“From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses,” forthcoming in Journal of Financial Economics*

An AI analyst trained to digest corporate disclosures, industry trends, and macroeconomic indicators surpasses most analysts in stock return predictions. Nevertheless, humans win ‘‘Man vs. Machine’’ when institutional knowledge is crucial, e.g., involving intangible assets and financial distress. AI wins when information is transparent but voluminous. Humans provide significant incremental value in ‘‘Man + Machine’’, which also substantially reduces extreme errors. Analysts catch up with machines after ‘‘alternative data’’ become available if their employers build AI capabilities. Documented synergies between humans and machines inform how humans can leverage their advantage for better adaptation to the growing AI prowess.

*American Association of Individual Investors (AAII) Best paper award winner, 2022 Midwest Finance Association Best Paper Award Winner, 2022 Global AI Finance Conference Best Paper Award Winner, 2022 CFRC Conference, PBC School of Finance, Tsinghua University Best Paper Award Winner, 2022 Annual Conference in Digital Economics, ACDE Best Paper Award Winner in Asset Pricing, 2022 SFS Cavalcade Asia-Pacific Conference

Sean Cao (Robert H. Smith School of Business, University of Maryland)

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