📈 Markets & Finance mixed · 1–3 years
A what‑if from the future

What if AI-native ad agencies undercut the trade-desk middle layer?

Automated, model-driven media buying disintermediates independent demand-side platforms and agencies, compressing ad-tech intermediary margins even as platform spend holds.

32%
our model probability
over 1–3 years
prediction markets — wisdom of the crowd
loading live odds…
Empirically anchored 32% · 90% range 8–56% · 17 analogues · measured class tech_ai_bull 57% in 3 yr · 3% held back for the unknown
how we built this number — every step
Measured class rate — tech_ai_bull ≈0.2842/yr → 57% in 3 yr57%
Analyst prior · editorial share 59% of the class34%
Pooled · weight 74%33%
Crowd — no liquid market
Reserve 3% · no extremizing (×1.0)33%
Published32%

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.

loading the timeline…

What it would mean

If this plays out, it is a mixed shock. Automated, model-driven media buying disintermediates independent demand-side platforms and agencies, compressing ad-tech intermediary margins even as platform spend holds. The trigger decomposes into signed root‑shocks — AI breakthrough ▲ · Consumer spending ▲ · 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.

MarketClassProjected move
1Nvidia NVDAon Hyperliquid 📈 chartEquity▲ +0.6%
hist -1.61–+3.35% · other way +5.21% (n=12)
2Semiconductors SMHon Hyperliquid 📈 chartEquity▲ +0.3%
hist +0.06–+0.4% · other way +3.33% (n=11)
3Solana SOLon Hyperliquid 📈 chartCrypto▼ -0.3%
hist -20.3–+3.26% · other way +24.73% (n=6)
4MicroStrategy MSTRon Hyperliquid 📈 chartEquity▼ -0.3%
hist -5.04–+8.03% · other way +6.61% (n=12)
5Hyperliquid (HYPE) HYPEon HyperliquidCrypto▼ -0.2%
model prior · unmeasured
6AMD AMDon Hyperliquid 📈 chartEquity▲ +0.2%
hist -2.7–+1.15% · other way +11.45% (n=12)
7Broadcom AVGOon Hyperliquid 📈 chartEquity▲ +0.2%
hist -0.18–+0.61% · other way -0.58% (n=7)
8Micron MUon Hyperliquid 📈 chartEquity▲ +0.2%
hist -3.27–+2.07% · other way +5.9% (n=12)
9TSMC TSMon Hyperliquid 📈 chartEquity▲ +0.2%
hist -0.02–+0.22% · other way +2.75% (n=12)
10Marvell MRVLon Hyperliquid 📈 chartEquity▲ +0.2%
hist -0.62–+1.23% · other way -0.94% (n=11)
11Ether ETHon Hyperliquid 📈 chartCrypto▼ -0.2%
hist -1.84–+1.25% · other way +11.62% (n=7)
12ASML ASMLon Hyperliquid 📈 chartEquity▲ +0.2%
hist -0.09–+0.22% · other way +3.83% (n=12)
13Nasdaq 100 NDXon Hyperliquid 📈 chartIndex▲ +0.1%
hist -0.03–+0.26% · other way -2.33% (n=12)
14Bitcoin BTCon Hyperliquid 📈 chartCrypto▼ -0.2%
hist -2.96–+4.78% · other way +7.92% (n=7)

Probable recommendation

If the scenario above plays out, the probable cross‑asset positioning → a scenario‑conditional read, not personalized investment advice
For a common-man portfolio: Mixed for a typical portfolio — the move is more about rotation than direction. Favour the winners over the losers below rather than net exposure.

Historical precedent — what analogous events actually did

Across 17 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.

Neuralink implants its first human brain-computer interface 2024-01 OpenAI releases GPT-4 2023-03 ChatGPT launches 2022-11 AlphaFold cracks the protein-folding problem 2020-11 AlphaGo defeats Lee Sedol 2016-03 TSMC slumps as DeepSeek roils AI-chip demand assumptions 2025-02 Nikkei 225 record single-day rebound 2024-08 Megacap AI-capex doubt selloff 2024-07 LK-99 room-temperature superconductor claim 2023-07 Nvidia AI-guidance blowout ignites the automation/AI capex wave 2023-05 Wegovy 2021-06 First mRNA COVID-19 vaccine authorized 2020-12 He Jiankui announces CRISPR-edited babies 2018-11 SpaceX lands an orbital rocket booster 2015-12 2008 global rice crisis: Thai benchmark tops $1,000/ton 2008-04 Soviet August coup attempt against Gorbachev 1991-08 Cuban Missile Crisis 1962-10
AssetHistory saysAbnormal (20d · 5d)HitnConfidencevs cascade
SOL SOLSHORT-16.8% · 5d -7.7%100%11 0.67✓ matches cascade
US dollar DXYSHORT-0.8% · 5d -0.3%76%16 0.42·
AMD AMDSHORT-2.6% · 5d -1.1%70%16 0.27⚠ differs
Gold XAULONG+0.3% · 5d -0.0% ↺ fades63%15 0.20·
Bitcoin BTCLONG+5.0% · 5d -2.8% ↺ fades61%14 0.17⚠ differs
TSM TSMSHORT-0.1% · 5d -1.6%60%15 0.14⚠ differs
MSTR MSTRLONG+8.4% · 5d -0.6% ↺ fades57%15 0.13⚠ differs
ASML ASMLSHORT-0.2% · 5d -0.8%60%15 0.13⚠ differs
MU MUSHORT-3.5% · 5d -2.0%57%16 0.09⚠ differs
AVGO AVGOLONG+0.4% · 5d -1.7% ↺ fades55%14 0.07✓ matches cascade
NVDA NVDALONG+3.0% · 5d +0.3%54%15 0.06✓ matches cascade
NDX NDXLONG+0.1% · 5d -0.5% ↺ fades51%16 0.02✓ matches cascade
Volatility VIXSHORT-0.4% · 5d -6.4%51%16 0.02·
SMH SMHLONG+0.1% · 5d +0.1%43%15 0.00✓ matches cascade

Methodology. Probability and impact are anchored to history and scored against what actually happens — wins and losses, in public, at Reality Check. Crowd odds live from Polymarket & Kalshi. By Vikas Singh, Quantitative Strategist. Updated 2026-07-03.