What if a critical-minerals crunch squeezed battery makers?
A lithium/critical-minerals crunch raises battery input costs and squeezes EV/cell makers' margins, but the macro footprint is narrow and the copper-miner read-through (Freeport) is only a loose proxy. Rhymes with the 2022 lithium spike to ~$80k/t that compressed automaker EV economics before the 2023-24 glut crashed prices. Forward angle: lithium is structurally oversupplied near-term, so a 'crunch' likely reflects a specific chokepoint (China processing, a single brine/mine) — trade the named bottleneck and ex-China refiners, not a broad commodity beta.
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 1–3 years 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. A lithium/critical-minerals supply crunch hits EV and battery makers. The trigger decomposes into signed root‑shocks — Industrial demand ▲ — 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 | Freeport (copper) FCX 📈 chart | Equity | ▲ +0.3% hist -2.19–+0.82% · other way +4.9% (n=12) |
| 2 | Copper XCUon Hyperliquid 📈 chart | Commodity | ▲ +0.1% hist -0.28–+0.22% · other way -0.49% (n=12) |
Probable recommendation
Why we may diverge from history
Trust the cascade long on FCX/copper: the -6.6% mean is dragged by Comex-squeeze and tariff-reversal windows, while the actual supply-tightening analogues (Grasberg, DRC) printed +9-12% on-channel.
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 |
|---|---|---|---|---|---|---|
| FCX FCX | SHORT | -2.1% · 5d -1.7% | 62% | 40 | 0.22 | ⚠ differs |
| High-yield credit HYG | SHORT | -0.4% · 5d -0.1% | 60% | 40 | 0.16 | · |
| Volatility VIX | LONG | +4.1% · 5d -0.7% ↺ fades | 55% | 40 | 0.08 | · |
| XCU XCU | SHORT | -0.4% · 5d -1.0% | 53% | 40 | 0.04 | ⚠ differs |
| Bitcoin BTC | LONG | +3.4% · 5d -1.8% ↺ fades | 51% | 39 | 0.02 | · |
| Gold XAU | SHORT | -0.1% · 5d -1.1% | 45% | 40 | 0.00 | · |
| US dollar DXY | SHORT | -0.0% · 5d +0.1% ↺ fades | 45% | 40 | 0.00 | · |
| 10y yield DGS10 | LONG | +3bp · 5d +2bp | 45% | 40 | 0.00 | · |
Why this probability
Lithium currently oversupplied; near-term crunch less likely despite EV demand. A base‑rate‑anchored prior, continuously scored against what actually happens — not a forecast.