Tokenized stocks are considered RWA (Real World Assets). They include several subcategories, such as: 1. **Equity Tokens**: Represent ownership in a company. 2. **Debt Tokens**: Represent loans or bonds issued by companies. 3. **Real Estate Tokens**: Represent ownership or shares in real estate properties. 4. **Commodity Tokens**: Represent physical commodities like gold or oil. 5. **Art Tokens**: Represent ownership in artworks or collectibles.
"Tokenized assets" is a broad term that can encompass many things—but the first step in research is to distinguish: tokenized stocks, tokenized U.S. Treasuries, and tokenized gold, while similar in name, are three types of products with significant differences in product structure, holder structure, and trading venues. Mixing them together for statistics is a common classification issue in RWA research.
Who is this article suitable for?
- Industry researchers building RWA classification frameworks;
- Analysts who need to classify tokenized stocks in reports;
- Observers entering from the traditional RWA (government bonds/credit) field, needing to understand the differences in stock categories.
Understanding differences through a lineage chart
Tokenized U.S. Treasury bonds/money market funds: holding-type products. Users hold rights to income, and the product's value is mainly reflected in the holding phase; common metrics are TVL and yield, with venues concentrated in DeFi protocols and a few platforms.
Tokenized gold/commodities: hedging-type products. The purpose of holding is often asset allocation, with moderate trading activity; common metrics are premium rates (deviation from spot gold).
Tokenized stocks: trading-type products. Trading hours are close to 7×24, with derivatives contracts occupying a large proportion; common metrics are trading volume, depth, and shares. Compared to the other two categories, its scale observation usually focuses more on trading metrics—this is a difference in product attributes, not the only measure. The implications of this classification will directly affect the choice of metrics in each chapter of the report.
The fourth category is easily overlooked: stock derivative contracts issued by exchanges (non-tokenized synthetic products). It does not provide underlying asset mapping and belongs to the category of synthetic contracts; when statistically measuring the market size of tokenized stocks, it is advisable to list them separately from contract forms and indicate the metrics to avoid confusion. Tokenized asset dashboard supports viewing four types of forms separately. Taking QQQ as an example, the detail page simultaneously presents its tokenized version and various exchange contract forms, making the classification comparison clear at a glance.
Three disciplines for statistics
- Classification first: group by holding-type/hedging-type/trading-type, then compare within groups;
- Form isolation: list tokenized stocks and stock derivative contracts separately, with annotations explaining the metrics;
- Consistent sources: all category data within the same report should use the same data source to avoid inconsistencies across sources.
Usage restrictions
- The classification framework serves as a research methodology, and the specific classification of products is subject to their issuance documents;
- Data for each form is point-in-time data, based on the current display of the tokenized asset dashboard ; for metric issues, see Tokenized asset FAQ .
Use this classification framework to check your report structure
Open the tokenized asset dashboard and filter through the data distribution of the four types of forms by asset category—your classification framework will have its first set of empirical materials. The comprehensive coverage under the categories, along with "What traditional assets have been tokenized?", forms a part of the tokenized asset section of the RWA research series.
