NMR
The Numeraire token (NMR) is an ERC- 20 based token that powers Numerai, a hedge fund that crowd-sources artificial intelligence to invest in the world’s stock market. [1][2][3]
Overview
NMR is a cryptocurrency token used to pay for services on the Numeraire network and also to power all Numerai applications. Users stake NMR tokens on various prediction models and are rewarded based on their performance. It is built on Ethereum following the ERC-20 standard for tokens. [3][6]
In 2017, the NMR token launched on Ethereum mainnet without an Initial Coin Offering (ICO), rather Numerai issued one million NMR tokens to 12,000 data scientists based on past contributions in Numerai Tournaments. [1][3]
NMR can be used as an Incentivization Tool for AI model development in financial predictions, for Market Strategy, and Community Engagement — building a network of skilled data scientists. [7]
Numerai
Numerai is an AI-run, crowdsourced hedge fund based in San Francisco. It was founded by South African technologist Richard Craib in October 2015. The trades of Numerai are determined by an AI, which is fueled by a network of thousands of anonymous data scientists. [3]
Numerai organizes a guessing game where people, often data scientists, create models to predict how money-related things like stocks will change. These models compete with each other. Those who make the best predictions win prizes. They can bet Numeraire Tokens(NMR) to win more if they are confident in their predictions. [4]
Numerai won a 2016 Forbes Fintech 50 award. In March 2017, Numerai designed and released a new ‘API’ that allows people around the world to create and submit predictions from machine language models to power hedge funds. [3][5]
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. [7]
NMR tokens are burned weekly, as tournament participants who venture losing models and predictions lose their stake in the competition. [1][2]
