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Research: Earnings Call Text Predicts Financial Restatements, But LLMs Face Data Leakage Issues

By PulseAugur Editorial · [1 sources] ·

A new research paper explores whether the language used in earnings calls can predict financial restatements. The study found that while text analysis can predict restatements to some extent, it does not significantly improve upon existing public firm information. A large language model performed better but raised concerns about data leakage and temporal relevance, as it was trained on data released after the restatements occurred. AI

IMPACT Highlights the need for careful evaluation of LLM performance in financial analysis, particularly regarding data leakage and temporal relevance.

RANK_REASON The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]

Read on arXiv cs.CL →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

Research: Earnings Call Text Predicts Financial Restatements, But LLMs Face Data Leakage Issues

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The cluster contains a research paper published on arXiv. [lever_c_demoted from research: ic=1 ai=0.4]
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COVERAGE [1]

  1. arXiv cs.CL TIER_1 English(EN) · Ahmet Efe, Shivank Sapra, Bilal Ahmed ·

    Do Earnings Calls Help Predict Financial Restatements? Evaluating Text Beyond Public Firm Information

    arXiv:2611.01123v1 Announce Type: new Abstract: Financial restatements correct errors in previously published financial reports. Could managers' language in earnings calls warn of them in advance? Comparing 109 calls that precede restatements with 218 matched control calls, we fi…

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