 A Topic Model for 10-K Management DisclosuresMatthias Fengler and Minh Tri Phan () No 2307, Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Abstract: We investigate the topics discussed in the Management's Discussion and Analysis (MD&A) section of 10-K filings from January 1994 to December 2018. In our modeling approach, we elicit the MD&A topics by clustering words around a set of anchor words that broadly define a potential topic. From the topics, we extract two hidden loading series from the MD&As - a measure of topic prevalence and a measure of topic sentiment. The results are three-fold. First, the topics we find are intelligible and distinctive but are potentially multi-modal, which may explain why classical topic models applied to 10-K filings often lack interpretability. Second, topic prevalence and sentiment tend to follow trends which, by and large, can be rationalized historically. Third, sentiment affects topics heterogeneously, i.e., in topic-specific ways. Adding to the extant document-level techniques, our study demonstrates the potential benefits of using a nuanced topic-level approach to analyze the MD&A. Keywords: 10-K files; MD&A; natural language processing; topic modeling (search for similar items in EconPapers) Downloads: (external link) Related works: Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text Persistent link: https://EconPapers.repec.org/RePEc:usg:econwp:2023:07 Access Statistics for this paper More papers in Economics Working Paper Series from University of St. Gallen, School of Economics and Political Science Contact information at EDIRC. |
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