SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
Financial distress prediction: Regularized sparse-based Random Subspace with ER aggregation rule incorporating textual disclosures
16 references·9 citing·36 second hop
Financial distress prediction: Regularized sparse-based Random Subspace with ER aggregation rule incorporating textual disclosures (2020)Financial distress prediction: Regularize…Deep learning models for bankruptcy prediction using textual disclosures (2018)Deep learning models for bank…Machine learning models and bankruptcy prediction (2017)Machine learning models and b…Prediction of financial distress: An empirical study of listed Chinese companies using data mining (2014)Prediction of financial distr…Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches (2013)Predicting financial distress…Measuring firm performance using financial ratios: A decision tree approach (2013)Measuring firm performance us…Evidential reasoning rule for evidence combination (2013)Evidential reasoning rule for…Management's Tone Change, Post Earnings Announcement Drift and Accruals (2009)Management's Tone Change, Pos…Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Bankruptcy prediction in bank…An application of support vector machines in bankruptcy prediction model (2004)An application of support vec…Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Credit rating analysis with s…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress (1985)Introducing Recursive Partiti…ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS (1985)ASSESSING THE VULNERABILITY T…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Financial Ratios As Predictors of Failure (1966)Financial Ratios As Predictor…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…Predicting financial distress using machine learning approaches: Evidence China (2024)Predicting financial distress…ESG performance and financial distress prediction of energy enterprises (2024)ESG performance and financial…Corporate financial distress prediction using the risk-related information content of annual reports (2024)Corporate financial distress …Financial distress prediction using the Q&A text of online interactive platforms (2023)Financial distress prediction…Predicting and interpreting financial distress using a weighted boosted tree-based tree (2022)Predicting and interpreting f…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…Development and application of a hybrid forecasting framework based on improved extreme learning machine for enterprise financing risk (2022)Development and application o…ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)An application of the cox proportional hazards model to bank failure (1986)A survey of business failures with an emphasis on prediction methods and industrial applications (1996)Predicting corporate financial distress: Reflections on choice-based sample bias (2002)Conditional logit analysis of qualitative choice behavior (1972)The Effect of Audit Quality on Earnings Management* (1998)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)A mathematical theory of evidence (1977)Judgment in Managerial Decision Making (1986)On the dempster-shafer framework and new combination rules (1987)Deng entropy (2016)Multi-sensor data fusion based on the belief divergence measure of evidences and the belief entropy (2018)Uncertainty measure in evidence theory (2020)A Discriminant Analysis of Predictors of Business Failure (1972)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Credit scoring with a data mining approach based on support vector machines (2006)Consumer credit-risk models via machine-learning algorithms (2010)Fuzzy sets (1965)Measuring the efficiency of decision making units (1978)Fuzzy sets (1996)Assessing bank efficiency and performance with operational research and artificial intelligence techniques: A survey (2009)Using artificial neural network models in stock market index prediction (2011)Financial Distress Prediction in an International Context: A Review and Empirical Analysis of Altman's Z‐ Score Model (2016)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Machine Learning in Banking Risk Management: A Literature Review (2019)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)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)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)In Search of Distress Risk (2008)Using neural network ensembles for bankruptcy prediction and credit scoring (2007)Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? (2009)
this work references cited by second hop

References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1980Financial Ratios and the Probabilistic Prediction of Bankruptcy6,005 cited
  • 1966Financial Ratios As Predictors of Failure4,753 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review1,068 cited
  • 2003Credit rating analysis with support vector machines and neural networks: a market comparative study1,017 cited
  • 2017Machine learning models and bankruptcy prediction952 cited
  • 2004An application of support vector machines in bankruptcy prediction model809 cited
  • 1985Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress748 cited
  • 2013Evidential reasoning rule for evidence combination722 cited
  • 2009Management's Tone Change, Post Earnings Announcement Drift and Accruals712 cited
  • 1985ASSESSING THE VULNERABILITY TO FAILURE OF AMERICAN INDUSTRIAL FIRMS: A LOGISTIC ANALYSIS559 cited
  • 2018Deep learning models for bankruptcy prediction using textual disclosures480 cited
  • 2014Prediction of financial distress: An empirical study of listed Chinese companies using data mining479 cited

Only edges whose both ends are imported exist here. Widen the year window, or show the whole map. Back to the work

  • 2013Measuring firm performance using financial ratios: A decision tree approach430 cited
  • 2013Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches394 cited
  • Cited by

    • 2024Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction53 cited
    • 2024Corporate financial distress prediction using the risk-related information content of annual reports47 cited
    • 2022Predicting and interpreting financial distress using a weighted boosted tree-based tree46 cited
    • 2024Predicting financial distress using machine learning approaches: Evidence China40 cited
    • 2024ESG performance and financial distress prediction of energy enterprises40 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
    • 2025Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework30 cited
    • 2022Development and application of a hybrid forecasting framework based on improved extreme learning machine for enterprise financing risk27 cited
    • 2023Financial distress prediction using the Q&A text of online interactive platforms26 cited