Now that NFTs have existed for a number of years and we are in the middle of a downward price trend, what better time to sit down and analyse how NFT floor prices have behaved over the years? In this article we will analyse the price floor data for seven different NFT projects of different ages, identify potential patterns and draw some main conclusions.
First, our methodology. Aggregated historical NFT price floor data is actually very difficult to find; it’s even harder to download. In light of this, we had to develop our own means of capturing price floor data for the projects we wanted to analyse. We chose to use the Covalent API to download data directly from the blockchain, which is where all data used in this analysis was generated from. This price floor data was then stripped of dates and indexed to 1, which means that all of the initial values are equal to one, and the X axis is simply days since price floor data became available (not necessarily mint price). In this way, the indexed price floor represents the multiplier that a theoretical person would have received if they had purchased the NFT at the floor price on the first day that data became available.
Furthermore, different NFT projects were included for a variety of reasons. CryptoPunks, CryptoKitties and Ethermon were selected because of their age, so that multiple years of data could be analysed. There are only so many ‘ancient’ NFTs out there, so the others — BAYC, Azuki, AutoGlyphs and MoonCats — were selected due to name recognition and popularity.
This aggregated and indexed price data can be seen below:
There are a couple of main takeaways from this data. Primarily: not a single NFT that was analysed had an indexed price below 1 at the end of the time series, meaning all holders of these projects would be above water — in USD terms — on their holdings. The second main takeaway of this data is that NFTs experience tremendous peak-to-trough volatility. This could be attributed to the various hype cycles that different projects have experienced over time. This volatility means that NFT top buyers can experience massive drawdowns. Finally, NFT price floors move for different reasons than cryptocurrencies at large and their movements are even less predictable.
In conclusion, we hope that there are efforts being made to better aggregate NFT price floor data. It’s possible that there are other metrics beyond just the floor price that can give researchers more insight into why certain NFTs move the way that they do. However, in the meantime, there is tremendous opportunity for those who are willing to roll up their sleeves and look where others have not.
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