Exploring the Liquidity of NFT Collections

Abstract

This paper provides the first analysis of non-fungible token (NFT) collection liquidity by applying a suite of widely used proxies that capture different dimensions of liquidity. Using transaction-level data from the OpenSea marketplace, manipulative trades are flagged and two novel methodologies for calculating liquidity are applied before performing a family of regressions to investigate its dynamics. I find that collection-specific attributes directly account for both NFT-specific liquidity idiosyncrasies and the impacts of manipulative trading. Following robustness tests, I identify that this collection-level power only exists in bull markets, similarly to real estate ZIP-code groupings. Finally, the estimated models reveal a non-linear liquidity pattern across a collection’s lifetime, with successful collections dipping in liquidity before recovering quickly. This paper deepens our understanding of how liquidity operates at the collection level in NFTs, offering findings for liquidity researchers in non-fungible asset markets.