🤖 AI Summary
This study addresses the prevalent conflation of on-chain transfer volume with the liquidity of tokenized real-world assets (RWAs). Raw transaction data frequently conflates non-trading operations, such as minting and burning, with genuine economic activity, while intermediary addresses severely distort ownership concentration metrics. Leveraging Ethereum on-chain data, this work introduces an event classification algorithm to systematically isolate non-economic transfers and reconstructs turnover rates and concentration indices by comparing metrics before and after intermediary removal. Results demonstrate that transfer classification substantially alters turnover estimates, and excluding intermediaries paradoxically increases concentration among remaining addresses. By exposing the measurement biases inherent in conventional on-chain metrics within the RWA domain, this research establishes a novel paradigm for accurately assessing true market liquidity.
📝 Abstract
On-chain transfer volume is often used to describe activity in tokenized real-world assets (RWAs), although recorded transfers may reflect very different economic functions, including token creation, destruction, issuer-related operations, and movements between other addresses. Ownership measures face a similar problem because a large address balance may belong to a pool or intermediary that represents multiple investors. We address these two measurement problems by decomposing transfer activity and making ownership coverage explicit. Transfer turnover is calculated before and after observable event categories are separated, using the same asset, observation window, and supply denominator. For ownership, we compare concentration measured against total supply with concentration among the addresses that remain after identified intermediaries are excluded. Using Ethereum-based tokenized funds from December 2025 to August 2026, we find that transfer classification can materially change measured turnover. We also show that removing an intermediary can lower concentration when measured against total supply while concentration among the remaining addresses increases. Transfer activity and address concentration need to be interpreted with their underlying transaction functions and ownership coverage in mind. These measures provide evidence about liquidity-related activity, but they do not directly measure market liquidity. The code and data used in the analysis are available at https://github.com/atytmr07/rwa-liquidity.