The non-fungible token (NFT) market emerges as a recent trading innovation leveraging blockchain technology, mirroring the dynamics of the cryptocurrency market. To deepen the understanding of the dynamics of this market, in the current study, based on the capitalization changes and transaction volumes across a large number of token collections on the Ethereum platform, the degree of correlation in this market is 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.

翻译：非同质化代币（NFT）市场作为利用区块链技术的新兴交易创新，反映了加密货币市场的动态特征。为深化对该市场动态的理解，本研究基于以太坊平台上大量代币集合的市值变化与交易量数据，通过使用去趋势相关系数和相关矩阵的多元形式，检验了该市场的相关程度。结果表明，相较于此前研究的其他市场，NFT市场的相关性强度较低。因此，相关矩阵的特征值谱更贴近马尔琴科-帕斯图尔分布，但仍存在部分偏离，表明相关性依旧存在。基于皮尔逊系数构建的相关矩阵与基于去趋势交叉相关系数独立构建的相关矩阵的结果对比表明，NFT市场的全局相关性源自更高频的波动。对应的市值变异性最小生成树（MSTs）呈现无标度特征，而交易量的MSTs则表现出更明显的去中心化特征。