Falsifiable NEAR

A 3–5 year thesis, scored in public

A NEAR thesis that can fail in public.

The claim: NEAR's value engine has moved from blockspace to Intents, and captured Intents revenue can grow faster than token dilution. We split that into six plain claims, each with a frozen pass/fail rule, and re-grade them on public data every day. Failing claims stay on the page.

Intents volume, 12 months
$33B

+207% YoY (90d window)

Captured revenue, annualised
$21.2M

+202% vs prior 90d

Take rate reaching holders
4.23 bps

Of Intents swap volume, trailing 90d

Daily active accounts
-75%

Trailing 90d vs a year earlier

Holder value ÷ dilution
0.19×

Needs ≥ 1.00× to offset issuance

Gross issuance, 12 months
2.51%

Of total supply minted per year

Claims holding, weekly1/6 → 3/6

Earlier points are backfilled with the frozen rules, so descriptive only. Out-of-sample points so far: 1.

Live pulse

Updated 00:47:07 UTC

NEAR price
$3.05
24h change
-11.7%
Intents volume 24h
$168.7M
Intents volume 7d
$865M
Chain TPS
8
All-time txns
5.5B

Snapshot model uses a 7-day average price of $3.61. Live values are shown for context and do not change any test result until the snapshot is rebuilt.

Falsification scorecard

Six tests, thresholds frozen at thresholds-v1

Each test has a numeric threshold in one constant in the pipeline (scripts/fetch_public.py). A unit test pins its hash, so the rules cannot be tuned without failing CI. Every rebuild is graded with the same rules, so a failing test can flip, and so can a passing one.

Disclosure: the thresholds were chosen after a first look at the 2026-11-12 snapshot, so results on that snapshot are in-sample. They were frozen on 2026-11-13; only results from later snapshots are out-of-sample. This snapshot: out-of-sample · sha256:b9548c7a9ca0…

  1. T1 · Demand

    Holds

    More money is swapping through NEAR Intents than a year ago

    Current
    3.07×
    Frozen threshold
    ≥1.50×

    205% of the pass linefail < 1.00×

    Intents volume, trailing 90d vs same 90d one year earlier

    pass ≥ 1.50x · fail < 1.00x · otherwise inconclusive

  2. T2 · Monetisation

    Holds

    NEAR is capturing more of that flow as revenue

    Current
    3.02×
    Frozen threshold
    ≥1.10×

    275% of the pass linefail < 0.90×

    NEAR holders revenue (buyback-directed), trailing 90d vs prior 90d

    pass ≥ 1.10x · fail < 0.90x · otherwise inconclusive

  3. T3 · Adoption

    Fails

    People still use the NEAR base layer

    Current
    0.25×
    Frozen threshold
    ≥0.90×

    28% of the pass linefail < 0.75×

    Avg daily active accounts, trailing 90d vs same 90d one year earlier

    pass ≥ 0.90x · fail < 0.75x · otherwise inconclusive

  4. T4 · Activity quality

    Holds

    Each remaining user pays more in fees

    Current
    1.98×
    Frozen threshold
    ≥1.00×

    198% of the pass linefail < 0.80×

    Gas fees per active account, trailing 90d vs one year earlier

    pass ≥ 1.00x · fail < 0.80x · otherwise inconclusive

  5. T6 · Market signal

    Fails

    Intents activity moves before the NEAR price

    Current
    0.079
    Frozen threshold
    >0.251

    32% of the pass lineno inconclusive band

    Max weekly lead correlation (1–4w) vs Bonferroni critical r

    pass if best leading r > critical r (0.2513) over 99 weeks · otherwise fail

Track record

27 weekly gradings, same frozen rules

Every column re-grades all six claims as of that week's data, using exactly the thresholds at thresholds-v1. From May 15, 2026 to Nov 13, 2026 the score moved from 1/6 to 3/6.

Read this as descriptive. These weeks are backfilled with rules chosen in November 2026, after the data was seen, so they show how the claims would have read, not a forecast that came true. Columns after Nov 12, 2026 are out-of-sample: 1 so far. The weekly grid is anchored to the latest snapshot, so the count grows by one each week; every committed snapshot stays in git history.

Weekly pass or fail result for each of the six claims from May 15, 2026 to Nov 13, 2026
ClaimMay 15, 2026Nov 13, 2026Flips
T1 More money is swapping through NEAR Intents than a year ago
0
T2 NEAR is capturing more of that flow as revenue
2
T3 People still use the NEAR base layer
0
T4 Each remaining user pays more in fees
2
T5 Buybacks and burn outweigh new token issuance
0
T6 Intents activity moves before the NEAR price
0
Claims holding3/6
  • pass
  • inconclusive
  • fail
  • no data
  • Source: data/public.json · history

Pillar 1 · Demand & monetisation · T1, T2

Intents demand is compounding, and NEAR is now capturing part of it

NEAR Intents lets users and agents swap assets across chains, with settlement coordinated on NEAR. Weekly swap volume is the leading indicator of demand. Captured revenue is the share NEAR sweeps to its revenue wallets. Since 23 Feb 2026, that revenue has funded open-market NEAR buybacks.

Weekly Intents swap volume vs captured revenue

Complete ISO weeks · USD · DefiLlama

Volume, trailing 90d
$12.4B

+207% YoY · +87% QoQ

Gross Intents fees, 12m
$53.9M

Protocol + frontend affiliate fees

Captured revenue, 90d
$5.2M

+202% vs prior 90d

Effective take rate
0.042%

4.23 bps of volume reaches holders

Pillar 2 · Base-layer adoption · T3, T4

Base-layer activity collapsed, but what remains pays more per account

A thesis that ignored this chart would not survive review. Daily active accounts and transactions are down sharply year over year. Gas fees per active account nearly doubled over the same period, which is consistent with incentive and bot traffic leaving and higher-value usage staying. The data supports that reading but cannot prove it.

Average daily active accounts and transactions, weekly

Distinct signer accounts, not humans · NearBlocks

Active accounts / day, 90d
71.8K

-75% vs 288.3K a year ago

Transactions / day, 90d
752.2K

-84% vs 4.6M a year ago

Gas fees per active account
$0.059

+98% YoY · daily average

Pillar 3 · Value accrual · T5

The gap that decides the thesis: holder value vs dilution

NEAR mints new supply every year. Holders are compensated by two flows: 70% of gas fees are burned, and captured Intents revenue is spent on buybacks. Coverage compares those flows with the dollar value of new issuance. Below 1.0×, a non-staking holder is being diluted.

Monthly holder value vs value of new issuance

Issuance = Δ total supply + burned NEAR, at monthly average price · complete months only

Gross issuance, 12m
32.1M NEAR

2.51% of supply · $115.9M at today's price

Holder value, annualised
$22.3M

Buybacks $21.2M + burn $1.1M

Coverage
0.19×

Holder value must grow 5.2× to offset dilution

Market cap ÷ holder value
201×

Market cap $4.5B

Market signal · T6

Does Intents activity lead the NEAR price? Not yet.

The first draft of this thesis listed this question as untested because it had no price history. We added a price series and fixed the method in advance: weekly log changes, lags of −4 to +4 weeks, and a Bonferroni-adjusted threshold across the four leading lags. No lag clears the bar.

Correlation by lag (positive = Intents leads price)

Dashed lines: critical |r| = 0.251 over 99 weeks

T6 resultFails
Strongest leading lag
4w · r=0.079

n=95 weekly pairs

Same-week correlation
-0.004

Scenario model · re-run it yourself

How fast must Intents grow for holders to stop being diluted?

Year 0 is the measured baseline from the snapshot. Coverage each year is (Intents volume × take rate + gas burn) ÷ (supply × issuance rate × price). Price is held constant on purpose: this is a sensitivity analysis of the token's economics, not a price target.

+50%

Measured trailing YoY: 207%

4.25 bps

Measured 90d: 4.25 bps

2.5%

Measured 12m: 2.5%

+10%

Gas burn is small either way

Coverage today
0.19×
Coverage, year 5
1.22×
Break-even growth
44%/yr

Holder value overtakes dilution in year 5.

Scenario projection by year
YearIntents volumeBuybacks + burnIssuance valueCoverage
Y0$50.2B$22.4M$118.8M0.19×
Y1$75.3B$33.2M$121.8M0.27×
Y2$113B$49.3M$124.8M0.40×
Y3$169.5B$73.5M$128M0.57×
Y4$254.2B$109.6M$131.2M0.84×
Y5$381.3B$163.8M$134.5M1.22×

Deep dive · raw chain data

Cross-check against the BigQuery public NEAR dataset

Aggregators can be wrong. The second pipeline queries raw transactions and receipts from bigquery-public-data.crypto_near_mainnet_us using versioned SQL, so anyone can audit signer counts and contract usage without relying on NearBlocks.

Active signers / day, last 90d
71.8K
Transactions / day, last 90d
747.2K
Window
90d

Aug 15, 2026 – Nov 12, 2026

Matches NearBlocks exactly
13/13

Weeks where signers and txns equal NearBlocks

Raw-chain counts reproduce the NearBlocks figures behind T3 to the unit in every comparable week, so the base-layer numbers above are not an aggregator artifact. This confirms NearBlocks; it is not a second, differently-defined measurement.

Top contracts by function-call receipts
ContractReceiptsOriginating txnsSigner-days
token.sweat17.8M14M4.3K
v2.ref-finance.near11.7M10M81.7K
intents.near11.5M8.8M33.2K
cooldogsclub.near10.8M503.5K51
game.hot.tg9.5M9.4M5.2M
v2.jars.sweat8.6M6.7M112
wrap.near8.5M5.2M151K
dclv2.ref-labs.near7.1M4.4M99.2K
claim.sweat6.6M4.8M91
17208628f84f5d6ad33f0da3bbbeb27ffcb398eac501a31bd6ad2011e36133a15.7M3.3M50.2K

Imported from BigQuery console exports of sql/daily_usage.sql and sql/contract_usage.sql. Raw exports are committed under data/bigquery/.

Methodology & reproducibility

Every number on this page comes from one command

Window: Nov 14, 2024 – Nov 13, 2026 (730 days). Snapshot generated Sat, 14 Nov 2026 04:26:27 GMT. No API keys, no hand-entered numbers, no sample data.

Re-run the analysis

git clone https://github.com/zecvilan/falsifiable-near && cd falsifiable-near
make data    # python3 scripts/fetch_public.py  (stdlib only)
make test    # unit tests for the statistics + aggregation
make dev     # dashboard at http://localhost:3000
Sources
EndpointFeeds
NearBlocks charts APITransactions, active/new accounts, price, total supply
DefiLlama · NEAR chain feesDaily gas fees (USD)
DefiLlama · NEAR chain revenueBurned share of gas fees (70%)
DefiLlama · NEAR Intents volumeDaily swap input volume (USD)
DefiLlama · NEAR Intents feesGross protocol + affiliate fees
DefiLlama · NEAR Intents holders revenueCaptured revenue directed to buybacks

Known limitations

  • NearBlocks 'active_accounts' counts distinct signer accounts, not humans; part of the year-over-year decline reflects the end of high-volume incentive and bot campaigns, which this data cannot separate from organic churn.
  • DefiLlama Intents volume counts swap input notional; it is not revenue. Holders revenue is NEAR's captured share swept to revenue wallets and, since 2026-02-23, used for open-market buybacks (DefiLlama methodology). Buybacks are treated as holder value in USD, not as burned supply.
  • Issuance is measured from the change in total supply plus burned NEAR; staking rewards are a transfer to stakers, so non-staked holders bear the dilution measured here.
  • NearBlocks circulating supply appears static; total supply is used for all supply calculations.
  • The lead/lag test is correlational over a short history and says nothing about causality. Its lags, frequency and critical value were set after the 2026-11-12 snapshot had been seen and are frozen since tag thresholds-v1; changing them would invalidate it.
  • Only keyless public aggregators are used here. The BigQuery pipeline (scripts/rebuild.py) gives contract-level detail from raw chain data and needs Google Cloud credentials.