Markets run on narrative. Not fundamentals — narrative. Fundamentals inform the narrative eventually, but the narrative moves first.
The consensus machine has a predictable structure. It starts with a correct observation about the world. The observation attracts capital. Capital attracts more capital. By the time the narrative is consensus, the trade is crowded, the assets are priced for the narrative to be true, and the original insight has been arbitraged away.
The cycle
Every consensus narrative follows the same arc:
- Contrarian thesis — a small group of people notice something the market hasn’t priced in
- Early adoption — smart money moves; prices begin to reflect the insight
- Narrative formation — the thesis becomes a story; media coverage begins
- Consensus — everyone agrees; the trade is crowded; the asset is expensive
- Resolution — reality either confirms or falsifies; the narrative unwinds accordingly
The edge in markets isn’t being right. It’s being right early.
The working hypothesis model
The reason I track theses publicly — with explicit falsification conditions — is that it forces precision.
Most market commentary is unfalsifiable. “AI will be huge.” “The dollar will weaken.” “Rates will come down eventually.” These statements can never be proven wrong because they don’t specify a timeframe or a threshold.
A thesis with a falsification condition is different. It’s a bet. And bets have to be settled.
The discipline of writing down what would change your mind is underrated. It forces you to have a view instead of a vibe.
The current landscape
I’m watching a few narratives that look like they’re somewhere between early adoption and consensus formation. The AI infrastructure trade is the obvious one. But there are others — in emerging market credit, in European equities, in the private credit market structure — where the consensus is forming around assumptions that deserve more scrutiny.
Those will be the subject of future pieces.
The working hypothesis is always provisional. That’s the point.
What would change my mind
- This publication tracks five or more theses over 18 months and none are falsified — meaning the falsification conditions were set too loosely to be meaningful
- A better framework emerges for tracking real-time epistemic accountability in market analysis that doesn’t require pre-committing to explicit theses
- The public scorecard model demonstrably fails to change the quality of analysis produced here versus a version without it