Can ChatGPT reduce human financial analysts' optimistic biases?

Xiaoyang Li, Haoming Feng, Hailong Yang, Jiyuan Huang

ECONOMIC AND POLITICAL STUDIES-EPS(2024)

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摘要
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.
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关键词
ChatGPT,large language models,analyst forecast,optimistic biases,human-machine interaction
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