Beyond the surface: advanced wash-trading detection in decentralized NFT markets

Abstract Wash trading in decentralized markets remains a significant concern magnified by the pseudonymous and public nature of blockchains. In this paper, we introduce an innovative methodology designed to detect wash-trading activities beyond surface-level transactions. Our approach integrates NFT ownership traces with the Ethereum Transaction Network, encompassing the complete historical record of all Ethereum-account normal transactions. By analyzing both networks, our method offers a notable advancement over techniques proposed in existing research. We analyzed the wash-trading activity of 7 notable NFT collections. Our results show that wash trading in unregulated NFT markets is an underestimated concern and is much more widespread in terms of both frequency and volume. Excluding the Meebits collection, which emerged as an outlier, wash trading constitutes up to 24% of the total trading volume. Specifically, for the Meebits collection, 93% of the total trade volume was attributed to wash trading.