Renaissance Technologies (“Ren Tech”) is one of the world's most successful and secretive hedge funds. It was founded by Jim Simons, a mathematician with a long history of contributions (Chern-Simons form, developments in string theory, and more in geometry and topology). He was also a code breaker in the Cold War.
Peter Brown, the CEO of Ren Tech, recently gave an interview where he outlined some of the operating principles behind the company. Brown studied under Geoffrey Hinton (one of the leading figures in modern machine learning). While Ren Tech is a quantitative hedge fund, it’s still surprising how many principles have to do with developers and technical infrastructure.
You can listen to the entire podcast here. But here’s the transcript where he talks about the operating principles, unedited.
First. Science. The company was founded by scientists. It’s owned by scientists. It’s run by scientists. We employ scientists. Guess what, we take a scientific approach to investing and treat the entire problem as a giant problem in mathematics.
Second. Collaboration. Science is best done through collaboration. If you go to a physics department, it would be absurd to imagine that the scientist in one office doesn't speak to the scientist in the office next door about what he or she is working on. So, we strongly encourage collaboration between our scientists. For example, we encourage people to work in teams. We constantly change those teams up so that people get to know others within
the firm. We pay everyone from the same pot instead of paying different groups in accordance with how much money they've made for us and so forth.
Third. Infrastructure. We want our scientists to be as productive as possible. And that means providing them with the best infrastructure money can buy. I remember when I was at IBM, there was this attitude that programmers were like plumbers. If you need a big project done, just get more programmers. But I knew that some programmers were, like, ten times or more productive than others. I kept pushing IBM management to recognize this fact. But it did not.
I remember being in an IBM managers meeting and some guy from corporate headquarters was explaining how they created something called their headlights program. The goal of which was to identify the best programmers in the company and pay them 20 percent more than the other programmers. Now, I figured this guy from corporate was making, like, $300,000 a year. So, I raised my hand and suggested they increase the pay of their best programmers to $400,000 a year. And he was stunned. He said, "What?
More than me? You've got to be kidding me. Well, if the guy's Bill Gates." I said, "No, Bill Gates was making, like, 400 million per year. Not 400,000." Anyway, they just didn't get it.
Okay, our fourth principle is no interference. We don't impose our own judgment on how the markets behave.
Now, there's a danger that comes along with success. To avoid this, we try to remember that we know how to build large mathematical models and that's all we know. We don't know any economics. We don't have any insights in the markets. We just don't interfere with our trading systems.
Yes, of course there are a few occasions where something's going on in the world and so we'll cut back because we think the model doesn't appropriately appreciate the risk of what's going on. But those occasions are pretty rare.
And finally, and most importantly, the last principle is time. We've been doing this for a very long time. For me, this is my 30th year with the firm. And Jim and others were doing it for a decade before I arrived. This is really important because the markets are complicated and there are a lot of details one has to get straight in order to trade profitably. If you don't get those details straight, the transaction costs will just eat you alive. So, time and experience really matters.