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For every measure in the register that targets a material with a free exchange benchmark, we measure what that benchmark actually did around the announcement and the implementation date — market-adjusted against a related complex, so a policy move is not just re-reading its own sector rally. Including the events that moved nothing, which are the majority.
1. Our relevance model discriminates. When the issuing country is a significant producer of the material, the measure coincides with a statistically distinguishable 21-day move 16.0% of the time. When it is not, that falls to 7.9%. Two-proportion test: z = 2.76, p = 0.006. That is the empirical case for exposure identification: knowing which measures touch a real chokepoint roughly doubles the rate at which you are looking at a genuine dislocation.
2. Direction is a coin flip. Among high-relevance events, 59.4% of 21-day abnormal moves were positive (38 of 64). There is no directional edge in this data, and we do not claim one. This platform tells you where to look, never which way it goes.
| Material | Events | Median |abnormal 21d| | Beat noise |
|---|---|---|---|
| Copper | 396 | 2.76% | 27/371 (7.3%) |
| Gold | 279 | 4.92% | 11/262 (4.2%) |
| Aluminium | 75 | 2.04% | 5/70 (7.1%) |
| Iron ore | 67 | 3.49% | 17/65 (26.2%) |
| Silver | 64 | 6.33% | 12/62 (19.4%) |
| PGMs | 26 | 4.55% | 4/24 (16.7%) |
Every event that beat the noise threshold, largest abnormal 21-day move first. Each row links to the filed action with its primary source, so any figure here is checkable back to the measure itself — a cohort statistic alone would not survive that scrutiny.
Close-to-close benchmark reaction around each IPTM action date, at T+1d/T+5d/T+21d, market-adjusted (beta=1) against a complex-specific benchmark (precious->GC=F, base->DBB, gold->DBC) so a policy move is not just re-reading its own complex rally. z-scores are standardized CARs against a pre-event estimation window.
Generated 2026-10-05. Related: early-warning track record and case studies.