Source: @AustenSfy
Wash trading has been prevalent in the NFT market since 2021, posing a significant risk to retail and institutional investors.
But now, investors and traders can identify projects that engage in wash trading and take proactive measures to avoid getting defrauded. There are two common ways to do this.
The first involves using algorithms to discriminate wash trading based on features like suspicious addresses, which can be identified by filtering out the number of unique transactions and the frequency of transactions.
The other way involves identifying circular trading patterns — an important feature of NFT wash trading. Circular trading involves transferring NFTs between specific addresses to inflate prices. Therefore, it is necessary to track all historical transactions in an NFT-specific address to trace this structure.
Detecting NFT wash trading is essential for all investors, but it requires a rigorous model and a large amount of historical data for training.
To address these challenges, the Footprint Batch Download solution streamlines the data acquisition process, enabling access to all levels of data, including raw and structured data. This makes it easy to process the data according to analysts’ rules and criteria, which is crucial for the accurate detection of NFT wash trading and the protection of investments. By leveraging this data and following a scientific modeling process, investors can make informed decisions and safeguard their assets.
Make Built-In Fraud Detection Your Product’s Competitive Advantage
In addition to detecting wash trading, Batch Download can also be used to build quantitative trading models with full historical data, conduct research for investment institutions, and aid in anti-money laundering efforts by analyzing on-chain behavior.
Investors can access comprehensive data from 24 chains, including 700k NFT collections, 2000 games, and 17 marketplaces. Users can process the data according to their own criteria on a platform ten times faster than other measures and which supports multiple clouds and regions.
Contact Footprint at [email protected]