Source registry

Every claim needs a boundary

Observed, calculated, estimated, projected, and inferred evidence remain visibly distinct. Attached PDFs are research inputs, not runtime dependencies and are not published here.

Observed

Displayed by the cited source at a stated date.

Calculated

Computed by CryptoImmovables from disclosed source values.

Estimated

Modeled by the publisher rather than counted directly.

Projected

A future scenario, not present market value.

Inferred

An interpretation bounded by the source and method.

01

live market snapshot

Tokenized Real Estate

RWA.xyz · Published 2026-08-22 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • The dated public snapshot reported $226.44M distributed value, $279.85M represented value, 19.36K holders, 853 monthly active addresses, 105 assets, and 11 countries.
  • Distributed value rose 11.59% over 30 days while monthly active addresses fell 25.04% over the same stated period.
  • The visible distributed platform table listed Groma, Reental, DigiShare, Securitize, RealtyX, BT Asset Hub, and Ondo at the displayed values.
  • RWA.xyz publicly defines distributed and represented assets by external-wallet mobility and peer-to-peer transferability.

Limitations

  • This is a dated snapshot, not a licensed live feed or a complete republication of the RWA.xyz database.
  • Locked market-share fields are unavailable and are not reproduced.
  • Displayed platform values are rounded; concentration calculations using them are approximate.
  • The snapshot shows a Hybrid label for one row, but a current public definition was not verified; CryptoImmovables does not define it.
  • Address and holder counts do not establish unique people, liquidity quality, legal ownership, or investment merit.
Evidenceobserved · calculated
Page / section referencesPDF pp. 1-3: headline metrics, chart timestamp, platform league table; PDF pp. 4-9: visible asset rows and tokenization-type labels; RWA.xyz Documentation: Methodology / Tokenization Type
02

empirical working paper

When bricks meet bytes: does tokenisation fill gaps in traditional real estate markets?

Bank for International Settlements · Published 2026-06-30 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • In the studied U.S. platform dataset, areas with weaker access to traditional credit showed faster growth in tokenized properties.
  • Trading rose by 35% cumulatively over the two days following a disaster declaration in the studied dataset.
  • The observed liquidity response depended on platform buyback features, creating a solvency trade-off.

Limitations

  • A BIS working paper reports the author's research and not necessarily BIS policy.
  • The analysis is U.S.-focused, covers selected property-level platforms and 2019-2025 data, and should not be generalized to all tokenized real estate.
  • The 35% result is an empirical event-study finding, not a guarantee that tokenization creates liquidity in other settings.
  • Buyback liquidity can fail or amplify stress when the supporting platform lacks capacity.
Evidenceobserved · calculated · inferred
Page / section referencesPDF p. 3: abstract and headline results; PDF pp. 19-22: sample, coverage, and descriptive statistics; PDF pp. 31-33: access-to-credit design; PDF pp. 35-38: disaster-event results and buyback mechanism; PDF pp. 46-47: conclusions and boundaries
03

policy paper

Tokenisation of assets and distributed ledger technologies in financial markets

OECD · Published 2025-01-09 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • The OECD identifies limited liquidity, ecosystem scale, custody, payment rails, interoperability, identification, standards, accounting, and legal recognition as adoption barriers.
  • Ownership of a token does not necessarily confer ownership of the underlying asset.
  • Policy should remain technology-neutral while addressing risks that may be more acute in DLT-based finance.

Limitations

  • The paper identifies possible impediments and policy considerations; it does not certify individual platforms or forecast market size.
  • Barriers vary by jurisdiction, asset, network design, and market structure.
Evidenceobserved · inferred
Page / section referencesPDF pp. 5-6: contents and executive summary; PDF pp. 10-13: liquidity, ecosystem scale, and investment rationale; PDF pp. 14-17: payment rails and settlement; PDF pp. 17-20: custody, interoperability, identity, standards, accounting, and legal issues; PDF pp. 21-22: technology-neutral policy considerations
04

regulatory guidance

Guidelines on the conditions and criteria for the qualification of crypto-assets as financial instruments

European Securities and Markets Authority · Published 2024-12-17 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • Classification is technology-neutral and focuses on economic function, rights, and obligations rather than the token label or technical form.
  • A crypto-asset qualifying as a financial instrument is subject to MiFID II rather than MiCA.
  • Classification requires a complete, case-by-case assessment.

Limitations

  • The guidance does not provide an automated legal conclusion for a specific offering.
  • National implementation, other EU rules, non-EU law, and the facts of an offering still matter.
  • MiCA status alone does not establish that an offering is lawful or suitable.
Evidenceobserved
Page / section referencesPDF p. 17: MiFID II rather than MiCA where the token is a financial instrument; PDF p. 27: rights, obligations, substance over form, and case-by-case analysis; PDF pp. 33-35: purpose, technology neutrality, and transferable-security criteria; PDF pp. 39-46: other financial-instrument categories and crypto-asset assessment
05

commercial forecast

Digital dividends: How tokenized real estate could revolutionize asset management

Deloitte Center for Financial Services · Published 2025-04-24 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • Deloitte forecasts $4T of tokenized real estate by 2035, versus less than $0.3T in 2024, at a stated 27% CAGR.
  • Deloitte separately forecasts $1T in private real estate funds, $2.39T in loans and securitizations, and $50B in undeveloped land and under-construction projects by 2035.

Limitations

  • These are projections, not current market values or an official census.
  • The method is a meta-analysis of market-size forecasts combined with Deloitte penetration assumptions.
  • The three detailed segments shown do not arithmetically equal the $4T headline and should not be presented as an exhaustive reconciliation.
Evidenceprojected · estimated
Page / section referencesPDF pp. 1-3: global and segment forecasts; PDF pp. 4-6: structures, operational considerations, and risks; PDF p. 7: forecast method and professional-advice limitation
06

adoption report

The 2025 Global Adoption Index

Chainalysis · Published 2025-09-02 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • India ranked first and the United States second in the 2025 composite index.
  • The methodology separates retail-sized centralized activity below $10,000 and institutional-sized activity above $1M, alongside other sub-indices.
  • APAC led grassroots activity while North America and Europe remained larger in absolute received value in the report period.

Limitations

  • Country transaction volumes are estimates informed by service web traffic; VPNs and location attribution introduce uncertainty.
  • The index changed methodology in 2025, limiting simple year-to-year comparisons.
  • Transfer-size categories are proxies and do not identify every actor's true retail or institutional status.
  • The report does not measure demand for tokenized real estate specifically.
Evidenceestimated · calculated · inferred
Page / section referencesPDF pp. 2-6: methodology and retail/institutional sub-indices; PDF pp. 6-11: rankings and geographic interpretation; PDF pp. 20-24: coverage caveats, corrections, and limitations
07

wealth estimate

The Crypto Wealth Report 2025

Henley & Partners / New World Wealth · Published 2025-09-23 · Reviewed 2026-08-23

Open source ↗

Claims permitted

  • The report estimates 241,700 crypto millionaires and 590M crypto users as of 30 June 2025.
  • The wealth figures use in-house wealth-tier models, a progressive Lorenz-curve distribution, and open-source information on large holdings.

Limitations

  • The figures are modeled commercial estimates, not an official census or verified count of named individuals.
  • Holdings may be pseudonymous, shared, custodial, lost, or otherwise difficult to attribute to people.
  • The report does not establish willingness or eligibility to invest in tokenized property.
Evidenceestimated · inferred
Page / section referencesPDF pp. 2-3: worldwide wealth statistics and as-of date; PDF p. 4: in-house model description; PDF pp. 12-14: disclaimers and publication date