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Passion for pixels: who sets the prices in the NFT digital art market?

Author

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  • Kaur Nagpal, Guneet
  • Renneboog, Luc

Abstract

Soaring prices of NFT digital art have sparked growing scholarly and public interest, raising questions about whether valuations reflect systematic fundamentals or speculative excess. This paper investigates what explains price formation in the NFT market using transactions from the CryptoPunks collectible market involving 3,230 unique traders. Leveraging the full observability of blockchain data, we estimate hedonic pricing models with progressively richer fixed-effect structures, culminating in a within-seller specification that identifies price effects from variation in individual seller behavior over time. Three findings emerge. First, the seller side carries the bulk of the identified within-trader pricing variation in a way that cross-sectional models conceal: seller experience is negatively associated with prices across sellers but positively associated within a seller over time, reflecting a learning effect; seller trading frequency reverses from positive to steeply negative once within-seller variation is isolated, corresponding to an 82.2% price reduction. Buyer characteristics play a comparatively limited role. Second, statistical rarity is priced uniformly across participants, while visual rarity, a pixel-level measure of aesthetic distinctiveness, is trader-mediated. Its premium attenuates when trader fixed effects absorb persistent valuation tendencies, revealing that visual effects in cross-sectional models partly reflect who trades rather than what is traded. Third, past comparable peak prices and recent trading activity anchor current transaction prices, but these effects attenuate substantially once trader composition is controlled for, indicating that market-condition sensitivity in standard hedonic models partly proxies for time-varying participation. Together, the findings highlight that trader composition is not merely a control variable in NFT valuation models; it materially affects the estimated pricing relationships.

Suggested Citation

  • Kaur Nagpal, Guneet & Renneboog, Luc, 2026. "Passion for pixels: who sets the prices in the NFT digital art market?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 111(C).
    • Handle: RePEc:eee:intfin:v:111:y:2026:i:c:s1042443126000892
    DOI: 10.1016/j.intfin.2026.102373
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    JEL classification:

    • Z11 - Other Special Topics - - Cultural Economics - - - Economics of the Arts and Literature
    • G12 - Financial Economics - - General Financial Markets - - - Asset Pricing; Trading Volume; Bond Interest Rates
    • G14 - Financial Economics - - General Financial Markets - - - Information and Market Efficiency; Event Studies; Insider Trading
    • G41 - Financial Economics - - Behavioral Finance - - - Role and Effects of Psychological, Emotional, Social, and Cognitive Factors on Decision Making in Financial Markets
    • M31 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Marketing and Advertising - - - Marketing

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