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| Type | Journal Article |
| Scope | Discipline-based scholarship |
| Title | Can ChatGPT reduce human financial analysts’ optimistic biases? |
| Organization Unit | |
| Authors |
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| Item Subtype | Original Work |
| Refereed | Yes |
| Status | Published in final form |
| Language |
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| Journal Title | Economic and Political Studies |
| Publisher | Taylor & Francis |
| Geographical Reach | international |
| ISSN | 2095-4816 |
| Volume | 12 |
| Number | 1 |
| Page Range | 20 - 33 |
| Date | 2024 |
| Abstract Text | 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. |
| Digital Object Identifier | 10.1080/20954816.2023.2276965 |
| Other Identification Number | merlin-id:24297 |
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| Keywords | ChatGPT, Large language model, Analyst forecast, Optimistic biases, Human-machine interaction |