SZodixStudyAcademic Library
ShelvesOpen access
Study · an open academic library·Metadata from OpenAlex (CC0)·Shelves·OpenAlex metadata, de-duplicated
A New Perspective of Performance Comparison among Machine Learning Algorithms for Financial Distress Prediction
16 references·16 citing·27 second hopsampled
A New Perspective of Performance Comparison among Machine Learning Algorithms for Financial Distress Prediction (2019)A New Perspective of Performance Comparis…Predicting failure in the U.S. banking sector: An extreme gradient boosting approach (2018)Predicting failure in the U.S…Machine learning models and bankruptcy prediction (2017)Machine learning models and b…A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring (2017)A boosted decision tree appro…Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Ensemble boosted trees with s…Computational Intelligence and Financial Markets: A Survey and Future Directions (2016)Computational Intelligence an…Using neural networks and data mining techniques for the financial distress prediction model (2008)Using neural networks and dat…Measuring Organizational Performance: Metrics for Entrepreneurship and Strategic Management Research (2007)Measuring Organizational Perf…Forecasting financial condition of Chinese listed companies based on support vector machine (2007)Forecasting financial conditi…Credit Scoring and Its Applications (2002)Credit Scoring and Its Applic…An International Survey of Business Failure Classification Models (1997)An International Survey of Bu…Multivariate Normality and Forecasting of Business Bankruptcy (1987)Multivariate Normality and Fo…Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Methodological Issues Related…Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Financial Ratios and the Prob…A Discriminant Analysis of Predictors of Business Failure (1972)A Discriminant Analysis of Pr…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…Survey, classification and critical analysis of the literature on corporate bankruptcy and financial distress prediction (2024)Survey, classification and cr…Predicting financial performance for listed companies in Thailand during the transition period: A class-based approach using logistic regression and random forest algorithm (2023)Predicting financial performa…Mining semantic features in patent text for financial distress prediction (2023)Mining semantic features in p…Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation (2023)Improved credit risk predicti…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…Impacts of crisis on SME bankruptcy prediction models’ performance (2022)Impacts of crisis on SME bank…Deep Learning-Based Model for Financial Distress Prediction (2022)Deep Learning-Based Model for…A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain (2022)A novel ensemble feature sele…Multi-class financial distress prediction based on support vector machines integrated with the decomposition and fusion methods (2021)Multi-class financial distres…Imbalanced credit risk prediction based on SMOTE and multi-kernel FCM improved by particle swarm optimization (2021)Imbalanced credit risk predic…Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress (2021)Financial Information Asymmet…Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators (2021)Feature selection and deep ne…A revision of Altman Z-Score model and a comparative analysis of Turkish companies' financial distress prediction (2021)A revision of Altman Z-Score …Tax Default Prediction Using Feature Transformation-Based Machine Learning (2020)Tax Default Prediction Using …Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange (2020)Predicting next day direction…Limited-dependent and qualitative variables in econometrics (1983)Forecasting Bankruptcy More Accurately: A Simple Hazard Model (2001)Do Managers Withhold Bad News? (2008)In Search of Distress Risk (2008)Conditional logit analysis of qualitative choice behavior (1972)The Effect of Audit Quality on Earnings Management* (1998)PORTFOLIO SELECTION* (1952)The Behavior of Stock-Market Prices (1965)Application of support vector machines in financial time series forecasting (2001)Literature review: Machine learning techniques applied to financial market prediction (2019)Machine learning in energy economics and finance: A review (2019)Deep Learning for Stock Market Prediction (2020)A Decision-Theoretic Generalization of On-Line Learning and an Application to Boosting (1997)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Statistical and machine learning models in credit scoring: A systematic literature survey (2020)Forecasting gold price with the XGBoost algorithm and SHAP interaction values (2021)Recent developments in consumer credit risk assessment (2007)A new hybrid classification algorithm for customer churn prediction based on logistic regression and decision trees (2018)Machine learning for credit scoring: Improving logistic regression with non-linear decision-tree effects (2021)The robust beauty of improper linear models in decision making. (1979)A neural network model for bankruptcy prediction (1990)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Managerial incentives and risk-taking☆ (2005)How does financial reporting quality relate to investment efficiency? (2009)A comparative study on base classifiers in ensemble methods for credit scoring (2016)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Machine Learning in Banking Risk Management: A Literature Review (2019)
this work references cited by second hop· second hop is a sample of the most-cited connections

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
  • 1984Methodological Issues Related to the Estimation of Financial Distress Prediction Models2,889 cited
  • 1972A Discriminant Analysis of Predictors of Business Failure1,168 cited
  • 2017Machine learning models and bankruptcy prediction952 cited
  • 2017A boosted decision tree approach using Bayesian hyper-parameter optimization for credit scoring770 cited
  • 2002Credit Scoring and Its Applications669 cited
  • 2016Computational Intelligence and Financial Markets: A Survey and Future Directions592 cited
  • 2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction419 cited
  • 1987Multivariate Normality and Forecasting of Business Bankruptcy354 cited
  • 2018Predicting failure in the U.S. banking sector: An extreme gradient boosting approach295 cited
  • 2008Using neural networks and data mining techniques for the financial distress prediction model283 cited
  • 2007Forecasting financial condition of Chinese listed companies based on support vector machine246 cited

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

1997
An International Survey of Business Failure Classification Models
246 cited
  • 2007Measuring Organizational Performance: Metrics for Entrepreneurship and Strategic Management Research244 cited
  • Cited by

    • 2021Multi-class financial distress prediction based on support vector machines integrated with the decomposition and fusion methods144 cited
    • 2022Deep Learning-Based Model for Financial Distress Prediction123 cited
    • 2022A novel ensemble feature selection method by integrating multiple ranking information combined with an SVM ensemble model for enterprise credit risk prediction in the supply chain95 cited
    • 2021Feature selection and deep neural networks for stock price direction forecasting using technical analysis indicators80 cited
    • 2020Predicting next day direction of stock price movement using machine learning methods with persistent homology: Evidence from Kuala Lumpur Stock Exchange74 cited
    • 2021A revision of Altman Z-Score model and a comparative analysis of Turkish companies' financial distress prediction64 cited
    • 2020Tax Default Prediction Using Feature Transformation-Based Machine Learning62 cited
    • 2021Financial Information Asymmetry: Using Deep Learning Algorithms to Predict Financial Distress61 cited
    • 2022Systematic Review of Financial Distress Identification using Artificial Intelligence Methods59 cited
    • 2021Imbalanced credit risk prediction based on SMOTE and multi-kernel FCM improved by particle swarm optimization57 cited
    • 2022Impacts of crisis on SME bankruptcy prediction models’ performance56 cited
    • 2023Improved credit risk prediction based on an integrated graph representation learning approach with graph transformation53 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
    • 2023Mining semantic features in patent text for financial distress prediction46 cited
    • 2023Predicting financial performance for listed companies in Thailand during the transition period: A class-based approach using logistic regression and random forest algorithm46 cited