What if Jet-fuel glut as new refineries outpace aviation recovery?
Kerosene output from new complex refineries outruns the pace of aviation-demand recovery, leaving jet fuel oversupplied; jet cracks compress and airline fuel costs fall, aiding carrier margins.
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 6–18 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. Kerosene output from new complex refineries outruns the pace of aviation-demand recovery, leaving jet fuel oversupplied; jet cracks compress and airline fuel costs fall, aiding carrier margins. The trigger decomposes into signed root‑shocks — Consumer spending ▲ · Inflation expectations ▼ · Jet fuel ▼ · Oil 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 | United Airlines UAL 📈 chart | Equity | ▲ +0.4% hist -7.38–+10.74% · other way +70.35% (n=5) |
| 2 | Delta DAL 📈 chart | Equity | ▲ +0.3% hist -3.29–+6.97% · other way +33.73% (n=5) |
| 3 | 30y Treasury yield DGS30 📈 chart | Rate | ▼ -1bp hist -3.6–+4.61% · other way +21.1% (n=12) |
| 4 | 10y Treasury yield DGS10 📈 chart | Rate | ▼ -1bp hist -3.12–+2.48% · other way +15.7% (n=12) |
Historical precedent — what analogous events actually did
Across 13 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 |
|---|---|---|---|---|---|---|
| DAL DAL | LONG | +6.7% · 5d +2.1% | 73% | 11 | 0.43 | ✓ matches cascade |
| Volatility VIX | SHORT | -7.3% · 5d -4.9% | 71% | 13 | 0.30 | · |
| Gold XAU | LONG | +1.4% · 5d +0.3% | 65% | 13 | 0.27 | · |
| 30y yield DGS30 | LONG | +6bp · 5d +2bp | 65% | 13 | 0.19 | ⚠ differs |
| UAL UAL | LONG | +11.0% · 5d -0.2% ↺ fades | 56% | 12 | 0.12 | ✓ matches cascade |
| 10y yield DGS10 | LONG | +3bp · 5d +2bp | 29% | 13 | 0.00 | ⚠ differs |
| US dollar DXY | SHORT | -0.1% · 5d -0.4% | 47% | 13 | 0.00 | · |
| Bitcoin BTC | LONG | +9.7% · 5d -2.0% ↺ fades | 50% | 7 | 0.00 | · |
| High-yield credit HYG | LONG | +2.0% · 5d -0.5% ↺ fades | 47% | 11 | 0.00 | · |