Raymond Chai built a
falsifiable thesis.
This is the test.
Raymond Chai proposed that 93% of on-chain economic activity flows through stablecoins — and he defined five specific conditions under which he would be wrong. This tool holds those conditions to live data. No predetermined verdict. No narrative. The investigation is open, the methodology is visible, and the finding — whatever it is — gets documented.
Raymond Chai put a thesis into the public record. When Paul Faulkner asked for the model behind the number, Raymond built the derivation live — in the comments, in real time, unprompted.
That intellectual honesty is the reason this is Lab Case 001. The Lab only investigates theses whose originators are willing to be named and willing to engage with a test. Raymond meets both conditions. The investigation is collaborative by design — he has seen the methodology, he is invited to challenge the test design, and any error he identifies gets corrected and credited.
This tool does not exist to destroy the thesis or to validate it. It exists to find out what the data actually says — and to document that finding transparently, whatever it turns out to be. The data decides. Not the narrative.
If any one of these triggers, the model fails
Raymond defined the conditions himself. We test them as stated. Conditions 1, 2, and 5 update automatically from live APIs. Conditions 3 and 4 require quarterly manual input and are flagged accordingly.
The headline number does not survive its own maths
This is a neutral forensic audit of the derivation Raymond provided in the LinkedIn thread. We are not arguing he is wrong about stablecoin dominance — we are auditing whether the 7% figure is internally consistent with the calculation steps he gave.
Rich list addresses with ≥1 BTC ≈ ~825,000 (addresses, not people)
With ≥10 BTC ≈ 130,000
With ≥100 BTC ≈ 18,000
Combined just under 1M addresses hold ≥1 BTC
STEP 2 — GLOBAL FINANCIAL SYSTEM
Global population ≈ 8.2B
Adults with financial access ≈ 5.5B
Active digital payment users ≈ 1–2B
STEP 3 — THE 7% CALCULATION
Monthly active crypto users ≈ 300–500M
On-chain stablecoin volume ≈ 80–90%
∴ Bitcoin-primarily users = 10% × 400M = 40M
40M ÷ 8.2B global population = 0.5%
40M ÷ 5.5B adults with access = 0.7%
40M ÷ 1.5B digital payment users = 2.7%
40M ÷ 400M crypto users = 10.0%
Raymond’s stated headline: ≈ 7%
~825k addresses hold ≥1 BTC · ~130k hold ≥10 BTC · ~18k hold ≥100 BTC · 4 addresses hold ≥100,000 BTC
Note: addresses ≠ people. Exchanges, ETF custodians, and custodial wallets aggregate millions of users behind single addresses.
Addresses with ≥1 BTC: ~824,957
Addresses with ≥10 BTC: ~130,280
Addresses with ≥100 BTC: ~18,173
Addresses with ≥1,000 BTC: ~1,941
Total addresses with any BTC: ~49.6M
WHAT THIS PROVES
BTC is highly concentrated ✓
Most addresses hold dust/small amounts ✓
WHAT THIS DOES NOT PROVE
How many people use Bitcoin primarily ✗
What % of users transact vs hold ✗
ETF/custodial holders don’t appear here ✗
To his credit, Raymond flagged two significant weaknesses unprompted. These are not our criticisms — they are his own:
-
Wash trading and genuine vs exchange-related volume. “I don’t have a good way to measure genuine economic activity vs exchange-related wash trading. Both Artemis and TokenTerminal try to filter out noise, but it’s imperfect.” This caveat is potentially model-busting: if 40–60% of stablecoin volume is circular bot traffic, the genuine ratio could look materially different.
-
Regulatory discontinuity risk. “The model assumes current regulatory trends continue. A global ban on unhosted stablecoin wallets or mandated on-chain KYC could change everything.” This is a fat-tail risk not captured in the five falsifiable conditions, which are all volume/usage metrics.
-
The 7% figure is self-described as a framing device. Raymond confirmed: “The 7/93 is a framing device for a real phenomenon.” This is intellectually honest but means the headline number should not be treated as a derived measurement. This tool tests the conditions, not the headline ratio.
-
Bitcoin’s L1 settlement value is excluded from the denominator. The model counts stablecoin transaction volume on Ethereum/Solana/Tron/BNB, but Bitcoin’s base-layer settlement of large OTC trades, ETF creations, and corporate treasury moves runs to tens of billions daily. If included, the economic value ratio shifts materially.
