What if an autonomous purchasing agent racks up millions in rogue orders?
A rogue agent burning cash freezes enterprise rollouts, hitting inference demand and the AI-capex bellwether NVDA first; the read-through is a pause in agentic deployment, not a capex collapse, so the move is shallow. Rhymes with the Jul-2024 megacap AI-ROI doubt selloff that knocked Nvidia ~7% intraday before mean-reverting. Skeptic's note: an isolated ops failure rarely dents physical GPU orders already booked.
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 risk-on shock. An autonomous purchasing agent racks up millions in erroneous orders, freezing enterprise agent rollouts. The trigger decomposes into signed root‑shocks — AI capex ▼ · Job displacement ▼ — 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 | Nvidia NVDAon Hyperliquid 📈 chart | Equity | ▼ -1.0% hist -1.75–+0.53% · other way +1.42% (n=12) |
| 2 | Broadcom AVGOon Hyperliquid 📈 chart | Equity | ▼ -0.7% hist -0.75–-0.27% · other way +1.03% (n=12) |
| 3 | Micron MUon Hyperliquid 📈 chart | Equity | ▼ -0.7% hist -1.92–+0.66% · other way +2.5% (n=12) |
| 4 | Semiconductors SMHon Hyperliquid 📈 chart | Equity | ▼ -0.5% hist -0.41–-0.24% · other way +1.09% (n=12) |
| 5 | AMD AMDon Hyperliquid 📈 chart | Equity | ▼ -0.3% hist -1.94–+0.94% · other way -2.91% (n=12) |
| 6 | TSMC TSMon Hyperliquid 📈 chart | Equity | ▼ -0.3% hist -1.83–+1.01% · other way +1.72% (n=12) |
| 7 | Marvell MRVLon Hyperliquid 📈 chart | Equity | ▼ -0.3% hist -0.37–-0.08% · other way +0.2% (n=12) |
| 8 | ASML ASMLon Hyperliquid 📈 chart | Equity | ▼ -0.3% hist -3.24–+1.8% · other way -2.38% (n=12) |
| 9 | Qualcomm QCOMon Hyperliquid 📈 chart | Equity | ▼ -0.2% hist -2.79–+2.03% · other way -1.26% (n=12) |
| 10 | S&P 500 SPXon Hyperliquid 📈 chart | Index | ▲ +0.1% hist -1.71–+1.53% · other way +0.67% (n=12) |
| 11 | Intel INTCon Hyperliquid 📈 chart | Equity | ▼ -0.2% hist -3.98–+3.09% · other way -4.74% (n=12) |
| 12 | Nasdaq 100 NDXon Hyperliquid 📈 chart | Index | ▲ +0.1% hist -0.58–+0.41% · other way -0.43% (n=12) |
Probable recommendation
Historical precedent — what analogous events actually did
Across 11 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 |
|---|---|---|---|---|---|---|
| Bitcoin BTC | SHORT | -5.3% · 5d -2.0% | 75% | 11 | 0.39 | · |
| NDX NDX | SHORT | -0.7% · 5d -1.4% | 75% | 11 | 0.32 | ⚠ differs |
| Gold XAU | LONG | +1.0% · 5d -0.5% ↺ fades | 67% | 11 | 0.26 | · |
| 10y yield DGS10 | SHORT | -14bp · 5d -1bp | 67% | 11 | 0.26 | · |
| ASML ASML | SHORT | -3.1% · 5d -4.8% | 67% | 11 | 0.25 | ✓ matches cascade |
| US dollar DXY | SHORT | -0.2% · 5d +0.1% ↺ fades | 67% | 11 | 0.25 | · |
| High-yield credit HYG | LONG | +0.6% · 5d +0.3% | 67% | 11 | 0.25 | · |
| AMD AMD | SHORT | -1.8% · 5d -3.6% | 67% | 11 | 0.23 | ✓ matches cascade |
| MU MU | SHORT | -1.5% · 5d -4.1% | 62% | 11 | 0.18 | ✓ matches cascade |
| TSM TSM | SHORT | -1.7% · 5d -1.7% | 58% | 11 | 0.12 | ✓ matches cascade |
| SPX SPX | SHORT | -2.0% · 5d -1.1% | 54% | 11 | 0.07 | ⚠ differs |
| NVDA NVDA | LONG | +1.2% · 5d -1.5% ↺ fades | 33% | 11 | 0.00 | ⚠ differs |
| AVGO AVGO | LONG | +0.1% · 5d -2.0% ↺ fades | 42% | 11 | 0.00 | ⚠ differs |
| SMH SMH | SHORT | -0.0% · 5d -1.1% | 50% | 11 | 0.00 | ✓ matches cascade |
Why this probability
Novel agent-spend failure mode; analogues are chip-demand selloffs, not actual rogue-spend events; short window. A base‑rate‑anchored prior, continuously scored against what actually happens — not a forecast.