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Pricing Dynamics and Herding Behavior of NFTs
Fridgen, Gilbert; Kräussl, Roman; Papageorgiou, Orestis et al.
2023
 

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Keywords :
Non-fungible tokens (NFTs); Machine Learning; Blockchain
Abstract :
[en] Non-fungible tokens (NFTs) took the digital art space by storm in 2021, generating massive amounts of volume and attracting a large number of users to a previously obscure part of blockchain technology. Still, very little is known about the determinants that contribute to NFT pricing and the market dynamics. This paper attempts to evaluate these factors analyzing 860,067 art NFTs that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales. We introduce a first-of-its-kind ranking system for NFT artists, adding a novel dimension to our analysis. Our results suggest that market liquidity and intrinsic value strongly predict average price of NFTs. Contrarily, social media activity surprisingly shows a negative association with NFT prices. We also uncover the dominance of a small group of artists, demonstrating the pronounced 'superstar effect' and herding behavior within the NFT market. This market dynamic, however, shows signs of shifting towards independent decision-making during extreme market volatility.
Disciplines :
Finance
Author, co-author :
Fridgen, Gilbert  ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Kräussl, Roman ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
Papageorgiou, Orestis ;  University of Luxembourg > Interdisciplinary Centre for Security, Reliability and Trust (SNT) > FINATRAX
Tugnetti, Alessandro  ;  University of Luxembourg > Faculty of Law, Economics and Finance (FDEF) > Department of Finance (DF)
Language :
English
Title :
Pricing Dynamics and Herding Behavior of NFTs
Publication date :
03 February 2023
Focus Area :
Finance
Available on ORBilu :
since 09 March 2023

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