Making better analysts’ forecast – an investigation of artificial intelligence applications in corporations
We explore the impact of artificial intelligence (AI) applications in corporations on analysts’ earnings forecast errors. We construct firm-level AI application data using text mining methods with Chinese A-share listed companies from 2011 to 2023. Our findings reveal that AI applications in corporations significantly reduce analysts’ earnings forecasting errors. Additionally, AI applications to reduce analysts’ earnings forecast errors are achieved through improving the accounting information quality of corporations and attracting more analysts to field research activities.
Authors
- Lei Chen (ORCID: https://orcid.org/0000-0003-4664-0700)
- Xiaotong Cai (ORCID: https://orcid.org/0000-0002-0406-5317)
- Wenhua Wang (ORCID: https://orcid.org/0000-0002-7682-0860)
- P. C. Lin
Institutions
- Fudan University (CN)
- University of Finance and Economics (MN)
- Guangdong University of Finance (CN)
- Yunnan University of Finance And Economics (CN)
- Vrije Universiteit Amsterdam (NL)
Publication Details
- Journal
- Applied Economics Letters
- Published
- 2025-02-26
- DOI
- https://doi.org/10.1080/13504851.2025.2472036
- Citations
- 1
- Primary Topic
- Big Data and Business Intelligence
- Type
- article
- Field-Weighted Citation Impact
- 2.28
Funders
- Guangzhou Office of Philosophy and Social Science
- China Postdoctoral Science Foundation
- Humanities and Social Science Fund of Ministry of Education of China