What if the FDA bans imports from a giant Indian generics plant?
An FDA ban on a giant Indian generics plant (Sun/Aurobindo/Dr Reddy's echoes of Ranbaxy 2013) drives US drug shortages and price spikes — a health-inflation and India-pharma-export shock, not a tech-tariff event. The semis/TSMC/Alibaba cascade is entirely mis-mapped. Transmission: US buyers scramble for ex-India supply, India pharma ADRs and the rupee's pharma-export line take the hit; medical-care CPI ticks up.
how we built this number — every step
The class rate is measured from our dated, sourced event library (decade-normalized Poisson — the full table is public at base_rates.json). The variant’s share within its class is the analyst’s editorial call, published so you can audit it. A wider range means thinner precedent. Full recipe: methodology · scored at Reality Check.
The butterfly cascade
How this trigger trickles across markets, left → right — the root shock, its first‑order moves, then the ripple effects. Drag any node; tap a market for its real price history.
Resolution timeline — how this probability is moving
Our model's odds (gold) over time vs the crowd's (Polymarket, blue), from the past toward the 0–6 months horizon. Each dot is a real macro event that nudged the probability — green pushed it up, red pushed it down. Tap a dot for the source. The gold path is an illustrative reconstruction anchored to today's estimate — real dated events, not a live re-estimate history.
What it would mean
If this plays out, it is a mixed shock. FDA bans imports from a giant Indian generic plant over data fraud, triggering US drug shortages and price spikes. The trigger decomposes into signed root‑shocks — Inflation surprise ▲ · Risk appetite ▼ — which propagate through our causal graph to the markets below.
If it happens — the markets it would move
Biggest moves first. Projected moves are cascade-model priors; hist A–B% = what comparable past events actually did (measured abnormal returns), and model prior · unmeasured marks markets with no analogue backing yet. Tap any market for its price history.
| Market | Class | Projected move | |
|---|---|---|---|
| 1 | 30y Treasury yield DGS30 📈 chart | Rate | ▲ +1bp hist -2.21–+7.48% · other way +5.4% (n=12) |
| 2 | 10y Treasury yield DGS10 📈 chart | Rate | ▲ +1bp hist -1.59–+5.0% · other way +6.3% (n=12) |
Historical precedent — what analogous events actually did
Across 40 analogous events (overlap‑weighted), as abnormal returns — market beta stripped, so it's the event's own effect, not the market backdrop. Shown at 20 days (persistent) and 5 days (immediate); ↺ fades = the two horizons disagree. Confidence = consistency × sample × significance.
| Asset | History says | Abnormal (20d · 5d) | Hit | n | Confidence | vs cascade |
|---|---|---|---|---|---|---|
| 30y yield DGS30 | LONG | +6bp · 5d +2bp | 58% | 40 | 0.16 | ✓ matches cascade |
| Volatility VIX | LONG | +3.5% · 5d +6.3% | 57% | 36 | 0.13 | · |
| 10y yield DGS10 | LONG | +4bp · 5d +2bp | 54% | 40 | 0.08 | ✓ matches cascade |
| Gold XAU | LONG | +0.4% · 5d -0.5% ↺ fades | 53% | 36 | 0.04 | · |
| Bitcoin BTC | LONG | +1.0% · 5d -2.3% ↺ fades | 53% | 36 | 0.04 | · |
| US dollar DXY | LONG | +0.0% · 5d +0.2% | 46% | 40 | 0.00 | · |
| High-yield credit HYG | LONG | +0.2% · 5d +0.3% | 45% | 36 | 0.00 | · |
Why this probability
Indian generic-plant import bans recur regularly (data-integrity); shortages frequent; 6mo window favorable. A base‑rate‑anchored prior, continuously scored against what actually happens — not a forecast.