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VGU RESEARCH REPOSITORY


Please use this identifier to cite or link to this item: https://epub.vgu.edu.vn/handle/dlibvgu/2008
DC FieldValueLanguage
dc.contributor.authorNguyen Dinh Anh Khoaen_US
dc.date.accessioned2025-10-08T05:07:09Z-
dc.date.available2025-10-08T05:07:09Z-
dc.date.issued2024-12-
dc.identifier.citationIEEEen_US
dc.identifier.urihttps://epub.vgu.edu.vn/handle/dlibvgu/2008-
dc.description.abstractThis study aims to comprehensively examine bankruptcy risk prediction in Vietnam by applying and evaluating the performance of several machine learning models, such as neural networks and tree-based algorithms, alongside advanced feature selection techniques. This is the first study to apply Elastic Net for feature selection in this context, alongside LASSO regression. Utilizing financial data from over 1500 publicly traded companies on Vietnam stock exchanges, the largest dataset in the field to date, the study explores the applicability of predictive modeling in predicting corporate bankruptcy risks and identifying key financial indicators of financial distress. The findings reveal that most models performed very well despite the class imbalance and missing values within the dataset. The study also demonstrates that Elastic Net outperform LASSO in feature selection by retaining more relevant features and maintaining models’ stability, particularly with kNN, SVM, and LSTM. Key financial metrics, including debt ratios, profitability measures, liquidity indicators, and market confidence variables, emerge as significant predictors. Moreover, findings also suggest missing values may carry valuable insights in predicting financial distress. These obtained results have practical implications for credit risk assessment, early warning systems for regulators, and corporate financial planning.en_US
dc.language.isoenen_US
dc.rightsAttribution-NonCommercial 4.0 International*
dc.rights.urihttps://creativecommons.org/licenses/by-nc/4.0/*
dc.subjectbankruptcy risks, machine learning, Elastic Net, LASSO, neural networken_US
dc.titleComprehensive Machine Learning Applications in Corporate Bankruptcy Risk Prediction: Evidence from Vietnamen_US
dc.typeThesisen_US
item.fulltextWith Fulltext-
item.languageiso639-1other-
item.grantfulltextrestricted-
Appears in Collections:Finance & Accounting (FA)
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