> ## Documentation Index
> Fetch the complete documentation index at: https://tokenterminal.com/docs/llms.txt
> Use this file to discover all available pages before exploring further.

# Registry

> Tokenized asset identity and the underlyings the tokens stand for.

Tokenized asset identity lives in the shared asset registry tables, under `asset_type in ('tokenized-stocks', 'tokenized-funds', 'tokenized-commodities', 'tokenized-cryptoasset')`.

* [`dimensions.assets`](/docs/catalog/assets/registry): one row per tokenized asset.
* [`dimensions.asset_tokens`](/docs/catalog/assets/registry): one row per chain each asset is issued on.
* [`dimensions.reference_assets`](/docs/catalog/assets/registry): the things those assets stand for, equities to cryptoassets.

Every column is documented at [Assets ▸ Registry](/docs/catalog/assets/registry).

## Sample queries

<Tabs>
  <Tab title="Assets by type">
    **Count tokenized assets by type.**

    ```sql theme={null}
    select
        asset_type,
        count(*) as assets
    from `dimensions.assets`
    where asset_type in (
        'tokenized-stocks', 'tokenized-funds',
        'tokenized-commodities', 'tokenized-cryptoasset'
    )
    group by asset_type
    order by assets desc
    ```
  </Tab>

  <Tab title="One underlying's tokens">
    **List every issuer's token for one underlying.** Each token's name says who issued it.

    ```sql theme={null}
    select
        assets.asset_id,
        assets.name,
        assets.symbol
    from `dimensions.assets` as assets
    join `dimensions.reference_assets` as reference_assets
        using (reference_asset_id)
    where reference_assets.reference_asset_id = 'nvda'
      and assets.asset_type = 'tokenized-stocks'
    order by assets.asset_id
    ```
  </Tab>

  <Tab title="Most-tokenized underlyings">
    **Rank underlyings by how many tokens stand for them.**

    ```sql theme={null}
    select
        reference_assets.reference_asset_id,
        reference_assets.name,
        reference_assets.type,
        count(*) as instruments
    from `dimensions.assets` as assets
    join `dimensions.reference_assets` as reference_assets
        using (reference_asset_id)
    where assets.asset_type in (
        'tokenized-stocks', 'tokenized-funds',
        'tokenized-commodities', 'tokenized-cryptoasset'
    )
    group by 1, 2, 3
    having count(*) > 1
    order by instruments desc
    ```
  </Tab>
</Tabs>

## Notes

`reference_assets` is the list of things tokenized assets stand for. Each row names one, classifies it in `type`, and points back to a tokenized asset through `linked_asset_id` where one exists. Some references are broad categories rather than single securities, such as `etf` and `realestate`, so the biggest counts land on those rather than on individual companies.

`type = 'fiat'` is what makes a reference a currency peg, and `currency_code` is filled in on the `fiat` rows only. The stablecoin columns `peg_currency` and `mica_indicator` on `assets` are both worked out from that pair. A reference that is a fund strategy, an equity or a commodity leaves `peg_currency` empty on its assets, rather than passing a non-currency label through as if it were one.