💡Solutions

MetaQuants' flagship products include NFT pricing and floor price oracles that serve as a backbone for protocols and platforms including our AI-driven NFT Terminal.

NFT Pricing Algorithm

MetaQuants provides users with an NFT Evaluation Solution which features three functionalities:

  • Wash Trading Filter - prevents deceitful sales from entering the model.

  • Point Estimate - a predicted price for the fair value of an asset.

  • Price Range - apart from a point estimate, a price range is computed, so different risk appetites can be accommodated.

Collection Floor Price

A Collection Floor Price API/Oracle is provided, a list of the supported projects can be found here. The solution encompasses:

  • Wash Trading Filter - prevents deceitful sales from entering the computation.

  • Anomaly Detection - a self-supervised machine learning model is employed to flag periods of anomalous activity.

  • Outlier Removal - sales over/under a predefined threshold are removed.

  • TWAP - time-weighted average of the floor price is returned by the API end-point.

MetaQuants offers a highly customizable framework through which the end user can define all variables for the Floor Price calculation. As an add-on, any collection can be included on-demand, but MetaQuants does not guarantee its legitimacy.

MQ NFT Terminal

We are developing an AI-powered terminal that is designed to address every facet of the NFT financialization narrative, and facilitate the generation of alpha for the end user.

  • General Metrics - NFT index, collection dominance, marketplaces volume, wash trading.

  • NFT News - aggregated information from leading NFT magazines and twitter profiles.

  • Collection Analytics - collection screener, market depth, floor price, top holders, sales.

  • Individual NFT Analysis - real-time appraisal, traits floor price, value drivers, cost basis.

  • NFT Finance Aggregator - NFT lending activities on P2Peer & P2Pool protocols.

  • Credit Risk Score - likelihood of liquidation for a loan on an address level.

  • Sentiment Analysis - correlation between events and floor data in a time-series manner.

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