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NMR (Numeraire) - When Crypto, AI & Stock Markets Merge

by Kamil S

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A Hedge Fund for Ethereum Based Equity Trading 

NMR (Numeraire) is one of the more innovative assets we have listed in the 15 Weeks of Summer campaign. Alongside COVAL, for instance, NMR offers unique investment opportunities that merge financial dimensions and offer great leveraging opportunities. The Numeraire token is powered by the Numerai foundation – a San Francisco hedge fund that uses artificial intelligence to make predictions in the stock market and trade equities on the Ethereum blockchain in the form of NMR staking. NMR was listed on the Coinemtro exchange last week, alongside other assets such as MKRCOMPCELO and LRC.

In this blog, we will learn all about it.

NMR – The Era of Democratized Trading

Essentially, Numerai is a quant hedge fund built on thousands of crowdsourced machine learning models. The team uses a dataset consisting of standard financial market data from a universe of roughly 5,000 global equities. Data scientists use information from several providers covering a 10-20 year time period.

The foundation is staying close to its initial vision – to offer readily available data as a core component in crowdsourcing solutions to significant data science problems.

Numerai has two layers of investment of which you can take advantage:

  • Signals – a platform where users pool together stock market strategies and predictions. Users can choose to participate in various investment plans by staking NMR on the network.
  • Tournament – a weekly contest where users can submit AI-augmented trading algorithms and bet on the most favorable outcome. Up until this point, approximately 4,903 staked models have been submitted for the most recent data tournament, with a staked amount totaling $20 million.

Numerai’s hedge fund growth in recent years can be largely attributed to its ability to mitigate the impact of traditional risk factors. After several years of operating with large quantities of data, the foundation has managed to build a portfolio where most of the returns come from purely accurate stock selection, rather than the more traditional factors like size and value. The strategy has worked well for Numerai, allowing the foundation to perform well during periods of market volatility as we experienced in 2020.

The Numerai Foundation

The Numerai network is a collective of thousands of coders who leverage artificial intelligence and machine learning to predict the stock market. The foundation has also gathered some of the best data scientists using high-quality stock market information. The result is a next-generation hedge fund which is outperforming market neutral indexes and traditional quant funds.

The Numerai Foundation was established in 2015 by Richard Craib, a graduate of pure mathematics from Cornell University. This is not Richard’s first approach to financial data regularization. Years back, Richard built Prudential (M&G) – a global equity fund powered by machine learning.

The operational day-to-day functions are being overseen by Dan Spier – COO, previously Head of Portfolio Trading at Aperio Group (now Blackrock).

Numerai’s investment group was led by Howard Morgan of Renaissance Technologies, and among its investors you will find Paul Tudor Jones and Naval Ravikant.

NMR Token – Now Trading on Coinmetro Exchange

NMR is the first token introduced by a hedge fund. Its utility is to stake on models in the Numerai tournament. Based on a scoring metric, users receive a fractional payout on their stake for performant models, with a portion of the stake being burned for poorly performing models. Stake payouts and burns occur on a blockchain with no direct financial benefit accruing to Numerai.

While staking is not required, only staked submissions are incorporated into Numerai’s Meta Model which ultimately manages the trading and the portfolios in the Numerai hedge fund. Data scientists whose predictive models perform well in the Numerai tournament are awarded NMR tokens – making the asset more valuable as more people enter the competition.

The data models for the tournament allow Numerai to actively participate in stock market trading based on the results revealed by participating projects. This innovative approach to stock trading makes Numerai one of the few hedge funds to rely significantly on AI-generated data predictions.

NMR token had an initial supply cap of 21 million tokens, but the maximum supply was cut to 11 million in 2019. An interesting fact is that 3 million NMR tokens remain locked until 2028 and will be released to tournament participants as rewards. As opposed to going through a traditional ICO (initial coin offering), Numerai instead decided to reward the participation of the community, distributing 1 million tokens to the 12,000 platform users with the highest activity.

Another important mechanism is that NMR tokens are burned every week, as tournament participants who propose unsuccessful models and predictions lose their stake in the competition.

Keeping It Coinmetro

NMR completes the solid palette of five assets that were listed last week on the Coinmetro exchange, solidifying our season-long 15 Weeks of Summer campaign. Check out last week’s BLOG to learn more about each token and understand how you can integrate them into your future investment.

What steps are you taking during this bear market so that you adequately strengthen your portfolio for the next year? Regardless of market conditions, at Coinmetro, innovation never stops. By listening to our community, we try to give back by offering prominent assets and continually improving our services and products.

You will find a lot of meaningful conversations on Coinmetro’s Discord and Telegram channels, meant to make us all better humans and better investors. As much as we like to talk, we also love to listen to our ever-growing community of Coinmetroids and learn something new every day. Join the conversation and stay close to Coinmetro for the long run! To experience our platform today, sign-up now with one of the fastest-growing crypto exchanges.

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