Can earnings management information improve bankruptcy prediction models?

DOI10.1007/S10479-021-04183-0zbMath1478.62315OpenAlexW3179653373MaRDI QIDQ2070698

Eric Séverin, David Veganzones

Publication date: 24 January 2022

Published in: Annals of Operations Research (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1007/s10479-021-04183-0

zbMATH Keywords

corporate financeearnings managementbankruptcy prediction models

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Statistical methods; risk measures (91G70) Learning and adaptive systems in artificial intelligence (68T05) Management decision making, including multiple objectives (90B50) Credit risk (91G40)

Cites Work

• Bankruptcy prediction using terminal failure processes
• Firm credit risk evaluation: a series two-stage DEA modeling framework
• Forecasting financial failure using a Kohonen map: a comparative study to improve model stability over time
• Forecasting bankruptcy using biclustering and neural network-based ensembles
• An out-of-sample evaluation framework for DEA with application in bankruptcy prediction
• 10.1162/153244303322753616
• Comparative analysis of artificial neural network models: Application in bankruptcy prediction

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