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Can Language Predict Bankruptcy? The Explanatory Power of Tone in 10‐K Filings
Author(s) -
Lopatta Kerstin,
Gloger Mario Albert,
Jaeschke Reemda
Publication year - 2017
Publication title -
accounting perspectives
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.238
H-Index - 17
eISSN - 1911-3838
pISSN - 1911-382X
DOI - 10.1111/1911-3838.12150
Subject(s) - bankruptcy , explanatory power , business , propensity score matching , predictive power , actuarial science , sample (material) , accounting , logistic regression , bankruptcy prediction , logit , matching (statistics) , going concern , finance , economics , econometrics , computer science , statistics , philosophy , chemistry , mathematics , audit , epistemology , chromatography , machine learning , auditor's report
We examine whether the language used in 10‐K filings reflects a firm's risk of bankruptcy. Our sample contains 424 bankrupt U.S. companies in the period 1994–2015 and we use propensity score matching to find healthy matches. Based on a logit model of failing and vital firms, our findings indicate that firms at risk of bankruptcy use significantly more negative words in their 10‐K filings than comparable vital companies. This relationship holds up until three years prior to the actual bankruptcy filing. With our investigation, we confirm the results from previous accounting and finance research. 10‐K filings contain valuable information beyond the reported financials. Additionally, we show that 10‐Ks filed in the year of a firm's collapse contain an increased number of litigious words relative to healthy businesses. This indicates that the management of failing firms is already dealing with legal issues when reporting financials prior to bankruptcy. Our results suggest that analysts ought to include the presentation of financials in their assessment of bankruptcy risk as it contains explanatory and predictive power beyond the financial ratios.