Unveiling Themes in 10-K Disclosures: A New Topic Modeling Perspective

Matthias Fengler and Minh Tri Phan
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Minh Tri Phan: University of St. Gallen (HSG)

No 24-106, Swiss Finance Institute Research Paper Series from Swiss Finance Institute

Abstract: We investigate the topics in the Management’s Discussion and Analysis (MD&A) section of 10-K filings. Our approach extracts MD&A topics by clustering words around anchor words that broadly define potential themes. The resulting topics are intelligible, distinct and multi-faceted, shedding light on why classical topic models applied to 10-K filings might lack interpretability. We extract two loading series from the MD&As: topic prevalence and topic sentiment. We find that topic prevalence exhibits significant variation throughout the sample period, while sentiment displays marked heterogeneity across topics. Linking MD&A topics to stock returns, we document non-uniform market perceptions toward the topic sentiment.

Keywords: 10-K files; MD&A; natural language processing; topic modeling (search for similar items in EconPapers)
Pages: 71 pages
Date: 2024-10
New Economics Papers: this item is included in nep-big
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Persistent link: https://EconPapers.repec.org/RePEc:chf:rpseri:rp24106

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