Revisiting Momentum through Dynamic Kernel Learning; AI Research and Networking Series, Feng Dong

On October 7, 2026, Dr. Feng Dong, Assistant Professor of Finance and Director of the Reed Finance Center at Elon University, presented “Revisiting Momentum through Dynamic Kernel Learning” as part of the AI Research and Networking Series, hosted by the Elon AI Hub. In this session, Dong explored how momentum in stock returns has changed over time and how machine learning can help researchers better understand these patterns. Drawing on nearly sixty years of U.S. equity market data, he examined how shocks to stock returns influence future prices, why traditional momentum strategies have weakened since 2000, and how a dynamic kernel learning framework can account for changing market conditions. His research demonstrated how computational approaches can contribute to financial research by identifying patterns that traditional models may not fully capture. Key Discussion Points include: How stock return momentum has evolved and why traditional strategies have weakened since 2000 Insights from nearly sixty years of U.S. equity market data How return-related shocks influence stock prices over time Using dynamic kernel learning to model changing market conditions How machine learning can uncover financial patterns that traditional models may miss Implications for financial research, investment strategies, and AI applications in finance About the Series The AI Research and Networking Series highlights AI-related research and applied work from Elon faculty as well as scholars and experts from outside the university. It is designed to support interdisciplinary dialogue, share current projects, and create space for collaboration. Each session includes a faculty-led presentation followed by time for discussion and networking. Since 2025, Elon has submitted four AI-related grant proposals and prepared two more, including collaborative NSF work with NC A&T and NC State and a Gates Foundation concept proposal. The series has provided a space for shared research interests to develop into grant work and other collaborations. About the Elon AI Hub The Elon AI Hub supports faculty, staff, and students as they think through how AI fits into their teaching, learning, research, and work. As stated in Elon’s Generative AI statement from the President and Provost, the decision to incorporate these technologies into teaching and learning is at the discretion of the Elon community. Some may choose to use generative AI in certain ways, and others may decide not to use it at all. The Hub does not promote or prescribe AI use. Our role is to provide clear information, practical examples, and hands-on support for those who want to better understand AI, AI tools, and how they are being used. Editorial Context The Elon AI Hub shares faculty perspectives on generative AI in teaching and research, including both those who use it and those who do not. These features are meant to document research, reflection, and experimentation, not to recommend a single approach. AI in academic settings raises questions about pedagogy, workload, data governance, equity, and student experience. Faculty and students are encouraged to weigh benefits and risks in light of their own goals and disciplines, as the university continues to review governance and ethical considerations. Featured Speaker: Dr. Feng Dong, Assistant Professor of Finance and Director of the Reed Finance Center, Elon University #ElonAIHub #AIResearchAndNetworking #ElonUniversity #ArtificialIntelligence #MachineLearning #FinancialResearch #AIinFinance #InterdisciplinaryResearch