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A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem
2 references·16 citing·43 second hop
A threshold-varying artificial neural network approach for classification and its application to bankruptcy prediction problem (2004)A threshold-varying artificial neural net…ZETATM analysis A new model to identify bankruptcy risk of corporations (1977)ZETATM analysis A new model t…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach (2020)Cost-sensitive business failu…Financial distress prediction using the hybrid associative memory with translation (2016)Financial distress prediction…Credit rating with a monotonicity-constrained support vector machine model (2014)Credit rating with a monotoni…An insight into the experimental design for credit risk and corporate bankruptcy prediction systems (2014)An insight into the experimen…The impact of multinationality on firm value: A comparative analysis of machine learning techniques (2013)The impact of multinationalit…Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction (2013)Application of hybrid case-ba…Predicting financial distress of the South Korean manufacturing industries (2012)Predicting financial distress…Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples – Evidence from the Chinese hotel industry (2011)Forecasting business failure:…AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies (2011)AdaBoost ensemble for financi…Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy (2010)Predicting bankruptcy using n…Dynamic financial distress prediction using instance selection for the disposal of concept drift (2010)Dynamic financial distress pr…A hybrid approach based on the combination of variable selection using decision trees and case-based reasoning using the Mahalanobis distance: For bankruptcy prediction (2009)A hybrid approach based on th…An integrative model with subject weight based on neural network learning for bankruptcy prediction (2007)An integrative model with sub…Artificial Neural Network Models for Forecasting Stock Price Index in the Bombay Stock Exchange (2006)Artificial Neural Network Mod…The evaluation of consumer loans using support vector machines (2005)The evaluation of consumer lo…Probabilistic neural networks for the identification of qualified audit opinions (2005)Probabilistic neural networks…Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Hybrid genetic algorithm and fuzzy clustering for bankruptcy prediction (2017)Predicting fraudulent financial reporting using artificial neural network (2017)Bankruptcy Prediction Using Deep Learning Approach Based on Borderline SMOTE (2020)Bankruptcy prediction for credit risk using neural networks: A survey and new results (2001)Bankruptcy prediction for Russian companies: Application of combined classifiers (2013)The performance of corporate financial distress prediction models with features selection guided by domain knowledge and data mining approaches (2015)Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods (2020)Credit rating analysis with support vector machines and neural networks: a market comparative study (2003)Forecasting stock market movement direction with support vector machine (2004)Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)A novel corporate credit rating system based on Student’s-t hidden Markov models (2016)Machine learning models and cost-sensitive decision trees for bond rating prediction (2019)Elements of Credit Rating: A Hybrid Review and Future Research Agenda (2021)Application of support vector machines in financial time series forecasting (2001)Financial time series forecasting using support vector machines (2003)Detecting stock-price manipulation in an emerging market: The case of Turkey (2009)Credit risk evaluation using neural networks: Emotional versus conventional models (2011)How low can you go? 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this work references cited by second hop

References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1977ZETATM analysis A new model to identify bankruptcy risk of corporations1,812 cited

Cited by

  • 2010Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy151 cited
  • 2005The evaluation of consumer loans using support vector machines135 cited
  • 2011AdaBoost ensemble for financial distress prediction: An empirical comparison with data from Chinese listed companies120 cited
  • 2009A hybrid approach based on the combination of variable selection using decision trees and case-based reasoning using the Mahalanobis distance: For bankruptcy prediction116 cited
  • 2011Forecasting business failure: The use of nearest-neighbour support vectors and correcting imbalanced samples – Evidence from the Chinese hotel industry99 cited
  • 2014Credit rating with a monotonicity-constrained support vector machine model89 cited
  • 2016Financial distress prediction using the hybrid associative memory with translation83 cited
  • 2013The impact of multinationality on firm value: A comparative analysis of machine learning techniques82 cited
  • 2006Artificial Neural Network Models for Forecasting Stock Price Index in the Bombay Stock Exchange80 cited
  • 2005Probabilistic neural networks for the identification of qualified audit opinions78 cited
  • 2010

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Dynamic financial distress prediction using instance selection for the disposal of concept drift
76 cited
  • 2014An insight into the experimental design for credit risk and corporate bankruptcy prediction systems75 cited
  • 2013Application of hybrid case-based reasoning for enhanced performance in bankruptcy prediction75 cited
  • 2012Predicting financial distress of the South Korean manufacturing industries75 cited
  • 2007An integrative model with subject weight based on neural network learning for bankruptcy prediction74 cited
  • 2020Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach71 cited