The measured version of any claim
is also the convincing version.
Every measurement is pre-registered, content-hashed, and recomputable. This page explains how — because the methodology being public is the proof.
What we guarantee.
We always
- Pre-register methodology before the first measurement
- Content-hash every artifact so results are recomputable
- Publish warts first — our own broker's defects lead
- Preserve original errors verbatim when retracting
- Publish kill ledger entries with the same visibility as registrations
- Publish confidence intervals, effective-N, and honest nulls
- Ship the can-fail proof beside every test
- Research, compute, and build every instrument entirely in-house
We never
- Make performance claims or imply edge
- Use a composite 1–10 rating for broker profiles
- Accept affiliate compensation from brokers we measure
- Silently disappear a killed hypothesis
- Retroactively adjust methodology after seeing results
- Fabricate data, statistics, or completion claims
- Ship a test without proving it can fail
- Resell external analytics or third-party intelligence
From hypothesis to published receipt.
Every measurement passes through six stages. None can be skipped, reordered, or retroactively modified.
Pre-registration
The methodology is written and content-hashed before any data is collected. This hash is the anchor — any post-hoc change to methodology would produce a different hash, and would be visible.
Data collection
Raw data is collected as point-in-time (PIT) snapshots — as-published, never backfilled. The raw archive is content-hashed at ingest. Timestamps are event-clock, not wall-clock where the instrument supports it.
Measurement execution
The pre-registered battery runs against the collected data. No parameter changes, no exclusions, no post-hoc methodology adjustments. The computation is deterministic — same inputs produce same outputs.
Can-fail proof
Every test ships with a demonstration that it could have failed. A test that always passes proves nothing. The can-fail proof is the difference between a measurement and a decoration.
Review & retraction
If an error is found, the original error is preserved verbatim — never deleted, never silently fixed. The correction is appended beside it. The circular denominator retraction is our founding example: the test was asserting its own defect.
Publication
The result — pass, fail, or null — is published with full provenance: methodology hash, data hash, computation hash, can-fail proof status. A kill is published with the same visibility as a registration. No silent disappearances.
Six kinds of receipt.
Process receipts are unfakeable-quickly, safe to publish (they promise nothing about returns), and legible to exactly the customers we want.
Pre-registration
Methodology committed and content-hashed before data collection begins. The hash is the anchor — any change is visible.
registered: 2026-03-14
first_data: 2026-03-16
Content hash
Every artifact — data, code, result — is SHA-256 hashed. The chain proves that declared results came from declared computation on declared data.
code: sha256:<computed from source bytes>
result: sha256:<computed at publication>
Kill ledger
Hypotheses that were registered, tested, and killed. Published with the same visibility as registrations — no silent disappearances.
evidence: linked
kill_date: recorded at the kill
Retraction
Original error preserved verbatim. The correction is appended beside it, never a silent replacement. The error is the proof of the discipline.
status: RETRACTED
correction: appended below
Can-fail proof
Every test ships with a demonstration that it could have failed. The self-test injects a known failure and asserts detection — REFUSED or PASS.
expected: REFUSED BY NAME
result: PASS (defect detected)
Forensic audit
Full investigation published with evidence chain. The agent fabrication audit is the founding example — the system caught its own system lying, and published the proof.
finding: agent fabrication
evidence: full chain published
The measurement cycle
Broker portraits accumulate over time. Each measurement is a snapshot — the profile builds as the history grows. New dimensions add when the battery expands, but existing measurements are never retroactively changed.
Register
Methodology locked, hashed
Collect
PIT data, content-hashed
Measure
Deterministic battery run
Publish
Result + full provenance
Feed Fidelity Battery — dimensions
The full measurement battery applied to each broker profile. Every dimension has a defined method, a can-fail proof, and an honest null.
Four columns: dimension, method, unit, honest null. Scroll sideways if they do not all fit.
| Dimension | Method | Unit | Honest null |
|---|---|---|---|
| Publication cadence | Inter-tick interval distribution, measured as floor (P01) and percentiles | ms | Insufficient ticks in sample |
| Bid-ask coordination | Joint vs. independent update detection via co-occurrence within cadence window | ratio | Indeterminate at current n |
| Staleness distribution | Per-side age since last update at each tick, measured as distribution | ms | Single-sided feed (no opposing quotes) |
| Spread regimes | Regime detection via change-point analysis on spread series | count | Insufficient variance for regime separation |
| Freeze / rollover | Gap detection + quote-age analysis during contract boundaries | behaviour | No rollover events in sample window |
| Non-crossing | Assertion: bid < ask at every observed tick | boolean | N/A (always computable) |
Methodology, per instrument family
Each suite measures a different discipline, so each carries its own battery and its own receipts. The full per-suite methodology pages: