What if Refining-margin boom lifts Valero, Marathon and Phillips 66?
A tight global product market and wide gasoline and diesel cracks drive a refining-margin boom that boosts merchant refiners Valero, Marathon Petroleum and Phillips 66, outperforming integrated peers.
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. A tight global product market and wide gasoline and diesel cracks drive a refining-margin boom that boosts merchant refiners Valero, Marathon Petroleum and Phillips 66, outperforming integrated peers. The trigger decomposes into signed root‑shocks — Diesel ▲ · Gasoline ▲ · 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 | Solana SOLon Hyperliquid 📈 chart | Crypto | ▲ +0.3% hist -3.46–+5.37% · other way +4.42% (n=6) |
| 2 | Hyperliquid (HYPE) HYPEon Hyperliquid | Crypto | ▲ +0.3% model prior · unmeasured |
| 3 | MicroStrategy MSTRon Hyperliquid 📈 chart | Equity | ▲ +0.3% hist -1.68–+3.72% · other way +4.71% (n=12) |
| 4 | Ether ETHon Hyperliquid 📈 chart | Crypto | ▲ +0.2% hist -2.7–+4.87% · other way -5.0% (n=6) |
| 5 | Nasdaq 100 NDXon Hyperliquid 📈 chart | Index | ▲ +0.2% hist +-0.0–+0.34% · other way +0.12% (n=12) |
| 6 | Bitcoin BTCon Hyperliquid 📈 chart | Crypto | ▲ +0.2% hist -4.21–+5.47% · other way -0.57% (n=9) |
| 7 | Tech sector XLK 📈 chart | Equity | ▲ +0.1% hist +0.02–+0.17% · other way +0.2% (n=12) |
Probable recommendation
Historical precedent — what analogous events actually did
Across 28 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 |
|---|---|---|---|---|---|---|
| NDX NDX | LONG | +0.2% · 5d -0.8% ↺ fades | 70% | 23 | 0.29 | ✓ matches cascade |
| ETH ETH | LONG | +4.8% · 5d -1.6% ↺ fades | 67% | 12 | 0.23 | ✓ matches cascade |
| Volatility VIX | SHORT | -3.8% · 5d -3.4% | 64% | 22 | 0.19 | · |
| US dollar DXY | LONG | +0.3% · 5d -0.0% ↺ fades | 61% | 28 | 0.19 | · |
| 10y yield DGS10 | LONG | +13bp · 5d +6bp | 58% | 28 | 0.15 | · |
| SOL SOL | LONG | +5.4% · 5d -6.4% ↺ fades | 58% | 12 | 0.11 | ✓ matches cascade |
| Gold XAU | SHORT | -0.9% · 5d -0.3% | 52% | 21 | 0.04 | · |
| MSTR MSTR | LONG | +3.5% · 5d -2.0% ↺ fades | 38% | 21 | 0.00 | ✓ matches cascade |
| Bitcoin BTC | LONG | +5.7% · 5d +0.0% | 50% | 12 | 0.00 | ✓ matches cascade |
| XLK XLK | LONG | +0.1% · 5d -0.6% ↺ fades | 48% | 21 | 0.00 | ✓ matches cascade |
| High-yield credit HYG | LONG | +0.5% · 5d -0.2% ↺ fades | 37% | 19 | 0.00 | · |