Most market models are trained on the last 20–30 years of data. That window contains exactly one rate cycle, one inflation regime, and one global liquidity environment. A real macro view needs centuries — World Wars, gold standards, the 70s, the 30s — and most systems quietly throw that data away.
Compiled a unified daily/monthly dataset from 1871 forward, with consistent definitions across regimes (gold standard, Bretton Woods, fiat).
Built regime-detection models that learn from cycles instead of fitting on the latest 10 years.
Layered a News Brain that aligns market moves with the actual narrative drivers of each era — not just the price action.
Ship a v3 (data-model-2) rebuild with cleaner abstractions for adding new asset classes without retraining the whole stack.
Live regime predictions running against 150+ years of historical context.
Out-of-sample regime classification holds up across the 70s inflation, 2008, and 2020 — eras most modern models can't see.
Fully versioned data + models — every prediction is reproducible from raw inputs.