Time: Tuesday, April 28, 2026, 2:00-3:30 p.m.

Venue: Guoshun Campus, Starr Building, Room 603

Host: Zhe Geng, PhD, Department of Finance

Topic: LLM-Based Expectations and Fed Communication

Speaker: Professor Bin Li, Wuhan University

Abstract: We introduce a new approach to measuring monetary policy surprises in FOMC press conferences. Our method uses large language models (LLMs) to generate counterfactual press-conference responses by the Federal Reserve Chair and measures policy surprises as deviations between realized and simulated answers. Using high-frequency intraday data from 2011 to 2025, we show that equity prices respond strongly to these surprises: hawkish surprises lead to significant declines in stock prices, while dovish surprises increase prices. Importantly, markets respond to the unexpected component of communication rather than to the level of the expressed policy stance. Heterogeneity tests show that market responses to policy surprises operate through expectation formation and belief updating. Reactions are strongest when the Chair's answers directly inform the future policy path, namely for forward-looking, policy-related, or statement-linked questions, and are larger, though slower to emerge, during periods of elevated market uncertainty. Responses are also stronger following dovish FOMC statements, when prior expectations are less anchored. Finally, omitting macroeconomic context or the policy statement from the LLM prompt eliminates the return predictability of policy surprises. Our findings demonstrate that LLMs provide a powerful tool for identifying economically meaningful surprises in real-time policy communication.

Bio:

Bin Li is currently Professor in the Department of Finance, School of Economics and Management, Wuhan University. He is a recipient of a Ministry of Education young scholar title. His research fields include fintech, financial machine learning, and quantitative investment management. With an interdisciplinary background spanning finance and technology, he has published in journals in economics, management, and computer science, including Journal of Financial Economics, Journal of Accounting Research, Journal of Management Sciences in China, Journal of Financial Research, Artificial Intelligence, and Journal of Machine Learning Research, as well as conference proceedings such as ICML. He has led projects funded by the National Natural Science Foundation of China and the National Social Science Fund of China, with two National Natural Science Foundation projects receiving the highest post-evaluation rating. He is also a Chartered Financial Analyst (CFA) charterholder, serves as a Council Member of the Wuhan University Education Development Foundation and Deputy Director of its Investment Advisory Committee, and concurrently serves as a member of the Teaching Guidance Committee for Finance-related Majors under the Ministry of Education.