【10月22日】数字金融Workshop 

第四讲 Harnessing Generative AI for Economic Insights 

时间/Time：2024年 10月22日 周二 北京时间 上午9:00-10:30

地点/Venue： Zoom会议（会议号: 897 2560 1400  密码: 938759）

主讲人/Speaker：杨保中 Baozhong Yang

主持人/Host：   胡佳胤 Jiayin Hu

摘要/Abstract:

We use generative AI to extract managerial expectations about their economic outlook from over 120,000 corporate conference call transcripts. The overall measure, AI Economy Score, robustly predicts future economic indicators such as GDP growth, production, and employment, both in the short term and to 10 quarters. This predictive power is incremental to that of existing measures, including survey forecasts. Moreover, industry and firm-level measures provide valuable information about sector-specific and individual firm activities. Our findings suggest that managerial expectations carry unique insights about economic activities, with implications for both macroeconomic and microeconomic decision-making. 

主讲人介绍/Biography:

Baozhong Yang is the H. Talmage Dobbs Jr Chair in Finance and Professor of Finance at the J. Mack Robinson College of Business in Georgia State University. He is also the Director of the FinTech Lab at the Robinson College, one of the first such labs associated with a business school in the nation. He has founded and organized the GSU-RFS FinTech Conference, a leading annual FinTech conference that offers dual submission to the premier journal Review of Financial Studies. Professor Yang is serving as an Associate Editor for the premier journal Management Science. Professor Yang has also served as referees for leading finance and economics journals and served on the Program Committees of prestigious conferences such as the Western Finance Association meetings.

Professor Yang’s research interests span theoretical and empirical studies in FinTech, Investments, and Corporate Finance. His most recent research involves innovative applications of Machine Learning and AI to study economic questions in Capital Markets and Corporate Finance. Professor Yang’s research has been published in leading academic journals in finance and other disciplines, including the Journal of Finance, Journal of Financial Economics, Review of Financial Studies, Management Science, and Journal of Accounting Research. His research has been widely cited and recognized by prizes such as the Michael J. Brennan Best Paper Award at the Review of Financial Studies, Panagora Asset Management Richard Crowell Prize (twice), Annual Conference on Digital Economics Best Paper Award, the SFS-Asia Cavalcade Best Paper Award, Chicago Quantitative Alliance Annual Academic Competition Prize, and Emerald Citations of Excellence.

Professor Yang’s papers have been extensively presented at prestigious conferences, such as the National Bureau of Economic Research (NBER) Big Data, NBER Economics of AI, NBER Blockchain, NBER Law and Economics, American Finance Association, and Western Finance Association meetings. He has been invited to present at leading universities, including Stanford University, UCLA, University of Maryland, University of Minnesota, and University of Toronto. Professor Yang’s research has been also widely covered by the media, including the NBER Digest, Bloomberg, Wall Street Journal, Financial Times, Forbes, The Guardian, CNBC, Chicago Booth Review, Columbia Law School Blog, Duke University FinTech Blog, and University of Oxford Business Law Blog.

Professor Yang received his Ph.D. in Finance from Stanford University and Ph.D. in Mathematics from the Massachusetts Institute of Technology. He has also been a Gold Medalist in the 33rd International Mathematical Olympiad while in high school.