Electronic Resource

Article - The usefulness of ChatGPT for textual analysis of annual reports 10.02.2024

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Can predictive AI models be successfully deployed to help investors process complex financial
information? We answer this question by examining the usefulness of ChatGPT generated
sentiment and complexity scores for a sample of UK annual reports. We document that both
measures contain economically significant value-relevant information as captured by their
association with (i) price reactions to annual report announcements and (ii) future levels and
changes in profitability. Further, both measures predict dispersion in investor beliefs suggesting
they capture differences in how investors process textual content of annual reports. The results
suggest that investors can employ predictive AI models, such as ChatGPT, to aid them in analyzing
textual characteristics of annual reports.

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Judul Seri

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No. Panggil

657.30285 BIL u

Penerbit

: SSRN (Social Science Research Network) / University of North Texas Digital Library.,

Deskripsi Fisik

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Bahasa

English

ISBN/ISSN

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Klasifikasi

657.30285 BIL u

Tipe Isi

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Tipe Media

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Tipe Pembawa

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Edisi

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Subjek

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Info Detail Spesifik

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Pernyataan Tanggungjawab

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