How wrong are non-fungible tokens (NFT) trading volumes on Ethereum?

A year 2022 wrong with the numbers

Could Ethereum (ETH) blockchain non-fungible token (NFT) volumes be misleading? According to Dune, a website specializing in data analysis, 58% of NFT exchanges in 2022 would be fake transactions from “ wash trade ».

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Wash trading, which could be translated as “volume manipulation”, is a technique to corrupt transaction volumes by artificially inflating the number of trades in a particular asset class.

Although these market manipulations are illegal in many countries, they are still very present in the world of NFTs: the washing rate reached 80% in January 2022 :

Figure 1 – NFT wash trade velocity between April 2018 and December 2022

While artificial trading volumes accounted for only a minority of transactions until the end of 2021, we see an explosion of these fake exchanges throughout 2022.

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Reasons for laundry trade

With the explosion in popularity of non-fungible tokens, The NFT fundraising industry has become increasingly competitive. To separate the wheat from the chaff, trading volume serves as an indicator of a collection’s health and popularity.

As a result, various NFT projects and marketplaces are trying to increase their trading volume through various mechanisms to gain market share. The most used method is the incentive of the distribution of tokens.

For example, the LooksRare marketplace, which specializes in NFTs, uses its cryptocurrency (LOOKS) to encourage investors to use its platform. Besides, it rewards its users with LOOKS tokens for their buying and selling on its marketplace.

However, wash trading occurs when a user moves one of his NFTs between two wallets that he himself controls. By using maximum ETH (cryptocurrency of the Ethereum network) in his fake transaction, the user secures a significant reward in LOOKS tokens while keeping his NFT. Thus, the platform’s trading volumes are changed by fake transactions..

Cases of wash trading also take place when certain projects want to position themselves in the general ranking of NFT collections. By artificially creating high trading volumes, they attract the curiosity of certain investors who, afraid of missing an opportunity, will acquire these NFTs at a price far from their real value, all for the benefit of the project that manipulated its numbers.

In this way, hundreds of millions of dollars artificially flow through the NFT sector. And despite the reduction in laundry trade in 2022, this phenomenon still accounts for 25% of exchanges completed in December 2022 :

Figure 2 – Weekly NFT trading volumes between December 2020 and December 2022

In the chart above, we see that the highest weekly volume rate was around $5 billion in January 2022. However, if you subtract artificial trading volumes from the calculation, August 2021 will be the month with the most activity, with around $1.8 billion in weekly volume.

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Are some marketplaces spared?

Since laundry trading is mainly motivated by the financial reward provided by certain platforms, those operating without a token are spared this phenomenon.

While the volumes of the LooksRare and X2Y2 marketplaces distribute tokens to their users, their wash-trade speed, respectively, is 98% and 86% compared to all their volumes.

In contrast, the largest NFT marketplace, OpenSea, does not award rewards to its users: its wash trade rate is then around 2.5% of its volumes.

To get these numbers, Dune’s report is based on 4 factors to distinguish between organic volumes and artificially inflated volumes. According to him, a transaction is considered laundering if:

• the buyer’s portfolio is the same as the seller’s;
• NFT goes back and forth between two different wallets;
• a portfolio has bought or sold 3 or more times the same NFT;
• both buyer and seller were provided with ETH by the same wallet.

Currently, the best method to limit laundering appears to be removing trading rewards on platforms like LooksRare and X2Y2. But in the future we can hope for a legal framework to limit this phenomenon.

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Source: Figures 1 and 2 – Dune