper/tables/*.tex (53), paper/figures/* (27), paper/results_macros.tex (3 468 macros). Gates: leakage (tests), numerical (tests + copula null reproduced on synthetic data), provenance (dataset versions 17 375 / 5 162 in every run_meta) — PASS.

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