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Cited by 591

The DOI matches its Crossref record; 4 of the 4 references it cites were found in a registry or an index.

ChatGPT for (Finance) research: The Bananarama Conjecture

Open access
Dowling, Michael, Lucey, Brian·2023·Finance Research Letters
DOI 10.1016/j.frl.2023.103662
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Abstract

We show, based on ratings by finance journal reviewers of generated output, that the recently released AI chatbot ChatGPT can significantly assist with finance research. In principle, these results should be generalisable across research domains. There are clear advantages for idea generation and data identification. The technology, however, is weaker on literature synthesis and developing appropriate testing frameworks. Importantly, we further demonstrate that the extent of private data and researcher domain expertise input, are key factors in determining the quality of output. We conclude by considering the implications, particularly the ethical implications, which arise from this new technology.

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Metadata

Authors
Dowling, M., & Lucey, B.
Venue
Finance Research Letters
Publisher
Elsevier BV
Published
2023-05
Volume
53
Pages
103662
ISSN
1544-6123 (ISSN-L)
DOI
10.1016/j.frl.2023.103662
OpenAlex
W4318014888
Cited by
591
References
4
FWCI
51.74
Type
journal article
Language
en
Open access
hybrid

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CoChat. (2026). Citation check: ChatGPT for (Finance) research: The Bananarama Conjecture. https://app.cochat.ai/papers/10.1016/j.frl.2023.103662
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Dowling, M., & Lucey, B. (2023). ChatGPT for (Finance) research: The Bananarama Conjecture. Finance Research Letters. https://doi.org/10.1016/j.frl.2023.103662

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.