Quants worth following: Marco Jean Aboav

"Quants worth following" is our interview series highlighting thought leaders in the quantitative trading industry who actively share their knowledge and resources with the community.

Marco Jean Aboav has spent two decades at the intersection of academia and quantitative finance. After earning his PhD, he began his career as a portfolio quant strategist before founding Etna Research, a financial AI firm focused on alpha discovery. Today, he balances his role as CEO with teaching financial technology as an associate professor, offering a rare dual perspective on the field.

In our conversation, Marco reflects on this journey and shares how data, AI, and infrastructure are shaping the next wave of innovation in quant trading, while also bridging the gap between research and real-world application.

While completing his PhD in London, Marco found himself surrounded by a thriving financial ecosystem.

“You can only watch the action from afar for so long. Eventually, I wanted to be part of it.”

Rather than choosing one path over the other, he set out to apply academic rigor to real-world problems—a mindset that continues to shape his work today.

The biggest divide, he says, lies in the objective function.

“One is focused on producing great papers. The other—if you're in systematic strategies—is about making PnL with decent risk. It’s a totally different engineering goal.”

Still, Marco sees value in blending both. Academic training offers depth and discipline, while industry experience sharpens practical intuition. For him, the strongest ideas are those that bridge the two worlds: rigorous, but built for execution.

Today’s quant landscape is more interdisciplinary than ever. A strong foundation in computer science, statistics, and financial modeling is now table stakes.

“Back then, everyone was using MATLAB and had only a basic grasp of computer science.”

Now, the bar is both higher and broader. Marco emphasizes that it’s not about having a PhD—it’s about applying a scientific mindset to real-world systems. And that starts with understanding the data.

“Everyone jumps to machine learning, but if you don't know where your data comes from, the fancy algorithms won't save you.”

Too often, junior quants reach for complex models without first building domain expertise. For Marco, the strongest quants are those who understand how data is generated—and how to engineer systems around it.

“Computer science is how you control your destiny.”

Tired of repeating the same advice, he built a public wiki to help others master the fundamentals of financial data science. From generative AI to signal processing, he believes the quants who can write scalable code—and understand what they’re modeling—are the ones who stay relevant.

While many traditional models are now rebranded under the AI/ML umbrella, Marco argues that the math is only part of the story.

“Without strong engineering, your models won’t make it to production.”

The real challenge lies in infrastructure. Quants today need to think like engineers—designing systems that are robust, testable, and deployable, not just mathematically elegant.

At the same time, macro volatility has become a growing concern. Geopolitical and economic shocks remain difficult to price, even as data access improves.

“You’re always one policy flip or tweet away from your PnL being upside down.”

Signals like CDS spreads or ETF flows may be more measurable, but that doesn’t make them more stable. Marco cautions that quantifying risk isn’t the same as mitigating it.

For students entering the field, the key is adaptability. Marco encourages building a foundation across finance, engineering, and business, not just for technical strength, but to stay creative as the landscape shifts.

“The quant mindset is what allows you to approach new problems and build something meaningful.

He points to emerging trends like modular data infrastructure and enterprise consumerization as areas where technical skill meets real-world impact.

The rise of retail tools and platforms has made markets more accessible, but Marco questions how much real power that gives individual investors.

"It’s a great business model—just look at Robinhood—but whether it benefits the average user is still up for debate."

He sees democratization as often being more about risk transfer than empowerment. Access is easier, but outcomes remain uneven.

Structured finance is evolving beyond static, one-size-fits-all products. With advances in infrastructure and AI, Marco sees a shift toward real-time, on-demand customization.

“The technology is here. Structuring is the next big game.”

His team is building tools that let investors generate and manage strategies dynamically, combining QIS infrastructure with AI agents to make product creation faster and more flexible. For Marco, the ability to structure on the fly is the next frontier.

Etna was created to solve a problem Marco had seen throughout his career: the friction between innovation and implementation.

“Think QIS on steroids—powered by deep infrastructure and AI-enhanced distribution.”

By offering modular building blocks for clients to construct their own systematic strategies—and deploying AI agents to support both engineering and sales—Etna is designed for speed, scale, and adaptability.

“You don’t need to be in New York or London anymore. The opportunity is global—and it’s being built right now.”

Marco believes the next wave of financial innovation will come from distributed teams. As automation accelerates and infrastructure improves, traditional career ladders are giving way to entrepreneurial ecosystems. Finance, he says, is no longer about where you are—it’s about what you build.

Catch the full interview with Marco Jean Aboav on YouTube here. For more interviews with professionals shaping the future of quant finance, explore the rest of our "Quants worth following" series here.