Track record

We grade our own readings.

A schema is only as useful as it has been right. Palanor scores its own predictions against what the indicators actually showed in the quarters that followed. The methodology is public, the data is sourced, and the track record is here.

Methodology

For each historical reading at time T, the distiller re-scores the schema at T + 90 days using the indicators present at that later moment. The retrospective stage is treated as ground truth.

Exact stage match — correctness 1.0
Off by one stage — correctness 0.5
Off by two stages — correctness 0.0
Off by three or more — correctness -0.5

Accuracy is the confidence-weighted average of correctness, clipped to 0..1. Schemas with too few historical readings show "insufficient data" rather than a fabricated score. Only live readings — written in real time — are graded. Retrospective readings (pre-launch quarterly backfills) are visible on the Schema Index for orientation but excluded from accuracy scoring, because scoring against indicators we already had is not the same thing as predicting the future.

Schema	Author	Accuracy
AI Margin Compression	Palanor (Tim Woodring)	insufficient data
Capital window closure schema	Palanor	insufficient data
Defense + national security schema	Palanor	insufficient data
Energy industry schema	Palanor	insufficient data
Financial Instability Hypothesis	Hyman Minsky	insufficient data
Howard Marks Market Cycle	Howard Marks (Oaktree)	insufficient data
Hype Cycle	Popularized by Gartner	insufficient data
Kondratiev Long Wave	Nikolai Kondratiev	insufficient data
Marathon Capital Cycle	Marathon Asset Management	insufficient data
Real estate industry schema	Palanor	insufficient data
Rolling Recession	Popularized by Liz Ann Sonders; refined by Torsten Sløk and contemporary macro analysts	insufficient data
SaaS industry schema	Palanor	insufficient data
Shiller CAPE Regime	Robert Shiller	insufficient data
Soros Reflexivity	George Soros	insufficient data
Talent cycle tightening schema	Palanor	insufficient data
The Big Cycle	Ray Dalio	insufficient data