From Man vs. Machine to Man plus Machine: The art and AI of stock analyses

被引：16

作者：

Cao, Sean ^{[1
]}

Jiang, Wei ^{[2
]}

Wang, Junbo ^{[3
]}

Yang, Baozhong ^{[4
]}

机构：

[1] Univ Maryland, Robert H Smith Sch Business, College Pk, MD USA

[2] Emory Univ, Goizueta Business Sch, Atlanta, GA 30322 USA

[3] Louisiana State Univ, EJ Ourso Coll Business, Baton Rouge, LA USA

[4] Georgia State Univ, J Mack Robinson Coll Business, Atlanta, GA USA

来源：

JOURNAL OF FINANCIAL ECONOMICS | 2024年 / 160卷

关键词：

Artificial intelligence; Machine learning; FinTech; Stock analyst; Alternative data; Disruptive innovation; CROSS-SECTION; RISK PREMIUM; BIG DATA; EARNINGS; MARKET; INVESTMENT; RETURNS; INFORMATION; PERSISTENCE; FORECASTS;

D O I：

10.1016/j.jfineco.2024.103910

中图分类号：

F8 [财政、金融];

学科分类号：

0202 ;

摘要：

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.

引用

页数：22

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