DAI digital art index: a robust price index for heterogeneous digital assets

Abstract The market of non-fungible tokens (NFTs), driven by blockchain and smart contracts, provides both artists and art collectors an unprecedented marketplace with more security, flexibility, publicity, and freedom to monetize. Yet, the emergence of such a market has been considered to be packed with speculation and economic uncertainty, given the limited understanding towards this market. To provide a precise depiction of the NFT art market and gauge market volatility, we construct the Digital Art Index, a novel price index using hedonic regression on the top 10 liquid NFT art collections (as of 2023). Addressing artwork price inequality, which often disrupts the price discovery process, this paper introduces two innovative alternative methods: Huberization and score-based filtering. These methods effectively mitigate the influence of outliers, particularly in an emerging market with limited accessible observations. In conclusion, the NFT art market presents significant opportunities for large gains, which are often favoured by risk-takers, but also carries the potential for significant losses. Its pricing is necessarily determined by institutional creators and platforms, meaning that solo artists may not benefit significantly in the current market environment.

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Publication Details

Journal
Journal of the Royal Statistical Society Series A (Statistics in Society)
Published
2026-01-15
DOI
https://doi.org/10.1093/jrsssa/qnag008
Primary Topic
Art History and Market Analysis
Type
article
Field-Weighted Citation Impact
0.00
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article

DAI digital art index: a robust price index for heterogeneous digital assets

Min-Bin Lin, Bingling Wang, Wolfgang Karl Härdle, Christian M Hafner et al.
Journal of the Royal Statistical Society Series A (Statistics in Society)
Art History and Market Analysis
article

DAI digital art index: a robust price index for heterogeneous digital assets

Min-Bin Lin, Bingling Wang, Wolfgang Karl Härdle, Christian M Hafner, Fabian Y R P Bocart
article en

Abstract

Abstract The market of non-fungible tokens (NFTs), driven by blockchain and smart contracts, provides both artists and art collectors an unprecedented marketplace with more security, flexibility, publicity, and freedom to monetize. Yet, the emergence of such a market has been considered to be packed with speculation and economic uncertainty, given the limited understanding towards this market. To provide a precise depiction of the NFT art market and gauge market volatility, we construct the Digital Art Index, a novel price index using hedonic regression on the top 10 liquid NFT art collections (as of 2023). Addressing artwork price inequality, which often disrupts the price discovery process, this paper introduces two innovative alternative methods: Huberization and score-based filtering. These methods effectively mitigate the influence of outliers, particularly in an emerging market with limited accessible observations. In conclusion, the NFT art market presents significant opportunities for large gains, which are often favoured by risk-takers, but also carries the potential for significant losses. Its pricing is necessarily determined by institutional creators and platforms, meaning that solo artists may not benefit significantly in the current market environment.

Journal of the Royal Statistical Society Series A (Statistics in Society)
National Yang Ming Chiao Tung University (TW), Humboldt-Universität zu Berlin (DE), WNET (United States) (US), Bucharest University of Economic Studies (RO), UCLouvain (BE)
Openalex Percentile: Top 66%
Art History and Market Analysis
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