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.
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
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