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Deep Learning-Based Model for Financial Distress Prediction · Study

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ArticleDeep Learning-Based Model for Financial Distress Prediction

Mohamed Elhoseny2022

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Articlebronze2022

Deep Learning-Based Model for Financial Distress Prediction

Mohamed Elhoseny · Noura Metawa · Gábor Sztanó · Ibrahim M. El‐Hasnony

123 citations·0/0 files stored·Annals of Operations Research

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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 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters 2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction 2013Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches 2019Circular economy transition in Italy. Achievements, perspectives and constraints 2018Forecasting stock market crisis events using deep and statistical machine learning techniques 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble

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2024Machine learning techniques in bankruptcy prediction: A systematic literature review 2024Artificial Intelligence Techniques for Bankruptcy Prediction of Tunisian Companies: An Application of Machine Learning and Deep Learning-Based Models 2023RETRACTED: The role of feature importance in predicting corporate financial distress in pre and post COVID periods: Evidence from China

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Details

Year2022

Typearticle

Published2022-05-25

VenueAnnals of Operations Research

ISSN-L0254-5330

Languageen

Citations123

Files0 public / 0

ShelfFinancial Distress and Bankruptcy Prediction

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doi10.1007/s10479-022-04766-5

openalex_workW4281490929

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2022

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