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Evidential strategies in financial statement analysis$sa corpus linguistic text mining approach to bankruptcy prediction
Journal of risk and financial management, 2022, Vol.15 (10), p.1-15
[Peer Reviewed Journal]
ISSN: 1911-8074 ;EISSN: 1911-8074 ;DOI: 10.3390/jrfm15100459
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Title:
Evidential strategies in financial statement analysis$sa corpus linguistic text mining approach to bankruptcy prediction
Author:
Nießner, Tobias
;
Gross, Daniel H
;
Schumann, Matthias
Subjects:
bankruptcy prediction
;
evidential strategies
;
financial statement analysis
;
text mining
Is Part Of:
Journal of risk and financial management, 2022, Vol.15 (10), p.1-15
Description:
The qualitative information of companies' financial statements provides useful information that can increase the accuracy of bankruptcy prediction models. In this research, a dataset of 924,903 financial statements from 355,704 German companies classified into solvent, financially distressed, and bankrupt companies using the Amadeus database from Bureau van Dijk was examined. The results provide empirical evidence that a corpus linguistic approach implementing evidential strategy analysis towards financial statements helps to distinguish between companies' financial situations. They show that companies use different approaches and confidence assessments when evaluating their financial statements based on solvency and vary their use of evidential strategies accordingly. This leads to the proposition of a procedure to quantify and generate features based on the analysis of evidential strategies that can be used to improve corporate bankruptcy prediction. The results presented here stem from an interdisciplinary adaptation of linguistic findings and provide future research with another means of analysis in the area of text mining.
Publisher:
Basel: MDPI
Language:
English
Identifier:
ISSN: 1911-8074
EISSN: 1911-8074
DOI: 10.3390/jrfm15100459
Source:
ProQuest Central
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