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Correlations versus noise in the NFT market
Marcin Wątorek1, Paweł Szydło1, Jarosław Kwapień2
1Faculty of Computer Science and Telecommunications, Cracow University of Technology, ul. Warszawska 24, 31-155 Kraków, Poland.
Chaos (Woodbury, N.Y.)
|July 3, 2024
Summary
The non-fungible token (NFT) market shows weaker correlations than other financial markets, with global links driven by high-frequency trading. Capitalization variability is scale-free, while transaction numbers are more decentralized.
Area of Science:
- * Financial Markets Analysis
- * Blockchain Technology and Cryptocurrencies
- * Complex Systems Science
Background:
- * The non-fungible token (NFT) market is a novel trading innovation utilizing blockchain technology.
- * NFT market dynamics share similarities with the cryptocurrency market.
- * Understanding inter-collection dependencies is crucial for market analysis.
Purpose of the Study:
- * To analyze capitalization changes and transaction volumes in the NFT market on the Ethereum platform.
- * To examine inter-collection dependencies using multivariate statistical methods.
- * To compare market dynamics with other financial markets.
Main Methods:
- * Analysis of capitalization and transaction volumes for numerous Ethereum-based NFT collections.
- * Application of detrended fluctuation analysis and correlation matrix formalism.
- * Construction of correlation matrices using Pearson and detrended cross-correlation coefficients.
- * Minimal spanning tree analysis for capitalization variability and transaction numbers.
Main Results:
- * NFT market exhibits lower correlation strength compared to previously studied financial markets.
- * Eigenvalue spectra of the correlation matrix closely follow the Marchenko-Pastur distribution, with minor deviations.
- * Global correlations in the NFT market are primarily driven by higher-frequency fluctuations.
- * Minimal spanning trees for capitalization variability show scale-free properties.
- * Minimal spanning trees for transaction numbers indicate a more decentralized structure.
Conclusions:
- * The NFT market, while exhibiting some market-like characteristics, possesses unique correlation structures.
- * The Marchenko-Pastur distribution's applicability suggests a significant portion of random correlations.
- * High-frequency trading plays a key role in establishing global correlations within the NFT ecosystem.
- * Distinct structural properties exist for capitalization variability versus transaction dynamics.
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