Who wins the man vs machine contest?
Cao et al. built their own AI model for 12-month stock predictions. Their “AI analyst” is trained using firm-level, industry-level, and macroeconomic variables, as well as textual information from firms’ disclosures, as inputs or predictors, but information from analyst forecasts was excluded. Their goal is to understand the circumstances under which human analysts retain their advantage, in that a forecast made by an analyst beats the concurrent AI forecast in terms of lower squared forecast error relative to the ex post realization. They find:
Human wins the “Man vs. Machine” contest when a firm is complex with intangible assets, and AI wins when information is transparent but voluminous. Analysts catch up with machines over time, especially after firms are covered by alternative data and their institutions build AI capabilities. AI power and human wisdom are complementary in generating accurate forecasts and mitigating extreme errors, portraying a future of “Man + Machine” (instead of human displacement) in financial analyses, and likely other high-skill professions.
From Man vs. Machine to Man + Machine: The Art and AI of Stock Analyses
Authors: Sean Cao, Wei Jiang, Junbo Wang, Baozhong Yang
From: Georgia State University, Emory University, Louisiana State University
