



I intentionally avoid the world of quantitative investing on this podcast. The whole point of this format is to learn about many different fields, and the vast majority of my time is already spent in quant world.

Occasionally I’ve broken this rule because of something unique, including this week’s conversation with Richard Craib, the founder and CEO of Numerai. If you listen to the podcast often you’ll have heard me reference Numerai, a hedge fund which blends quant investing, cryptocurrencies, crowdsourcing, and machine learning — talk about a PR company’s dream.

One important note: Numerai is both incredibly open and very secretive. You may sense a bit of frustration on my part, but that is only because, as a fellow quant who loves details about data and modeling, we couldn’t go deeper into the details on the record.

We discuss how Numerai has created an incentive structure to work with data scientists around the world in an attempt to build better investing models. The idea of having data scientists stake cryptocurrency in support of the quality of their models is fascinating. Like many hedge funds, Numerai doesn’t share its track record, so we don’t know if this works—but I hope you, like me, use this conversation as inspiration for how different technologies can intersect.

Hash Power is presented by Fidelity Investments

Please enjoy my conversation with Richard Craib.

Show Notes

2:32 – (First Question) – How he came up with Numerai and how its related to his background

4:08 – How he works with and models the data for his system

5:24 – Describing machine learning as it relates to his work, and specifically linear regression

7:11 – The important stages in his sequence

8:46 – How the scale in the number of data scientists they use is different from other areas

11:30 – Which is the most important aspect of creating alpha; their data, algorithm work, proprietary ensembling of those algorithms.

14:30 – The idea of staking in blockchain

17:30 – Does the magnitude of the stake matter in blockchain

19:10 – Understanding the full incentive structure for both staked and unstaked work

21:07 – How is the prize pool determined

22:29 – Philosophy on how to source interesting data

26:11 – His thoughts on the crowd model and the wisdom of crowds

27:12 – The size of stakers for Numerai

27:51 – Interpreting the models and knowing when something is broken

30:03 – How they think about people not submitting their models

31:48 – Their model building

32:39 – Most interesting set of things they are working on to improve the overall process

35:38 – The Market for “Lemons”: Quality Uncertainty and the Market Mechanism

37:11 – How people can come along with their own data

39:00 – His thoughts on the quantitative investment community

40:44 – What else is interesting him in the hedge fund world

44:03 – Building a marketplace and staving off competition

46:16 – Kindest thing anyone has done for him