Tokenized but Illiquid? Evidence from Real-World Asset Markets

Battle Count: 65

The paper is moderately relevant to quantitative trading. It provides empirical evidence on liquidity conditions in tokenized RWA markets, which is directly useful for traders and portfolio managers considering tokenized Treasuries, gold, or private credit as tradable instruments. The finding that size does not predict liquidity and that participation breadth matters more than scale has practical implications for position sizing and execution strategy. However, the paper does not develop trading signals, backtest strategies, or model price dynamics. Its contribution is more in market structure understanding and liquidity measurement than in direct alpha generation or execution optimization.

The empirical methodology is straightforward and uses standard econometric tools: descriptive statistics, Kruskal-Wallis tests, Spearman correlations, and panel OLS with fixed effects. No machine learning, deep learning, or complex optimization is involved. The main implementation challenge lies in data collection (manually constructing the token-month panel from RWA.xyz and Etherscan) rather than in the statistical analysis itself. A researcher with standard econometrics training could replicate the analysis given access to the underlying data.

The primary data sources (RWA.xyz and Etherscan) are publicly accessible, but the token-month panel was manually collected and constructed by the author. The specific monthly snapshots, variable definitions, and panel construction process are described in detail, but the raw collected dataset is not explicitly linked or deposited. The empirical strategy (Kruskal-Wallis, panel OLS with fixed effects) is standard and reproducible given the data. The small sample size (9 tokens, 6 months) limits generalizability but aids verification.