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Using Machine Learning, Neural Networks, and Statistics to Predict Corporate Bankruptcy
3 references·16 citing·34 second hop
Using Machine Learning, Neural Networks, and Statistics to Predict Corporate Bankruptcy (1997)Using Machine Learning, Neural Networks, …Forecasting with neural networks (1993)Forecasting with neural netwo…Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Managerial Applications of Ne…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…Predicting financial distress through ownership pattern: dynamics of financial resilience of Bangladesh (2024)Predicting financial distress…Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends (2024)Predicting Construction Compa…Gated recurrent unit network: A promising approach to corporate default prediction (2024)Gated recurrent unit network:…Forecasting financial distress in listed Chinese construction firms: leveraging ensemble learning and non-financial variables (2024)Forecasting financial distres…Corporate governance and financial distress: lessons learned from an unconventional approach (2022)Corporate governance and fina…Predicting Firms’ Financial Distress: An Empirical Analysis Using the F-Score Model (2021)Predicting Firms’ Financial D…Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting (2021)Predicting Firm-Level Bankrup…Comparing the Performance of Deep Learning Methods to Predict Companies’ Financial Failure (2021)Comparing the Performance of …Review of Corporate Governance Practices and Financial Distress Prediction (2018)Review of Corporate Governanc…Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data (2014)Self-Adaptive MOEA Feature Se…A Grey System Theory‐Based Default Prediction Model for Construction Firms (2014)A Grey System Theory‐Based De…Įmonių bankroto prognozavimo modelių tinkamumo nustatymas (2006)Įmonių bankroto prognozavimo …Company failure in South Africa: Classification and prediction by means of recursive partitioning (2006)Company failure in South Afri…Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline (2005)Bankruptcy prediction: the in…Predicting Corporate Bankruptcy: whither do we stand? 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this work references cited by second hop

References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 1992Managerial Applications of Neural Networks: The Case of Bank Failure Predictions1,121 cited
  • 1993Forecasting with neural networks432 cited

Cited by

  • 2021Comparing the Performance of Deep Learning Methods to Predict Companies’ Financial Failure51 cited
  • 2021Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting51 cited
  • 2005Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline46 cited
  • 2021Predicting Firms’ Financial Distress: An Empirical Analysis Using the F-Score Model43 cited
  • 2022Corporate governance and financial distress: lessons learned from an unconventional approach40 cited
  • 2004Predicting Corporate Bankruptcy: whither do we stand?32 cited
  • 2006Company failure in South Africa: Classification and prediction by means of recursive partitioning31 cited
  • 2024Predicting Construction Company Insolvent Failure: A Scientometric Analysis and Qualitative Review of Research Trends29 cited
  • 2014A Grey System Theory‐Based Default Prediction Model for Construction Firms25 cited
  • 2004Multiple Criteria Linear Programming Data Mining Approach: An Application for Bankruptcy Prediction21 cited

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

  • 2006Įmonių bankroto prognozavimo modelių tinkamumo nustatymas20 cited
  • 2024Predicting financial distress through ownership pattern: dynamics of financial resilience of Bangladesh20 cited
  • 2018Review of Corporate Governance Practices and Financial Distress Prediction18 cited
  • 2024Forecasting financial distress in listed Chinese construction firms: leveraging ensemble learning and non-financial variables17 cited
  • 2024Gated recurrent unit network: A promising approach to corporate default prediction17 cited
  • 2014Self-Adaptive MOEA Feature Selection for Classification of Bankruptcy Prediction Data17 cited