New Study: NFT Prices Are Manipulated by Few with Wash Trades (Artificial Demand)

New Study: NFT Prices Are Manipulated by Few with Wash Trades (Artificial Demand)

NFT Prices

New Study: NFT Prices Are Manipulated By Few With Wash Trades (Artificial Demand). Photo by Mati Mango from Pexels

A new study has shown that Non-Fungible Tokens (NFT) prices are manipulated by few with wash trades, which artificially inflates the price of an asset by opening multiple accounts and trading with themselves.

This behavior is not only fraudulent, but the artificial price inflation also results in end users purchasing the NFT asset at a much higher price than its actual valuation.

Wash trading refers to when a trader buys and sells an asset with the intention of misleading and manipulating the market. This can include buying and selling something for tremendously inflated prices to distort its perceived value and demand.

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Cryptocurrency wash trading involves companies trading with each other to create the illusion of liquidity or manipulate the value of assets being traded.

Conceptually, NFT wash trading applies to the purchase or sale of non-fungible tokens not intended for acquiring something, like buying items to simulate artificial demand for a specific project.

The white-haired, green-eyed pixelated character known as a CryptoPunk 9998 sold for more than $500 million worth of Ether was just wash traded, according to Bloomberg.

The Ethereum blockchain shows the money from the NFT trade ended up right back where it started, raising questions of artificial demand.

“Someone bought this punk from themselves with borrowed money and repaid the loan in the same transaction. While the bid is technically briefly valid it can never be accepted. Larva would add filtering to avoid generating notifications for that kind of transaction in future,” tweeted Larva labs, which created the CryptoPunk.

Regardless of who is involved, wash trading is disastrous, whether for projects, traders, investors, or a global network of enthusiasts.

There are several things that can be used for early detection of wash trading like the use of group clustering, collusive cliques and nearest neighbor algorithms. Other methods that help are hidden Markov models, spectral clustering, and correlation statistics.

However, market manipulators are hard to catch and even though the tokens are non-fungible, they are still anonymous, making fraud detection difficult. When caught, wash traders keep coming up with new ways to wash trade and increase NFT prices.

Scour, a unique product created by BitsCrunch, an Al-powered analytics company that can actively remove washtrades from exchanges, reduced the wash traders by over 40 percent within two months.