发表机构
Antalya Bilim University; Universiti Brunei Darussalam; Western Sydney University（安塔利亚科技大学; 文莱达鲁萨兰大学; 西悉尼大学）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
针对代币化现实世界资产中链上转移量和所有权度量的误导性问题，本文提出分解转移活动并明确所有权覆盖范围的方法，实证表明分类可显著改变周转率，且这些度量不直接等于市场流动性。
AI 中文摘要
链上转移量常被用来描述代币化现实世界资产（RWAs）的活动，尽管记录的转移可能反映不同的经济功能，包括代币创建、销毁、发行方相关操作以及其他地址之间的移动。所有权度量面临类似问题，因为一个大额地址余额可能属于代表多个投资者的池或中介机构。我们通过分解转移活动并明确所有权覆盖范围来解决这两个度量问题。转移周转率是在可观察事件类别被分离前后计算的，使用相同的资产、观察窗口和供应量分母。对于所有权，我们将针对总供应量测量的集中度与在排除已识别中介机构后剩余的地址中的集中度进行比较。使用2025年12月至2026年8月基于以太坊的代币化基金，我们发现转移分类可以显著改变测量的周转率。我们还表明，当针对总供应量测量时，移除中介机构可以降低集中度，而剩余地址中的集中度则增加。转移活动和地址集中度需要结合其底层交易功能和所有权覆盖范围来解释。这些度量提供了关于流动性相关活动的证据，但它们并不直接衡量市场流动性。分析中使用的代码和数据可在该https URL获取。
英文摘要
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.
