Abstract
An understanding of what influences the NFT market is valuable in such a speculative space, and predictors of directional shifts in NFT sales are beneficial to NFT users and investors alike. For these reasons, research was undertaken to determine if metrics relating to consumer behavior could predict NFT market sales. To begin, a Buyer Activity Metric and a Buyer Valuation Metric were calculated using open-access data regarding the NFT market. A three-variable vector autoregression (VAR) model was then constructed using these metrics and NFT sales data. Changes in monthly NFT sales were found to be Granger-caused by changes in both the Buyer Activity Metric and the Buyer Valuation Metric. Changes in each metric were determined to precede changes in NFT sales by up to four months. The associations were also determined to be unidirectional, indicating a clear cause-and-effect style relationship. Questions about these predictive abilities were then theoretically explored.
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