一、主题：From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
曹顺，佐治亚州立大学Robinson商学院终身副教授。美国伊利诺伊大学香槟分校会计学博士毕业。主要研究领域：公司信息披露，大数据分析，深度学习和人工智能，文本和图像分析。在Journal of Financial Economics, Journal of Financial and Quantitative Analysis, Journal of Accounting Research, The Accounting Review, Contemporary Accounting Research, and IEEE Computer等金融学、会计学和计算机科学领域的顶级期刊上发表多篇文章。
Abstract: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.