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A dynamic financial distress forecast model with multiple forecast results under unbalanced data environment
13 references·13 citing·27 second hop
A dynamic financial distress forecast model with multiple forecast results under unbalanced data environment (2019)A dynamic financial distress forecast mod…Financial distress prediction: The case of French small and medium-sized firms (2017)Financial distress prediction…Random forests-based early warning system for bank failures (2016)Random forests-based early wa…Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble (2016)Dynamic financial distress pr…Bankruptcy prediction using terminal failure processes (2014)Bankruptcy prediction using t…Corporate financial distress and bankruptcy : predict and avoid bankruptcy, analyze and invest in distressed debt (2005)Corporate financial distress …Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction using s…Neural network prediction analysis: The bankruptcy case (1996)Neural network prediction ana…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…A neural network model for bankruptcy prediction (1990)A neural network model for ba…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)ZETATM analysis A new model t…Early warning of bank failure (1977)Early warning of bank failureFINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework (2025)Predicting financial distress…Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction (2024)Survey, classification and cr…Imbalanced customer churn classification using a new multi-strategy collaborative processing method (2024)Imbalanced customer churn cla…Cost-sensitive stacking ensemble learning for company financial distress prediction (2024)Cost-sensitive stacking ensem…Financial distress prediction using the Q&A text of online interactive platforms (2023)Financial distress prediction…Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system (2023)Class‐imbalanced financial di…A Hybrid Approach for Predicting Corporate Financial Risk: Integrating SMOTE-ENN and NGBoost (2023)A Hybrid Approach for Predict…Systematic Review of Financial Distress Identification using Artificial Intelligence Methods (2022)Systematic Review of Financia…Predicting and interpreting financial distress using a weighted boosted tree-based tree (2022)Predicting and interpreting f…Is the Financial Report Quality Important in the Default Prediction? SME Portuguese Construction Sector Evidence (2022)Is the Financial Report Quali…Enterprise credit risk prediction using supply chain information: A decision tree ensemble model based on the differential sampling rate, Synthetic Minority Oversampling Technique and AdaBoost (2022)Enterprise credit risk predic…Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress (2021)Financial Information Asymmet…Financial Distress Prediction and Feature Selection in Multiple Periods by Lassoing Unconstrained Distributed Lag Non-linear Models (2020)Financial Distress Prediction…Financial Ratios As Predictors of Failure (1966)Conditional logit analysis of qualitative choice behavior (1972)The Effect of Audit Quality on Earnings Management* (1998)Positive Accounting Theory (1985)Designing a neural network for forecasting financial and economic time series (1996)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)A hybrid stock price index forecasting model based on variational mode decomposition and LSTM network (2020)Adaptive stock trading strategies with deep reinforcement learning methods (2020)Combining corporate governance indicators with stacking ensembles for financial distress prediction (2020)Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Credit risk measurement: Developments over the last 20 years (1997)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)Forecasting with artificial neural networks: (1998)Neural network credit scoring models (2000)Application of data mining techniques in customer relationship management: A literature review and classification (2008)Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Consumer credit-risk models via machine-learning algorithms (2010)A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? 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References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy6,005 cited
  • 1977ZETATM analysis A new model to identify bankruptcy risk of corporations1,812 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 1977Early warning of bank failure960 cited
  • 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters872 cited
  • 1990A neural network model for bankruptcy prediction853 cited
  • 2005Corporate financial distress and bankruptcy : predict and avoid bankruptcy, analyze and invest in distressed debt371 cited
  • 2017Financial distress prediction: The case of French small and medium-sized firms220 cited
  • 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble173 cited
  • 2014Bankruptcy prediction using terminal failure processes152 cited
  • 1996Neural network prediction analysis: The bankruptcy case149 cited
  • 2016Random forests-based early warning system for bank failures95 cited

Cited by

  • 2021Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress

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61 cited
  • 2022Systematic Review of Financial Distress Identification using Artificial Intelligence Methods59 cited
  • 2024Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction53 cited
  • 2022Predicting and interpreting financial distress using a weighted boosted tree-based tree46 cited
  • 2022Enterprise credit risk prediction using supply chain information: A decision tree ensemble model based on the differential sampling rate, Synthetic Minority Oversampling Technique and AdaBoost40 cited
  • 2024Cost-sensitive stacking ensemble learning for company financial distress prediction34 cited
  • 2020Financial Distress Prediction and Feature Selection in Multiple Periods by Lassoing Unconstrained Distributed Lag Non-linear Models34 cited
  • 2024Imbalanced customer churn classification using a new multi-strategy collaborative processing method33 cited
  • 2025Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework30 cited
  • 2023Financial distress prediction using the Q&A text of online interactive platforms26 cited
  • 2023A Hybrid Approach for Predicting Corporate Financial Risk: Integrating SMOTE-ENN and NGBoost26 cited
  • 2022Is the Financial Report Quality Important in the Default Prediction? SME Portuguese Construction Sector Evidence24 cited
  • 2023Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system20 cited