Semantic Scholar Open Access 2023 24 sitasi

Can ChatGPT reduce human financial analysts’ optimistic biases?

Xiaoyang Li Hao Feng Hailong Yang Jiyuan Huang

Lihat Sumber DOI

Abstrak

Abstract This paper examines the potential of ChatGPT, a large language model, as a financial advisor for listed firm performance forecasts. We focus on the constituent stocks of the China Securities Index 300 and compare ChatGPT’s forecasts for major financial performance measures with human analysts’ forecasts and the realised values. Our findings suggest that ChatGPT can correct the optimistic biases of human analysts. This study contributes to the literature by exploring the potential of ChatGPT as a financial advisor and demonstrating its role in reducing human biases in financial decision-making.

Penulis (4)

Xiaoyang Li

Hao Feng

Hailong Yang

Jiyuan Huang

Format Sitasi

APA MLA BibTeX

Li, X., Feng, H., Yang, H., Huang, J. (2023). Can ChatGPT reduce human financial analysts’ optimistic biases?. https://doi.org/10.1080/20954816.2023.2276965

Akses Cepat

Lihat di Sumber doi.org/10.1080/20954816.2023.2276965

Informasi Jurnal

Tahun Terbit: 2023
Bahasa: en
Total Sitasi: 24×
Sumber Database: Semantic Scholar
DOI: 10.1080/20954816.2023.2276965
Akses: Open Access ✓