Numeraire ( $NMR ) is a unique cryptocurrency associated with Numerai, a San Francisco-based hedge fund that leverages the power of artificial intelligence (AI) and machine learning for investment decisions. Launched in 2017, NMR is considered the first cryptocurrency created and released by a hedge fund.

What is NMR?

NMR is an ERC-20 token built on the Ethereum blockchain. ERC-20 tokens offer flexibility and are widely used in various decentralized applications (dApps). NMR plays a crucial role within the Numerai ecosystem, serving several purposes:

  • Incentivizing data scientists: Numerai frequently conducts tournaments where data scientists compete by submitting machine learning models that predict financial market outcomes. Top performers are rewarded with NMR tokens.

  • Staking: NMR holders can stake their tokens to participate in the Numerai protocol and earn rewards based on the performance of the collective intelligence gathered from the submitted models.

  • Governance: NMR token holders have voting rights on proposals that impact the Numerai platform's future development.

What makes NMR unique?

Several aspects distinguish NMR from other cryptocurrencies:

  • Hedge fund connection: Unlike most cryptocurrencies, NMR is directly tied to a real-world hedge fund, offering a potential link to traditional financial markets.

  • Focus on AI and machine learning: NMR is deeply rooted in the world of AI and machine learning, promoting innovation in these fields within the financial sector.

  • Stake-based rewards: The ability to stake NMR tokens and earn rewards based on the overall platform's performance adds another layer of utility to the token.

    Tokenomics & Distribution

    The maximum supply of NMR is 11,000,000 tokens reduced from an initial 21 Million.  Numerai distributed 1 Million tokens to active platform users and 3 Million tokens are locked until 2028 and will be released as a reward incentive for tournament participants. 

    NMR tokens are burned weekly, as tournament participants who venture losing models and predictions lose their stake in the competition.



    Review Score: 8.4



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