HKUST-NYU Stern MSGF and HKUST DBA programs are cohosting a seminar and program info session in Shanghai on April 18, 2026.

In this event, Prof. Jialin Yu will present findings from his recent finance research demonstrating that stock networks exhibit predictive lead-lag relationships in returns—indicators strong enough to generate returns that beyond what conventional investment strategies capture.

Program Heads from HKUST-NYU Stern MSGF and HKUST DBA programs will also be on site to introduce the programs. This is a great opportunity to meet the admissions team in person and seek guidance on your application. 

This talk will be of particular interest to senior executives, investment professionals, and policymakers seeking a rigorous yet practical framework for navigating increasingly interconnected financial markets.

About the Seminar “Networks, Images, and Lead-Lag Return Predictions”

Traditional investors typically focus on either individual companies or broad market factors like value and size. But our research reveals a powerful middle layer: the network of connections between stocks.

Here's the pattern: when a group of "leader" stocks moves today, related "laggard" stocks tend to follow tomorrow. This relationship is strong enough to generate meaningful returns beyond what traditional investment strategies capture.

We use a data-driven approach by treating the network of stock connections like an image and analyzing it with computer vision techniques. This reveals patterns that standard factors like market, value, profitability, and even momentum cannot explain. We also show that much of what was previously called "factor momentum" actually stems from these stock-to-stock lead-lag effects. And the most important connections vary over time rather than staying fixed to categories like industry or geography.

Key Management Insight: Investors and firms should view the stock market as a dynamic network, not a list of isolated tickers. Systematically identifying which stocks lead and which follow creates an additional source of returns. These cross-stock connections can also signal where risks may propagate (e.g., supply-chain stress, liquidity crunches), valuable for early-warning systems and stress testing. Firms can apply existing AI and image-processing infrastructure to better understand these complex financial and supply-chain networks.

Speaker: Prof. Jialin Yu, Academic Director of HKUST-NYU Stern Master of Science in Global Finance, Professor of Finance at HKUST

Date: April 18, 2026
Time: 2:00 pm- 4:00 pm
Venue: HKUST Shanghai Center, 上海市徐汇区云锦路701号37层
 

Register HERE! 
Seats are limited and not guaranteed upon registration. Successful registrants will receive a confirmation email before April 11, 2026.

We look forward to meeting you in Shanghai!