NFT collector Pranksy criticizes Blur for "fake trading" being too serious! Trading volume related data cannot be referenced.

NFT renowned collector Pranksy recently revealed on social media that the phenomenon of fake transactions in Blur has become too serious, with less than 1/3 of trading users generating 3/4 of the total trading volume, rendering transaction volume-related data unusable. In this regard, what are some possible solutions to address this issue?

In the early days, one of the biggest arguments against NFTs was that most sales were 'wash trading'.

At that time, it was not a very accurate statement, but today it is.

22.3% of users made up 76.2% of global volume yesterday in only 29% of the total sales.

Despite being just… pic.twitter.com/6efoBAIEFf

— Pranksy 📦 (@pranksy) July 17, 2023

Pranksy Criticizes Blur for Fake Trading Phenomenon

Pranksy expressed on Twitter that in the early days of the NFT craze, one of the biggest reasons against NFTs was the prevalence of "fake trading" or wash trading.

Back then, based on data, this argument wasn't very accurate. However, Pranksy believes that the wash trading issue in the current NFT market is indeed severe, with Blur's airdrop mechanism being the main culprit.

Below are the transaction counts, unique users, and trading volume data for mainstream NFT markets, showing that Blur's data is in a rather unnatural state.

"22.5% of users account for only 29% of total transactions but drive 76.2% of global trading volume," Pranksy stated.

Although Blur's total transaction count is just over a quarter, its trading volume accounts for three-quarters. Pranksy mentioned that even laypeople can see from the chart that this phenomenon is due to large transactions mainly occurring on Blur, but the real reason is because some users keep conducting trades for the purpose of receiving Blur token airdrops.

"How long will it take for us to start deriving useful data from volume-based analysis?" Pranksy questioned.

Despite the apparent prevalence of fake trading on Blur, Pranksy pointed out that similar situations have occurred during the coin issuance on platforms like Rarible and Looksrare, so the blame cannot solely be placed on a specific platform and its incentive measures.

Too Many Fake Trades, How to Improve Information Accuracy?

In response to Pranksy's concerns about unreliable data, Twitter user @unlock_VALue shared a solution.

They suggested manually filtering out addresses that are clearly engaged in airdrop farming, such as the top 20 addresses on Blur's leaderboard. While this method may not completely eliminate fake trades, it can increase data accuracy to some extent.