Learning From the Renaissance (No, Not That One...)

Jim Simons is a mathematician and cryptographer who realized that the complex math he used to break codes could help explain financial patterns – and he made billions because of it in his notoriously secretive hedge fund firm called Renaissance Technologies.

He is famous not only for the duration of his success and the size of his results ... but also for the way he made his money (with much lower volatility and risk than his peers and competitors).

His flagship - the Medallion fund - has averaged a net return of 39.1% and has been closed to new investors since 1993. Even more impressive is that those results are on top of their 5% management fee and a 44% performance fee.

To put that into perspective, if you had invested $1,000 into the Medallion Fund in 1988 when it launched, your money would have grown to in excess of $23MM at the end of 2019.

His background is impressive. Simons taught at Harvard and MIT and worked with the NSA. Here is a video where he shares some thoughts in a 2015 TED talk interview. It's worth a watch.

 

via TED

Interesting stuff ... I hope you got something from it. 

His success exists at the nexus of vast amounts of data, next-level technological infrastructure, and intellectual property built by various flavors of mathematicians. A good place to be in the coming world, and a reminder that if you don't know what your edge is, you don't have one. 

Despite advanced math still being a mystery to many,  most rely on it more than ever ... for example, look at what we're seeing with the growth of machine learning and AI.

The Heartbeat of AI is Still Human

Today, the best algorithms are autonomous. They don't rely on inventors to derive novel insights from the ingested datasets. They take whatever data they can get their hands on, process it, and extract decision signals. Some don't even form hypotheses, they simply look for correlations - the data is an abstraction to be solved in the purest sense. 

You don't have to understand why the models do what they do - simply, what it's doing, and that you trust it's construction. 

Regardless of how autonomous the systems get, humans are still vital. 

Simons built a team of mathematicians whose motivation was doing exciting mathematics and science (rather than hired guns who could be lured away by money).

That doesn't mean money wasn't a motivator, but it hits on something important. 

The heart of good math and good AI will always benefit from the quality of the humans around it. You still have to champion integrity, culture, and purpose.

 

Better Math as a Competitive Advantage

We stayed ahead of the pack by finding other approaches and shorter-term approaches to some extent ... but the real thing was to gather a tremendous amount of data – Jim Simons

If you've been to our office, or heard me speak, you know how important I believe those ideas are to continuing prosperity. 

Constant innovation on a massive scope and scale creates more ways to win.

Onwards!