Shanghai, April, 2026 – Can a mathematical model predict the stock market and evaluate a football player's hidden value at the same time? On April 22, the Xuemin Institute of Advanced Studies at Fudan University hosted the latest session of the "Xuemin Lecture," featuring Prof. Mathieu Rosenbaum from PSL-Paris Dauphine University. He introduced the audience to the fascinating world of "Hawkes Processes" and how this mathematical tool is revolutionizing both high-frequency trading and sports analytics.

Hosted by Dr. Xiaohong Helena Yang, Executive Dean of the Xuemin Institute, the lecture broke down complex mathematical concepts into engaging, real-world applications.

Giving Events a "Memory"

Prof. Rosenbaum began by explaining the core idea behind the Hawkes Process: it is a model for events that have a "memory." Unlike purely random events (like flipping a coin), many things in the real world are "self-exciting"—meaning one event increases the likelihood of another happening soon after.

Originally used to predict earthquakes and their aftershocks, the Hawkes Process has since been applied to predict crime waves, track how information goes viral on social media, and, most notably, understand financial markets.

A Unified Theory for the Stock Market

In the financial world, stock prices are driven by the flow of buy and sell orders. Prof. Rosenbaum demonstrated how his team used the Hawkes Process to solve a long-standing problem in finance: creating a single model that explains the complex behaviors of the market.

By analyzing massive amounts of high-frequency trading data, his team built a two-layered model. The first layer captures "fundamental trading" (investors buying or selling based on long-term value), while the second layer captures "reactive trading" (algorithms reacting to market movements in milliseconds). This breakthrough approach, known as "rough volatility," has fundamentally changed how experts understand and navigate modern financial markets.

Measuring the "Hidden Value" of Football Players

Moving from Wall Street to the football pitch, Prof. Rosenbaum shared an exciting new application of his research. Why are some players considered indispensable even if they rarely score goals?

Traditional football statistics focus heavily on direct actions like goals and assists, often ignoring the crucial contributions of midfielders and defenders. Using high-precision data tracking every touch of the ball, Prof. Rosenbaum’s team built a 12-dimensional Hawkes Process model to measure a player's "indirect contribution."

The model calculates how a single touch by a defensive player sets off a chain reaction that eventually leads to a scoring opportunity. The results showed that many defensive midfielders and center-backs are just as vital to a team's attack as the star forwards. This innovative approach provides football clubs with a powerful new tool for evaluating player value and refining team tactics.

About Prof. Mathieu Rosenbaum

Prof. Mathieu Rosenbaum is a Full Professor at PSL-Paris Dauphine University and is widely recognized as one of the world's leading experts in market microstructure and high-frequency trading. He is the pioneer of "rough volatility" models, a breakthrough that earned him the prestigious Louis Bachelier Prize in 2020. Beyond quantitative finance, he is a pioneer in sports analytics, collaborating with major organizations like the French Professional Football League and Paris Saint-Germain.

The Xuemin Lecture series is dedicated to building a high-level platform for cutting-edge academic exchange, inviting top global scholars to share their pioneering research and promote the integration of basic sciences across various fields.