models and counting.

A New Abstraction

The stock market is inefficient with respect to new developments in machine learning because only a small fraction of the world's data scientists have access to its data.

Numerai data scientists aren't traders or quants, and they don't want to be. They are experts in statistics, machine learning and artificial intelligence, working as geneticists, physicists, students and professors.

They have specialized in building predictive models on data—any data. So we give them stock market data in its purest, most abstract form and let their machine learning algorithms discover its predictive structure.

Learn more about our thesis in Encrypted Data For Efficient Markets

Assembling a Super Intelligence

Numerai is not a search for the ‘best’ model; it is a platform to synthesize many different, uncorrelated models with many different characteristics.

Data scientists compete on the leaderboard but models are ranked and rewarded based on their contribution to the meta model.

Learn more in Super Intelligence for the Stock Market

August 2016

A Proof of Intelligence

Nearly all of the most valuable companies and infrastructures throughout history were valuable through their strong network effects.

But no hedge fund has ever harnessed network effects. Negative network effects are too pervasive in finance, and they are the reason that there is no one hedge fund monopoly managing all the money in the world.

To make Numerai the first hedge fund with positive network effects, we issued a million crypto-tokens to our twelve thousand data scientists to incentivize coordination.

Learn more in A New Cryptocurrency For Coordinating Artificial Intelligence

Read our white paper

February 2017

A New Approach

Numerai manages an institutional grade long/short global equity strategy for the investors in our hedge fund. We transform and regularize financial data into machine learning problems for our global network of data scientists.

Our data scientists don't need capital, data, or finance domain knowledge to compete on Numerai. Numerai investors provide the capital, and Numerai embeds our finance domain knowledge into the design of our datasets.

Because Numerai data scientists do not know what our data represents, human biases and overfitting are overcome. Numerai does not know what algorithms our data scientists are using because data scientists only upload predictions—their code and intellectual property remains theirs. This trustless relationship between Numerai and our data scientists is facilitated by encryption, and anonymity.

Data scientists do not need to tell us who they are, and receive payments in Bitcoin.

Become a data scientist

A Rogue Intelligence

February 27th 2016, an artificial intelligence named NCVSAI joined Numerai. It’s creator downloaded encrypted stock market data, trained a machine learning model, and began submitting stock predictions to Numerai. He uses an untraceable email address. He doesn’t share any code. He is completely anonymous.

In early May, NCVSAI uploads a set of global equity price predictions from his model. At this time, NCVSAI had the most accurate model on Numerai. His strongest prediction: buy Salmar ASA — a Norwegian salmon company.

Numerai’s hedge fund went long Salmar ASA.

Learn more in Rogue Machine Intelligence and A New Kind of Hedge Fund


Solving global capital allocation would be equivalent to mankind allocating its resources perfectly forever. This is clearly worth getting right, and that is why there are so many people working in finance. The promise of artificial intelligence is that we can get to perfect capital allocation without the human capital cost. The world doesn't need another hedge fund, it needs exactly one hedge fund that's powered by every artificial intelligence.


Peter Diamandis

Founder of Singularity University and the IBM Watson AI XPRIZE

Ash Fontana

Board Member at Kaggle

Joey Krug

Thiel Fellow and Co-founder of Augur

Dr Norman H. Packard

Founder of Prediction Company


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