Quantitative methods shape the financial landscape in the 21st century. Deep within the numbers, stories are unfolding — and those stories quietly guide how practitioners think about alpha, risk, and asset management. The ability to analyze the growing body of financial data has become imperative for future financial leaders, and the Wharton School’s finance department is answering the call to teach these skills with a new degree program focused solely on quantitative finance: the Dr. Bruce I. Jacobs Master of Science in Quantitative Finance (Jacobs MSQF).
While the program itself is novel to the University of Pennsylvania, Wharton faculty have long been at the forefront of academic financial research. With a generous gift from Bruce I. Jacobs and Kenneth N. Levy, Wharton established the Jacobs Levy Equity Management Center for Quantitative Financial Research and the Wharton-Jacobs Levy Prize for Quantitative Financial Innovation in 2011 to advance quantitative finance at the intersection of theory and practice. The Center has since served as the School’s headquarters for disseminating the world’s most innovative quantitative findings. The Center, the Prize, and in 2020 the MBA major in quantitative finance, which is supported by gifts from Jacobs to establish the Dr. Bruce I. Jacobs Scholars in Quantitative Finance and the Dr. Bruce I. Jacobs Professorship in Quantitative Finance, have all contributed to the strong quantitative culture in the finance department.
All the while, Wharton faculty members have watched as new technologies continue to transform the field.
Incorporating Big Data Models Into Quant Finance
Quantitative finance relies on mathematical models and datasets to understand market trends, price securities, and evaluate risk. Nikolai Roussanov, the Moise Y. Safra Professor of Finance at Wharton and academic advisor for the MBA quantitative finance major, explains that quantitative finance uses “mathematical and statistical methods together with rich financial data to construct trading strategies, optimize portfolios, and control risk.” The applications can range from asset management to corporate finance, along with more big-picture wealth management strategies and asset allocation.
The scope of quantitative finance has evolved since its inception. In the 20th century, many “quants,” or quantitative finance professionals, were based in investment banks and hedge funds and employed heavily mathematical methods to conduct financial engineering. As the 21st century progressed, the field shifted from being primarily model-driven to incorporating a broader ecosystem that combines theory, computation, and large-scale empirical analysis.
“It’s not that models are less important. Different tasks and problems call for different tools and methods,” Roussanov elaborates. “Rather, it’s very empirical. We’re using data to understand the behavior of asset prices.” Today’s leading quantitative finance firms represent the use of empirical analysis in practice.
The emphasis on data analysis in quantitative finance is driven by new technology. Itay Goldstein, Joel S. Ehrenkranz Family Professor and chairperson of Wharton’s finance department, reflects on the changes he’s witnessed in the field over his academic career.
“There was an increase in computational power, which allows you to do a lot more analysis and do more sophisticated things,” he says. “There has been an increase in the availability of data and a lot more dimensions in which you can build a trading strategy or portfolio allocations.”
The advent of artificial intelligence marks a major advancement, Goldstein says: “We always talk about the introduction of AI, which uses even more sophisticated methods to find patterns in the data and even introduces machines that are learning by themselves and coming up with these new avenues by themselves without getting instructions from humans.”
Faculty research has been at the forefront of showing how artificial intelligence is transforming finance — and the risks embedded in that transformation. This faculty expertise sets the stage for Wharton’s newest degree program.
How the Jacobs MSQF Meets the Moment of Quant Finance
The Jacobs MSQF will bring students right to the technological frontier of Wharton faculty’s unmatched expertise in quantitative methods, machine learning, artificial intelligence, and financial markets.
David Musto, the Ronald O. Perelman Professor in Finance, was recently named faculty director of the Jacobs MSQF program. To understand how innovative this master’s program is, he explains, all one needs to do is look at what’s being added to the curriculum.
Musto is especially excited about the course in data science for finance. Although data science has been part of Wharton’s finance teachings, he explains, “It’s going to be adapted to the latest in AI, to bring it up to the cutting edge of quantitative techniques, fitting big models to the data to help pick up predictive patterns and manage money.”
This course will be taught by professor Winston Wei Dou, whose research with Goldstein on AI in finance has received acclaim for demonstrating the risk of AI-powered market manipulation through collusive trading, despite AI not being programmed for collusion.
Musto highlights another Jacobs MSQF course that will instruct students on the foundations of asset pricing. This course will be taught by Jessica Wachter, the Dr. Bruce I. Jacobs Professor in Quantitative Finance, who served as the chief economist and director of the Division of Economic and Risk Analysis at the U.S. Securities and Exchange Commission from 2021 to 2025. Musto sees this course as providing students with a doctoral-level understanding of asset pricing, which will help them build their own frameworks for pricing assets.
Wachter’s research recently made headlines after it revealed how investors systematically overreact to repetitive earnings news, then correct this overreaction in the months that follow. Those findings challenge widely held beliefs about market efficiency. Jacobs MSQF students won’t just learn about established frameworks; they’ll also engage with faculty who are actively redefining our understanding of markets.
Along with access to faculty experts, students will work directly with industry professionals from the Jacobs MSQF Advisory Board through the Applied Research Practicum. Musto explains that in this course, “The practitioner helps pose a question that the students work on — a sort of question you’d work on in the quant workplace.” The practicum will help bridge the gap between the theoretical training students receive in the classroom and the complexity that comes with real-world application.
Seizing the Opportunity to Become Finance Leaders
Advanced quantitative tools are reshaping the field, and Wharton is preparing its students to become leaders in this bold new future of finance. “This is a thriving industry,” says Goldstein. “There is a lot of opportunity for getting involved.”
Jacobs MSQF students will develop fluency with empirical tools. The quantitative finance field is becoming increasingly reliant on large datasets. The ability to mine useful information out of complex data represents the advantage Jacobs MSQF students will have upon entering the industry. “Empirical tools are key because we need to understand what data tells us,” Roussanov explains. “The bleeding edge of quantitative finance is understanding how these newfangled tools — in the previous decade, machine learning; now, it’s AI — are being increasingly used.”
Empirical skills are essential as discussion about AI’s adoption ramps up in the finance community. “There’s a lot of debate about the ability of AI to, in some sense, do a better job at prediction in a financial context,” Roussanov says. “That’s where a lot of academic research is focused, and these are the tools we want our students to be equipped with.”
One of the most purposeful elements of the program’s arrangement is its versatility. The framers of this degree wanted the material to remain relevant to developments in the business sector.
“Wherever the industry goes, we’ll be right there with it,” Musto emphasizes. The industry partners who make up the Jacobs MSQF Advisory Board are essential to this effort: “The board members are a window into the different cultures and different approaches of the companies they work for,” Musto says.
The students comprising the program’s first cohort will make history not only for Wharton, but also for the broader financial landscape. It’s a pivotal moment made possible by Jacobs’s vision and a devotion to quantitative finance inherent at Wharton. As Musto says, “Quant has always been central to the culture of the finance department, but now, with the Jacobs MSQF, we’ll be spreading and strengthening that culture among Wharton students and in the broader financial community.”
Published as “Building a Program for the Data-Driven Era” in the Spring/Summer 2026 issue of Wharton Magazine.
