Source: blockchain.news
Crypto asset manager CoinShares has launched a helpful Twitter bot for NFT investors.
On Thursday, CoinShares Announced the launch of a Twitter bot called ‘CoinSharesNFTAI’. Based on the functionality of the Twitter bot, CoinSharesNFTAI would help NFT investors predict a “fair price” for any NFT listed on Opensea.
The Twitter bot would help NFT investors on Twitter sift through the uncertainties in the NFT space and learn how much an NFT could be worth with a single tweet. To activate the bot, users would need to tweet a link to the NFT Opensea they would like to verify and then mention the bot (@CoinSharesNFTAI) in the tweet.
In the announcement, CoinShares stated that pricing NFTs could be a difficult task, especially since their value is volatile and millions of them are available on the market.
“Based on our quantitative and cryptographic experience, we came up with an experimental project to price NFTs, whether you already own them or not. This model is based on proven mathematical concepts to predict a fair price for any NFT.” currently listed on @opensea”. CoinShares said in the announcement.
The bot’s predictions are based on identified factors such as hype, rarity, profits, content, and products, as well as the transaction volume and history of an NFT project.
CEO Jean-Marie Mognetti said in a statement, noting: NFTs are one of the newly discovered digital assets in the crypto industry today, and it is essential that everyone feel comfortable buying and selling them. He added: “To this end, we made our proprietary NFT pricing algorithm publicly available via our CoinSharesNFTAI Twitter bot.”
CoinShares is a Europe-based digital asset investment and trading group, a pioneer in innovative financial products and services for the cryptocurrency industry.
In recent company news, CoinShares announced its intention to launch an algorithmic trading platform, HAL, for retail traders. The platform will provide retail traders with access to a variety of algorithmic trading strategies for $20 per month.
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