The non-fungible token (NFT) market has been surprising us with not only new creative digital arts but also sky-rocketing prices. Everyone wants to find the next Crypto Punks, Bored Ape Yacht Club or Azuki before the price goes out of reach for most of us. Although the price of any NFT is difficult to predict given the variety of traits and rarity, it is possible to predict the floor price in the very near future using time-series statistical models.
This article will show you how to acquire historical NFT data to build a floor price prediction model for Bored Ape Yacht Club (BAYC) collection in Python. The model can be also used to predict other NFT collections by simply changing the NFT contract address.
This is the first article of its kind and the article is minted as NFTs. Holders of the NFT will gain access to my next article - NFT token price prediction model.
Note: This model was built in January 2022 using the historic data downloaded from back then. The USD equivalent price might have changed since then due to ETH price movements. This article only shows a methodology for NFT floor price prediction. It is by no means a real-time live prediction of the NFT. The data used in this article has not been updated since January and might contain inaccurate prices. Readers should not use the price predicted in this article for investment purpose.