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MacroLens is the Industrial Policy & Trade Monitor (IPTM) — a typed, machine-readable, free-data register of geoeconomic government actions with a relational graph linking actions to countries, sectors, materials, and companies. The country macro scorecard and the Mineral Dependency Atlas are supporting evidence layers that give every policy action its economic and supply-chain context.
New here? How to read MacroLens → walks the five-layer transmission chain (macro → trade → policy → market → company) and shows three entry points depending on the question you arrived with. Who is this for? → ranks the personas this is built to serve.
MacroLens is a structured event knowledge graph of geoeconomic policy, with a policy-transmission-mechanism layer that traces each action through to sector, material, and named-company exposure. It sits at the intersection of three established traditions and joins them in a way none of them does individually:
What is novel is the join. GDELT does not quantify exposure. The Atlas of Economic Complexity does not track policy events. The transmission-mechanism papers are not data. Global Trade Alert covers tariffs only. No one publicly maintains the structured event layer with typed causal edges between actions and full forward-traversal to material and company exposure.
Practically, that means: you can land on any action, read its primary source, see which prior actions it responds to and which actions have responded to it, walk the typed exposure forward to the affected sectors / materials / companies, and link back to the country macro context — without leaving the dataset. That round-trip is the product.
The IPTM is a free, public, typed, cross-referenced register of geoeconomic policy actions. News terminals carry the headlines as unstructured text. Global Trade Alert covers tariffs. Think-tanks publish narrative analyses. The structured layer is the gap MacroLens fills: a register where each government action is typed, severity-scored, time-stamped, primary-source verified, and cross-referenced to the countries / sectors / materials / companies it touches, with explicit causal edges between related actions.
responds_to causal edges — the network structure that headlines hide.The site is organised around four thematic lenses that share one country / sector / material / company / action graph. The Policy lens is the product; the other three are supporting evidence.
The IPTM register, themes, exposure rankings, weekly brief.
The 44-country macro scorecard. It gives every IPTM action its country-context: when an action targets, say, Korea, the KR per-country page shows the macro score, the regime-exposure ranking, the relevant ETFs.
The Mineral Dependency Atlas: strategic-material dossiers + cross-cutting analyses + monthly reports. It gives every IPTM action affecting a material the structural-dependency context behind why it matters.
DCA picks, calibration, backtest. We publish what works and what does not: the retired v3b composite failed out-of-sample by −11.2 pp/yr vs ACWI, and that failure is preserved on /backtest rather than buried. The IPTM signal backtest published a clean null result.
responds_to causal-edge layer and the sector adjacency both require sustained curation and primary-source verification per edge.Next.js 15 / React 18 on Node 20, deployed via PM2 with a Caddy reverse-proxy. Content in markdown rendered with a minimal custom renderer. Python sidecar for the IPTM signal backtest, picks calibration, GDELT ingestion, IPTM cluster detection, and RSS polling. yfinance for prices. No paid data dependencies.