Zhendi Su and Cubist Systematic Credit

Zhendi Su joined Cubist as a portfolio manager in the San Francisco area two years ago to launch the Firm’s first systematic credit strategy. She took the time to tell us about her career and the opportunity for systematic credit.

 

How did you get interested in investing?

I studied STEM at school: first chemical engineering and then computer science. In those early years, I was having trouble finding something that excited me. I was missing that spark. Some friends who also studied STEM and then went on to work on Wall Street suggested I try finance.

I got a job in San Francisco in fixed income passive investing, doing analytics, programming, and math. It was fine, but a little boring, until one day the new head of the credit group on the hedge fund side of the business was looking for somebody with spare bandwidth to help him.

He gave me a project trading CDX, a technical quant strategy he wanted me to help him implement. It was using a programming language called R. I didn’t know R at the time. I studied computer science, but the programming languages I was most familiar with were C++ and Java. But the project sounded interesting. Why not give it a shot?

It became so interesting. It really felt like a light bulb went off. It was like, this is what I want to spend all my time on.

 

What came next in your career?

When I first joined the hedge fund group, I was essentially the junior PM on my team. I was taking care of all things technical on the desk. We were responsible for managing liquidity and portfolio risk. There was a separate research group that was responsible for writing the model. Being naturally curious, I wanted to know everything about these models and how they were created.

Because we are on the West Coast, my group had to be on the desk at 5:30 a.m. The researchers, they are night owls. They don’t come in early.

Our model would bomb all the time, because credit can be tricky: the data’s dirty, the vendor’s not reliable, liquidity is hard to model, whatever. So sometimes in the morning, the PM’s are ready to go, but the model is not. I saw an opportunity. I talked to the head of the researchers and said, “I’m happy to help you solve the production problem in the morning until you come in.” Of course, it was another programming language that I didn’t know, too!

So I learned a new (rather archaic) programming language on a giant piece of software that was written by probably 10-plus researchers over a decade, trying to figure out what went wrong. The benefit was that I learned a ton about the model. I used that opportunity to really learn everything about quantitative investing to the extent that in a couple years I was able to do the research back test and launch my own strategy. If I didn’t have that experience, I probably wouldn’t have been able to pull that off.

 

How have you seen systematic credit change since you started?

Just 10 years ago systematic credit was a very different world. I remember at the time my group sat next to the credit trading desk, and it was so loud because they were constantly talking on the phone, putting in orders. Their phones were ringing all the time. Whereas if you went up one floor to where the equity traders were, it was silent because everything’s done electronically. Over the years, it’s gotten quieter and quieter on the credit desk, too, as all these electronic trading platforms for credit are popping up. What used to be a phone call or an instant message is now a click on the computer. With that, there is a proliferation of structured data coming up.

 

Sounds like a huge opportunity.

Yes. This appeals to the entrepreneurial side of me. I draw the analogy from when equity trading went from manual to exchange and really exploded exponentially. People who were the early adopters of systematic quant equities back then, look at how successful they are. This is what I see as the opportunity.

 

What attracted you to Cubist?

I decided to come to Cubist, number one, because this is a state-of-the-art systematic equity shop. They’ve done it. They really know what’s going on in the equity world. They have the best data team and business operations. I’m going to borrow a lot of that expertise and use it to apply to the credit world.

This is a field that’s offering a lot of potential. It’s vastly changing. My vision is that probably five to 10 years from now, how people make money off of credit is going to look very different than today.

Also, I really appreciate that the whole management team here really have a lot of respect for investors, and they give you autonomy and a lot of help at the same time. It’s like the VC equivalent of finance. People who give you the backing, who give you the budget, the help when you need it, and the freedom and autonomy to let you build your own system. I felt like that was a good fit. Looking back, it was a really good decision. The last couple years have been just great for me.

 

Do you have any advice for analysts?

A couple of things come to mind. Number one is the power of compound interest. Every day you do 5% more, and it really builds up your knowledge base. Over the long run, it makes a huge difference. I look back and 15 years ago, I probably didn’t know what a bond was. But I never stopped trying to do that 5% more every single day.

Number two is don’t be afraid to jump off the deep end. That seems scary, but trust that given enough effort and perseverance, you will find the answers that you need. A lot of people are rooting for you and help is often readily available as long as you ask for it. It often takes a village to succeed and you are never alone.

Number three, and I cannot emphasize this enough, is follow your bliss. I’ve tried chemical engineering, technology, computer science. Quant finance is something that keeps me wanting to do that 5% extra every day. Never underestimate it if you find something that really lights you up, follow that!