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Deep learning models for bankruptcy prediction using textual disclosures · Study

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Deep learning models for bankruptcy prediction using textual disclosures

Feng Mai, Shaonan Tian, Chihoon Lee, Ling Ma

2018-10-20articleEuropean Journal of Operational Research480 citationsclosed

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

Abstract

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Citations in this library

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References

1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY

2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks

1966Financial Ratios As Predictors of Failure

2008Annual report readability, current earnings, and earnings persistence

2001Forecasting Bankruptcy More Accurately: A Simple Hazard Model

2008In Search of Distress Risk

2004Assessing the Probability of Bankruptcy

2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review

Cited by

2021CatBoost model and artificial intelligence techniques for corporate failure prediction

2023Financial applications of machine learning: A literature review

2022Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering

2021The effect of green energy, global environmental indexes, and stock markets in predicting oil price crashes: Evidence from explainable machine learning

2020Predicting the citation counts of individual papers via a BP neural network

2022Assessing credit risk of commercial customers using hybrid machine learning algorithms

2020Bankruptcy Prediction Using Deep Learning Approach Based on Borderline SMOTE

2021The value of text for small business default prediction: A Deep Learning approach

Details

Year2018

Typearticle

VenueEuropean Journal of Operational Research

Languageen

Files0 public / 0

Identifiers

doi10.1016/j.ejor.2018.10.024

openalex_workW2897596136

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