Abstract

Non-fungible tokens (NFT) have recently emerged as a novel blockchain-hosted financial asset class that has attracted major transaction volumes. However, preprocessing and analysis of NFT transaction data, which investors often rely on for their investment decisions, pose several challenges not commonly encountered in traditional financial data. These challenges arise mainly due to the non-fungible nature of NFTs as well as the intrinsic characteristics of the blockchain, the primary data source for NFT transactions. Using data consisting of the transaction history of eight highly valued NFT collections, a selection of such challenges is illustrated. These include price differentiation by token traits, the possible existence of lateral swaps and wash trades in the transaction history, and finally, severe price volatility. This paper provides an overall summary of the challenges associated with data analytics on NFT transaction data and lay a foundation for future research on the topic.

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