The Dark Side of NFTs: A Large-Scale Empirical Study of Wash Trading
Shijian Chen, Jiachi Chen, Jiangshan Yu, Xiapu Luo, Yanlin Wang
TL;DR
This work provides the most comprehensive empirical study of NFT wash trading to date, analyzing 8,717,031 transfer events and 3,830,141 sale events across 2,701,883 NFTs. It defines three wash-trading types—Round-trip, Unprofitable, and Hidden—and proposes heuristic detection algorithms augmented by FP-Growth to identify wash-trading address pairs/groups. The study reports 824 transfer events, 5,330 sale events, 370 address pairs, and 29 groups linked to wash trading, totaling $8,857,070.41 in value, with detailed findings on marketplace design, profitability, project design, payment tokens, user behavior, and ecosystem implications. The results underscore that a small minority of actors can drive sizable wash-trading activity, reveal gaps in current marketplace safeguards, and motivate practical recommendations for detection and alerting integrated into NFT platforms.
Abstract
NFTs (Non-Fungible Tokens) have seen significant growth since they first captured public attention in 2021. However, the NFT market is plagued by fake transactions and economic bubbles, e.g., NFT wash trading. Wash trading typically refers to a transaction involving the same person or two colluding individuals, and has become a major threat to the NFT ecosystem. Previous studies only detect NFT wash trading from the financial aspect, while the real-world wash trading cases are much more complicated (e.g., not aiming at inflating the market value). There is still a lack of multi-dimension analysis to better understand NFT wash trading. Therefore, we present the most comprehensive study of NFT wash trading, analyzing 8,717,031 transfer events and 3,830,141 sale events from 2,701,883 NFTs. We first optimize the dataset collected via the OpenSea API. Next, we identify three types of NFT wash trading and propose identification algorithms. Our experimental results reveal 824 transfer events and 5,330 sale events (accounting for a total of \$8,857,070.41) and 370 address pairs related to NFT wash trading behaviors, causing a minimum loss of \$3,965,247.13. Furthermore, we provide insights from six aspects, i.e., marketplace design, profitability, NFT project design, payment token, user behavior, and NFT ecosystem.