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              講座:From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses

              發布者:金融系    發布時間:2021-04-29

              題 目:From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses

              嘉 賓:Sean Cao, Associate Professor, Georgia State University

              主持人:吳文鋒  教授、副院長  上海交通大學安泰經濟與管理學院

              時 間:2021514日(周五)14:30-16:00

              地 點:上海交通大學徐匯校區安泰樓A503 

              內容簡介:

              An AI analyst we build to digest corporate financial information, qualitative disclosure and news is able to beat the majority of human analysts in stock forecasts and generate excess returns compared to following human analysts alone. In the contest of “machine vs. human,” we find that the relative advantage of such an AI Analyst is stronger when the firm is complex, and when information is high-dimensional, transparent and voluminous. Human analysts remain competitive when critical information requires institutional knowledge (such as the nature of intangible assets). The edge of the AI analyst over human analysts declines over time, when analysts gain access to alternative data and to in-house AI resources. Combining AI’s computational power and the human art of understanding soft information produce the highest potential in generating accurate forecasts. Our paper suggests a future of “machine plus human” in high-skilled professions as an alternative to the replacement of humans by machines.

              演講人簡介

              Sean Cao is an associate professor at J. Mack Robinson College of Business of Georgia State University. Professor Cao’s research examines the usefulness of firm information and disclosures for investor and corporate decision-making. A unifying theme in his research is to protect investors’ wealth and increase firms’ operational efficiency and market value using large-scale data analytics of corporate disclosures. His research has been published in premier journals across finance, accounting, and computer science such as Journal of Financial Economics, Journal of Accounting Research, The Accounting Review, Contemporary Accounting Research, and IEEE Computer.

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