In May, NFTs from the Milady collection boomed on OpenSea thanks to Elon Musk.
In fact, Musk posted a tweet depicting one of the images from the Milady Maker collection.
Although it was just a meme built on one of those images, and had nothing to do with that collection, the collection generated a total trading volume of more than 45,000 ETH (more than $26 million), whereas until the previous month it had never exceeded 1,500 ETH.
In reality, the NFT collection was already booming in the weeks leading up to Elon Musk’s meme, even though it had already been on the crypto markets for almost two years, and Musk merely caused it to jump even higher.
Since then, however, this mini-bubble has deflated.
Summary
The mini-bubble on the Milady NFT collection caused by Elon Musk
To analyze how it inflated, and how this mini-bubble has since burst, we need to engage in two different reasonings, namely one on prices and one on volumes.
At the end of April, the average trading price of the nearly 10,000 NFTs in this collection was about 2.7 ETH, already up from 1.9 ETH at the beginning of the month.
By the beginning of May the average price had already risen to 3.5 ETH, but with the perhaps unintentional push by Elon Musk it reached close to 5 ETH.
This is an increase of 163% in one month.
By the end of May, the average price had already returned to 3.5 ETH, and in June it dropped to 2.8. It is worth noting that this price is in line with the price at the end of April, i.e. 40% higher than at the beginning of April.
It later recovered above 3 ETH, but only to fall back again near 2.7.
So from a price perspective the mini-bubble was rapid and significant, but its burst did not wipe out all the gains. In light of this, it is possible to say that April’s gains were probably not due to the mini-bubble, while only those of the first half of May were.
Elon Musk manipulates trading volumes on the Milady NFTs
The most striking numbers are those relating to volumes.
In April, there had been no significant increase in weekly volumes, always ranging between 2,000 and 3,000 ETH.
The real boom occurred in May. During the first week they had already risen to almost 4,500, while after Musk’s tweet they sprang to over 13,000 ETH.
The increase was 420%, making it clear that this was a mini-bubble.
Moreover, when this bubble burst, weekly volumes literally collapsed, first falling below 2,000 ETH and then even below 1,000.
In other words, current volumes are less than half of what they were pre-bubble.
The comparison with the price trend is interesting, because while the volumes inflated a lot and then deflated to the point of collapsing, the average price inflated less, and then did not even fall to pre-bubble levels.
Moreover, the fact that 70% of the owners of the NFTs in this collection turn out to own only one suggests that there has been a real phase of large distribution, perhaps not only thanks to Elon Musk.
Comparison with Bored Ape Yacht Club
If one compares this data with that of the currently most successful collection on OpenSea, namely Bored Ape Yacht Club (BAYC), it turns out that it is not that uncommon for trading volumes on OpenSea to change so much and so quickly, even apart from prices.
Indeed, the average selling price of BAYC’s 10,000 NFTs on OpenSea has dropped from 55 ETH in early April to the current 34 ETH, or a loss in two months of about 38%.
Volumes, on the other hand, first fell, then surged, and then fell again.
At the beginning of April the weekly volume was about 21,000 ETH, which is much higher than that of Milady Maker.
In May it had dropped to below 6,000 ETH, but in June it surged again to over 40,000 ETH.
In late June and early July, however, they returned first below 20,000 ETH and then also below 10,000.
Even with regard to this collection, the overwhelming majority of holders (81%) have only one NFT, so the comparison with Milady Maker holds.
Therefore, this story teaches us that on OpenSea the trading volumes of specific collections can change a lot and also very quickly, while instead the prices are paradoxically somewhat less variable.
They still vary a great deal, but definitely less than the oh-so-high variability of trading volumes.