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Correlations versus noise in the NFT market

Marcin Wątorek, Paweł Szydło, Jarosław Kwapień, Stanisław Drożdż

arXiv 23 Apr 2024 · Finance — Statistical Finance · publishedChaos An Interdisciplinary Journal of Nonlinear Science (2024) · 9 citations (OpenAlex)

arXiv:2404.15495 · PDF · DOI · OpenAlex · Extracted main text

Abstract

The non-fungible token (NFT) market emerges as a recent trading innovation leveraging blockchain technology, mirroring the dynamics of the cryptocurrency market. The current study is based on the capitalization changes and transaction volumes across a large number of token collections on the Ethereum platform. In order to deepen the understanding of the market dynamics, the collection-collection dependencies are examined by using the multivariate formalism of detrended correlation coefficient and correlation matrix. It appears that correlation strength is lower here than that observed in previously studied markets. Consequently, the eigenvalue spectra of the correlation matrix more closely follow the Marchenko-Pastur distribution, still, some departures indicating the existence of correlations remain. The comparison of results obtained from the correlation matrix built from the Pearson coefficients and, independently, from the detrended cross-correlation coefficients suggests that the global correlations in the NFT market arise from higher frequency fluctuations. Corresponding minimal spanning trees (MSTs) for capitalization variability exhibit a scale-free character while, for the number of transactions, they are somewhat more decentralized.

Citation extraction

100
references
132
in-text mentions
101
distinct cited
4
self-citations
8,522
main-text words

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Most heavily cited references

The works this paper leans on most, across its whole bibliography — not restricted to papers in our corpus. Ranked by composite intensity, which combines how often a work is mentioned, how many sections mention it, and how much of that falls in the main text rather than the appendix.

ReferenceIntensityMentionsSectionsMain text
1author author S. Drożdż, author J. Kwapień, \ and\ author M. Wątorek… (2023) ) NoStop self0.92843100%
2author author P. Szydło, author M. Wątorek, author J. Kwapień, \ and… (2024) ) NoStop self0.87452100%
3author author M. Watorek, author S. Drożdż, author J. Kwapień, autho… (2021) ) NoStop0.87452100%
4author author J. Kwapień\ and\ author S. Drożdż,\ title title Physic… (2012) 01.007 journal journal Physics Reports\ volume 515,\ pages 115–226 ( year 2012) NoStop0.69351100%
5CryptoSlam,\ @noop title Cryptomslam,\ howpublished https://www.cryp…0.64422100%
6author author V. A.\ Marcenko\ and\ author L. A.\ Pastur,\ title tit… (1967) ) NoStop0.64422100%
7author author K. Polovnikov, author V. Kazakov, \ and\ author S. Syn… (2019) 123075 journal journal Physica A\ volume 540,\ pages 123075 ( year 2020) NoStop0.64422100%
8author author A. Z.\ Górski, author S. Drożdż, \ and\ author J. Kwap… (2008) ) NoStop0.64422100%
9author author M. L.\ Mehta,\ @noop title Random Matrices\ ( publishe… (2004) ) NoStop0.64422100%
10author author M. Tumminello, author F. Lillo, \ and\ author R. N.\ M… (2010) ) NoStop0.64422100%

Showing the top 10 of 101 scored citations.

Cited by, within the corpus

arXiv econ.EM papers that cite this one, ranked by how heavily they lean on it.

Citing paperIntensityMentionsSections
12607.139160.40511