This paper examines the level of speculation associated with art non-fungible tokens (NFTs), comprehends the characteristics that confer value on them and designs a profitable trading strategy based on our findings. We analyze 860,067 art NFTs that have been deployed on the Ethereum blockchain and have been involved in 317,950 sales using machine learning methods to forecast the probability of sale, the trade frequency and the average price. We find that NFTs are highly speculative assets and that their price and recurrence of sale are heavily determined by the floor and the last sales prices, independent of any fundamental value.