数字加密货币
计量经济学
价值(数学)
计算机科学
经济
大数据
微观经济学
机器学习
数据挖掘
计算机安全
作者
Florian Horky,Carolina Rachel,Jarko Fidrmuc
标识
DOI:10.1016/j.frl.2022.103007
摘要
While the traditional art market stagnates, the digital art market is booming partially due to its connection with non-fungible tokens, which allow any unique goods to be mapped in a digital environment. Using unique individual data from the online art NFTs marketplace SuperRare, we combine econometric tools with recent machine learning approaches. This approach allows us to define explanatory variables out of the NFTs descriptions for our Hedonic pricing approach. Using these variables, we are able to show that our Hedonic pricing models exhibit relevant informational value for NFTs prices. Moreover, we show that NFTs cannot be viewed as a simple derivative of cryptocurrencies.
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