Heterogeneous rarity patterns drive price dynamics in NFT collections

Fuente: arXiv
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Autori principali: Mekacher, Amin, Bracci, Alberto, Nadini, Matthieu, Martino, Mauro, Alessandretti, Laura, Aiello, Luca Maria, Baronchelli, Andrea
Natura: Preprint
Pubblicazione: 2022
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author Mekacher, Amin
Bracci, Alberto
Nadini, Matthieu
Martino, Mauro
Alessandretti, Laura
Aiello, Luca Maria
Baronchelli, Andrea
author_facet Mekacher, Amin
Bracci, Alberto
Nadini, Matthieu
Martino, Mauro
Alessandretti, Laura
Aiello, Luca Maria
Baronchelli, Andrea
contents We quantify Non Fungible Token (NFT) rarity and investigate how it impacts market behaviour by analysing a dataset of 3.7M transactions collected between January 2018 and June 2022, involving 1.4M NFTs distributed across 410 collections. First, we consider the rarity of an NFT based on the set of human-readable attributes it possesses and show that most collections present heterogeneous rarity patterns, with few rare NFTs and a large number of more common ones. Then, we analyze market performance and show that, on average, rarer NFTs: (i) sell for higher prices, (ii) are traded less frequently, (iii) guarantee higher returns on investment (ROIs), and (iv) are less risky, i.e., less prone to yield negative returns. We anticipate that these findings will be of interest to researchers as well as NFT creators, collectors, and traders.
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id arxiv_https___arxiv_org_abs_2204_10243
institution arXiv
publishDate 2022
record_format arxiv
spellingShingle Heterogeneous rarity patterns drive price dynamics in NFT collections
Mekacher, Amin
Bracci, Alberto
Nadini, Matthieu
Martino, Mauro
Alessandretti, Laura
Aiello, Luca Maria
Baronchelli, Andrea
Statistical Finance
Computers and Society
Physics and Society
We quantify Non Fungible Token (NFT) rarity and investigate how it impacts market behaviour by analysing a dataset of 3.7M transactions collected between January 2018 and June 2022, involving 1.4M NFTs distributed across 410 collections. First, we consider the rarity of an NFT based on the set of human-readable attributes it possesses and show that most collections present heterogeneous rarity patterns, with few rare NFTs and a large number of more common ones. Then, we analyze market performance and show that, on average, rarer NFTs: (i) sell for higher prices, (ii) are traded less frequently, (iii) guarantee higher returns on investment (ROIs), and (iv) are less risky, i.e., less prone to yield negative returns. We anticipate that these findings will be of interest to researchers as well as NFT creators, collectors, and traders.
title Heterogeneous rarity patterns drive price dynamics in NFT collections
topic Statistical Finance
Computers and Society
Physics and Society
url https://arxiv.org/abs/2204.10243