Working Paper
Blockchain technologies have enabled the creation of decentralized applications which let users own and transact scarce digital assets called nonfungible tokens or NFTs. Although still in its infancy, the industry has generated over $2.5bn in transaction volume and attracted interest from organizations such as the NBA, several football (soccer) clubs, major brands, and gaming companies to create platforms for trading digital collectibles. A major question faced by NFT platforms is how to help participants value the digital items.
The authors introduce a novel dataset and study how traditional approaches to valuation may exhibit significant biases in this market. They find that while buyers value NFTs much like we would expect them to value physical collectibles, sellers have a tendency to price sub-optimally, which causes traditional hedonic regression approaches to generate inaccurate valuations.
The authors develop a valuation approach based on a structural model of the selling mechanism used in a popular NFT market to highlight these biases and develop a proof-of-concept decision support tool to help participants make more informed decisions.
