Non-fungible tokens (NFT) have recently emerged as a novel blockchain hosted financial asset class that has attracted major transaction volumes. Investment decisions rely on data and adequate preprocessing and application of analytics to them. Both owing to the non-fungible nature of the tokens and to a blockchain being the primary data source, NFT transaction data pose several challenges not commonly encountered in traditional financial data. Using data that consist of the transaction history of eight highly valued NFT collections, a selection of such challenges is illustrated. These are: price differentiation by token traits, the possible existence of lateral swaps and wash trades in the transaction history and finally, severe volatility. While this paper merely scratches the surface of how data analytics can be applied in this context, the data and challenges laid out here may present opportunities for future research on the topic.
翻译:投资决定依赖于数据和适当的预处理以及分析工具的应用。由于这些工具的不可互换性质,加上一个链条是主要数据来源,因此,NFT交易数据构成传统金融数据中通常没有遇到的若干挑战。利用8个高价值NFT收藏的交易历史数据,可以对此类挑战进行选择。这些挑战包括:按象征性特征分列的价格差异、交易历史中可能存在的横向互换和洗涤交易,以及最后是严重的波动性。虽然本文仅仅触及了数据分析方法如何应用于这一背景下的表面,但此处列出的数据和挑战可能会为今后关于这一专题的研究提供机会。