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

dc.contributor.author Wang, Junbo
dc.contributor.author Cao, Sean
dc.contributor.author Yang, Baozhong
dc.contributor.author Jiang, Wei
dc.date.accessioned 2021-11-12T18:42:41Z
dc.date.available 2021-11-12T18:42:41Z
dc.date.issued 2021
dc.description.abstract An AI analyst we build to digest corporate financial information, qualitative disclosure, and macroeconomic indicators is able to beat the majority of human analysts in stock price forecasts and generate excess returns compared to following human analysts. In the contest of “man vs machine,” the relative advantage of the 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 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 produces the highest potential in generating accurate forecasts. Our paper portraits a future of “machine plus human” (instead of human displacement) in high-skill professions.
dc.identifier.uri http://hdl.handle.net/10125/76922
dc.subject Artificial Intelligence
dc.subject Machine Learning
dc.subject FinTech
dc.subject Stock Analyst
dc.subject Alternative Data
dc.subject Disruptive Innovation
dc.title From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
dc.type.dcmi Text
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