In the summer of 2024, three talented students—Sophia, Marvin, and Mannan—joined Optiver Amsterdam as trading interns. Alongside 16 of their peers, they embarked on a significant group project aimed at predicting one-day-out realised volatility. While united by a common goal, each intern brought a unique perspective, skill set and approach to the challenge.

We spoke with them during the project phase of their eight-week internship. They shared insights into their training, simulated trading experiences, and how these shaped their contributions to the collective project.

Meet Sophia

Study: Mathematics and Philosophy

Meet Marvin

Study: Data Science and Business

Meet Mannan

Study: Mathematics and Statistics

Building a strong foundation: From lectures to simulated trading

The internship began with lectures, trading games and simulated trading sessions, equipping interns with the practical insights and decision-making skills essential for tackling their project.

What was the initial training like, and how did it prepare you for the challenges ahead?

Sophia: The first week felt like being back in university lectures, but with more focused study led by experts in the field, which was quite cool. We covered finance-specific topics like options, trading theory, and macroeconomics. Having about 60 interns—both tech and trading—together in one room made it more interactive and you see other people’s perspectives on things.

Marvin: The first one and a half weeks were a mix of lectures, daily trading games, and some open-outcry exercises—like estimating the number of words in all the Harry Potter books. That was interesting since I hadn’t read them and didn’t even know how many there were! You just go with your best estimate and trade off that.

The instructors would pause our trading games whenever they saw we might be going off track, especially in the first days. It was cool because we got live feedback right then and there. It kept things moving and wasn’t just back-to-back lectures.

Mannan: The first couple of weeks were intense—like covering a whole term’s worth of uni content in just seven days. The trainers made it manageable by focusing on making everything practical, which I preferred over pure theory. I’d never learned at this pace before, but there was lots of support, and I could tell everything we learned would be useful later.

How did you apply your newfound knowledge in a simulated trading environment?

Marvin: The term “sim trading” is almost misleading because we’re actually trading in live markets—the EURO STOXX 50 options—just with paper money. Our trades don’t hit the exchange or use real money, but we’re using the same systems as the traders downstairs, and it all unfolds live. It wasn’t just theory or projects—it was applying all of that in real time, which gave us a true sense of what it might be like if we were doing it for real.

Sophia: When you first start sim trading, for the first hour, you immediately forget the theory you’ve done. You’re just looking at colours, graphs, and lots of flashing things on the screen, having fun pushing buttons. Then, once you get used to what buttons to push, you start to actually think about the theory. You make the connection—”Here’s what I learned three days ago, and that’s how it’s relevant here.”

Mannan: Every couple of days during sim trading, we’d get a 30-minute shadow session where one of the traders or mentors sits with you and asks about your decision-making—why did you do this, why did you do that. You learn so much more than you realise in those 30 minutes—they make you re-evaluate almost everything you’re doing.

Tackling the challenge: The S&P straddle project

Armed with practical experience, the interns dove into their project: determining whether buying a same-day expiring S&P 500 straddle and immediately reselling it 15 minutes later would be profitable. Each intern approached the project’s complexities from their unique standpoint..

What was the initial training like, and how did it prepare you for the challenges ahead?

Sophia: We’re in a group of 19 people all working on the same project. The question is: If you bought this straddle that’s going to expire today and then sold it 15 minutes later, would you make or lose money, and how much?

We’re trying to find a model for this based on linear regressions and tons of data we have access to. It’s not an easy problem—if there were a straightforward solution, everyone would have made a bunch of money on it. So it’s more of an exploratory project to see if there’s anything interesting in the data that Optiver hasn’t really looked at yet.

Marvin: We started by coming up with our own ideas but also talked to some of the traders who trade these options. Understanding the signals they look for daily helped us incorporate similar things or build new hypotheses based on their experience. It’s a broad and open project in one of the most liquid volatility markets in the world, so even generating a small positive P&L is a good result.

Mannan: Our goal is so open-ended—I really like that about it. I haven’t had a lot of experience with data analysis and research, so it was all very new to me. But I like how it’s not just about analysing data or building complicated models; we’re using linear regressions and keeping it simple. It’s more about the ideas you can come up with and thinking creatively about how to make money—basically, coming up with something new.

How did you approach the group nature of the project?

Sophia: Our group has been pretty collaborative—we always share the results we get, whether it’s “don’t bother looking at this, I didn’t find anything” or “this could be really useful, you should have a look at it too.” We often see something interesting or weird, graph it, and get everyone to discuss why it’s happening.

We have quite different ways of thinking about and approaching problems, so it’s never the same person solving the problem every time. It’s really useful how much more we get done as a group or just by having another pair of eyes on something.

Marvin: For the first week, we were all working by ourselves—brainstorming ideas together but executing and coding them individually. Then our group got put into smaller teams, and it was fun seeing all the different approaches people had.

I realised we could go through our ideas a lot more efficiently by splitting up the work. One of us is working on building a backtesting engine while others are creating different features. Apart from our group we also talked to traders who actually work with these options—they shared the signals they look for, which helped us add practical elements to our models that we wouldn’t have thought of on our own.

Mannan: Because of the scale of the project, it’s not feasible for one person to achieve everything in a week and a half. Sharing our challenges and successes made us more effective as a group. Even though there are 19 of us, everyone seems to be exploring different avenues, and at the end of the day all our ideas come together to make something really impactful. 

Are you ready to take on real-world challenges and collaborate with bright minds from around the globe?

At Optiver, we empower interns to dive deep into the world of trading, offering hands-on experiences that bridge the gap between theory and practice. If you’re excited by the prospect of working on meaningful projects in a dynamic and collaborative setting, explore our internship opportunities.