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When Mayannk Kumar Singh from Kolkata and Utkarsh Pandey from Bangalore first crossed paths in a group project during their first MSc in Financial Engineering course at WorldQuant University, neither expected their collaboration would lead to published research — but that’s exactly what happened.

What began as a class assignment grew into a shared interest in exploring fundamental investing indicators, eventually leading them to co-author a technical whitepaper titled "Effectiveness of Enterprise Multiple(EM) in Determining Returns in Technology Stocks." The study was later published in the International Journal for Multidisciplinary Research Review and Studies (IJMRRS). How did they get here?

Mayannk was particularly drawn to understanding the fundamental aspects of investing: "I wanted to explore what the fundamental aspect was to investing or to gaining some insights into the markets based on the returns." Noting that recent research tended to overlook fundamental indicators, he proposed analyzing Enterprise Multiples (EM) as a predictor of stock returns and reached out to Utkarsh to collaborate. Utkarsh recalled how the research journey evolved. “We were kind of lost in the big sea of topics in finance. It took us six courses to really find our footing and decide on a focus. Once we figured it out, we completed the paper in about two months.”

The pair had a clear goal in mind: to apply what they learned in the MScFE program in a way that would feel straightforward and accessible: “We wanted to present our work in a way that’s easy for other students to follow,” Utkarsh added. “As students ourselves, we know how overwhelming the technical details of whitepapers can be. I’m confident that if fellow WQU students read our paper, they’ll be able to follow along and connect it to the courses they’ve completed or will come across in the future."

Their study examined the effectiveness of the Enterprise Multiple (EV/EBITDA) in predicting technology stock returns. Utilizing time-series analysis, including GARCH models, they accounted for the heteroskedastic nature of stock data since 2017. They applied a weighted aggregation scheme to balance data reliability across different years. Their analysis concluded that Enterprise Multiples were less reliable than P/E ratios in predicting stock returns, as indicated by adjusted R² values showing weaker explanatory power than a simple mean-based model.

Conducting independent research alongside professional commitments and coursework deadlines was no small feat, but both found the Program’s real-time progress tracking and quick feedback invaluable. They advise new students to trust the curriculum, as "topics will connect over time."

Looking ahead, Mayannk, whose background is in electronics and communication, hopes to apply his MScFE degree to secure a role at a hedge fund. Utkarsh, currently a back-end engineer at a cybersecurity startup, is seeking roles that blend programming, math, and finance. While their career paths may diverge, Mayannk and Utkarsh plan to continue collaborating and contributing to the financial engineering community — a partnership that began with a simple group project at WorldQuant University and has already made its mark.