Tisha HiraniVerified

Filmmaking and quant look very different on paper, but I think the mindset overlaps more than I expected. In editing, you're constantly asking what actually matters to the story and what is just noise. In quant research, it's surprisingly similar, you can generate hundreds of ideas, but most of them don't survive testing.

Filmmaking also taught me to be comfortable iterating without getting attached to the first version of an idea. That has probably helped me more in research than the "filmmaker's eye for patterns" ever could.

The opening scene would probably be four people sitting around trying to figure out what exactly we had gotten ourselves into.

The plot twist was that the competition kept getting more serious, while our preparation somehow kept getting more chaotic. We went from experimenting with ideas to testing hundreds of alphas, dealing with bad ideas, good ideas that didn't survive testing, and eventually making it to the national finals.

And then we won Nationals. That part definitely wasn't in the original script.

I got into quant through competitions rather than through a traditional finance route. I was already interested in mathematical problem-solving and programming, and I came across quantitative trading and WorldQuant's competitions.

What clicked for me was the research loop: you have a hypothesis, you turn it into something testable, you run it against data, and the data gets the final say. I liked that there was very little room for convincing yourself that an idea was good just because it sounded good.

I don't think I've found a perfect balance yet. There were definitely periods where one thing completely took over, especially during the final stages of IQC.

What helped was treating them differently. Classes had fixed deadlines, while research could easily expand indefinitely, so I had to get better at deciding when an idea had been tested enough and moving on.

And honestly, some weeks involved a fairly unreasonable amount of sleep deprivation. I wouldn't recommend that part of the strategy.

I'd say my biggest role is stress-testing our ideas. I tend to take a hypothesis and keep pushing at it, questioning the assumptions, asking my teammates for opposing views, and looking for explanations we might have missed. I want us to know not just whether an alpha works in the IS period, but why it works, when it could fail, and whether that reasoning holds in other years and situations.

I'm also the people person in the team. I handle a lot of the outreach and networking, but I see that as part of the research process, bringing in new perspectives, asking the right people the right questions, and turning those conversations into better ideas for the team.

The toughest part was probably the final stretch, when the pressure increased much faster than the time available. We had ideas that looked promising but weren't robust enough, deadlines getting closer, and very little room to experiment blindly.

The way we got through it was by becoming much more ruthless about prioritisation. Instead of trying to make every idea work, we focused on what had evidence behind it, tested aggressively, and cut what wasn't working.

That was probably one of the biggest lessons from the competition: sometimes the most useful research decision is deciding what not to spend another three hours on.

I don't think you need to act like a man to enter a domain that has nothing to do with gender. If you like it, you simply do it. Of course you'll look stupid at the start, but that's true when you enter any new domain.

And honestly, I think a little audacity goes a long way. There are plenty of people who walk into quant with ridiculous confidence before they actually know what they're doing. You don't need to wait until you feel completely ready. Start, be willing to look stupid for a while, and let yourself get good at it.

One thing that surprised me was how often an idea that sounded intuitively strong turned out to be weak once we actually tested it. And sometimes the opposite happened, relatively simple ideas could become surprisingly useful after the right transformations, neutralisation or combination with other signals.

It made me much more skeptical of intuition on its own. In quant, an idea isn't really interesting because it sounds clever. It's interesting when the data keeps giving you a reason to believe it.

For the Global Finals, I'm focusing on two things: improving the research process and understanding why our strongest signals work rather than just optimising their performance. At this stage, robustness matters much more than finding one spectacular backtest.

And obviously, I'd love to win. But getting to represent India internationally has already been a pretty surreal outcome for something that started as a competition I was curious enough to try.

In five years, I'd like to be doing quantitative research professionally. That's definitely the direction I'm most serious about.

Filmmaking is something I picked up because I genuinely enjoy editing and making things. I don't see it as an alternative career I need to somehow combine with quant. I'd like to keep doing it on the side because it makes college more than just classes, competitions, and internships.

I think I'll be happier looking back and remembering that I actually did things I enjoyed in my free-willed years, rather than realising I spent all of them preparing to be "professional."