Suspicious trading in nonfungible tokens (NFTs)

Abstract

This paper employs a three-pronged approach to examine price patterns in a substantial chunk of trades in nonfungible token (NFT) transactions to identify suspicious trading activities. Tests based on Benford's Law, clustering via Student's t-test, and Pareto–Levy analyses identify nonconformity. This potentially signals manipulation. Reapplying Benford's Law to a subset of 50 highly popular NFTs’ trading volumes, we observe adherence in first and second digits. To ensure robustness, we re-apply a χ2 test and the Mean Absolute Deviation statistic and notice that the principal findings accord with contemporary research on cryptocurrencies and certain asset classes in the traditional financial markets. Our findings constitute further evidence on the Wild Wild West nature of emerging digital asset markets and underscore the need for regulation to prevent market abuse and instill investor confidence.