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Unveiling themes in 10-K disclosures: A new topic modeling perspective

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  • Fengler, Matthias R.
  • Phan, Tri Minh

Abstract

We analyze the topics in the Management’s Discussion and Analysis (MD&A) section of 10-K filings. Based on word embeddings, our approach identifies MD&A topics by clustering words around anchor words that broadly define potential themes. The resulting topics are interpretable, distinct, and minimally affected by noise. From the MD&As, we extract two loading series: topic prevalence and topic sentiment, both of which exhibit substantial temporal variation and heterogeneity across topics. Examining the link between MD&A topics and stock returns, we reveal that the market response to topic sentiment varies across topics and time horizons.

Suggested Citation

  • Fengler, Matthias R. & Phan, Tri Minh, 2025. "Unveiling themes in 10-K disclosures: A new topic modeling perspective," International Review of Financial Analysis, Elsevier, vol. 103(C).
    • Handle: RePEc:eee:finana:v:103:y:2025:i:c:s105752192500208x
    DOI: 10.1016/j.irfa.2025.104121
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    Keywords

    10-K files; MD&A; Natural language processing; Topic modeling;
    All these keywords.

    JEL classification:

    • C55 - Mathematical and Quantitative Methods - - Econometric Modeling - - - Large Data Sets: Modeling and Analysis
    • G30 - Financial Economics - - Corporate Finance and Governance - - - General
    • M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting

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