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ArticlePredicting distresses using deep learning of text segments in annual reports

Rastin Matin2019

Article2019

Predicting distresses using deep learning of text segments in annual reports

Rastin Matin · Pia Mølgaard

103 citations·0/0 files stored·Expert Systems with Applications

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Financial Distress and Bankruptcy Prediction Corporate Insolvency and Governance Stock Market Forecasting Methods

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy 2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks 2001Forecasting Bankruptcy More Accurately: A Simple Hazard Model 2008In Search of Distress Risk 2004Bankruptcy Prediction with Industry Effects 2001Bankruptcy prediction for credit risk using neural networks: A survey and new results 2007Using neural network ensembles for bankruptcy prediction and credit scoring

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Details

Year2019

Typearticle

Published2019-05-01

VenueExpert Systems with Applications

ISSN-L0957-4174

Languageen

Citations103

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1016/j.eswa.2019.04.071

openalex_workW2900743306

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2024Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models

2020A two‐stage Bayesian network model for corporate bankruptcy prediction

2022Business Failure Prediction Based on a Cost-Sensitive Extreme Gradient Boosting Machine