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A Robust Deep Learning Model for Financial Distress Prediction
13 references·1 citing·36 second hop
A Robust Deep Learning Model for Financial Distress Prediction (2020)A Robust Deep Learning Model for Financia…Predicting distresses using deep learning of text segments in annual reports (2019)Predicting distresses using d…Financial distress prediction using the hybrid associative memory with translation (2016)Financial distress prediction…Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble (2016)Dynamic financial distress pr…Predicting Financial Distress: A Comparison of Survival Analysis and Decision Tree Techniques (2015)Predicting Financial Distress…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…Bank distress prediction: Empirical evidence from the Gulf Cooperation Council countries (2013)Bank distress prediction: Emp…Predicting financial distress of the South Korean manufacturing industries (2012)Predicting financial distress…Financial distress prediction in banks using Group Method of Data Handling neural network, counter propagation neural network and fuzzy ARTMAP (2010)Financial distress prediction…Failure prediction of dotcom companies using neural network–genetic programming hybrids (2010)Failure prediction of dotcom …Analyzing the financial distress of Chinese public companies using probabilistic neural networks and multivariate discriminate analysis (2007)Analyzing the financial distr…Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters (2005)Bankruptcy prediction using s…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)FINANCIAL RATIOS, DISCRIMINAN…A Comparative Analysis of Machine Learning Classifiers and Ensemble Techniques in Financial Distress Prediction (2020)A Comparative Analysis of Mac…Financial Ratios As Predictors of Failure (1966)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Business failure prediction based on two-stage selective ensemble with manifold learning algorithm and kernel-based fuzzy self-organizing map (2017)Corporate Bankruptcy Prediction Model, a Special Focus on Listed Companies in Kenya (2020)Corporate failure prediction models in the twenty-first century: a review (2020)An application of support vector machines in bankruptcy prediction model (2004)Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)The random subspace binary logit (RSBL) model for bankruptcy prediction (2011)Cash demand forecasting in ATMs by clustering and neural networks (2013)A robust TOPSIS method for decision making problems with hierarchical and non-monotonic criteria (2022)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Ensemble learning with label proportions for bankruptcy prediction (2019)Metaheuristics for rich portfolio optimisation and risk management: Current state and future trends (2019)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)When Is a Liability Not a Liability? 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References

  • 1968FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY14,869 cited
  • 2005Bankruptcy prediction using support vector machine with optimal choice of kernel function parameters872 cited
  • 2014Prediction of financial distress: An empirical study of listed Chinese companies using data mining479 cited
  • 2013Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches394 cited
  • 2016Dynamic financial distress prediction with concept drift based on time weighting combined with Adaboost support vector machine ensemble173 cited
  • 2015Predicting Financial Distress: A Comparison of Survival Analysis and Decision Tree Techniques127 cited
  • 2019Predicting distresses using deep learning of text segments in annual reports103 cited
  • 2016Financial distress prediction using the hybrid associative memory with translation83 cited
  • 2010Financial distress prediction in banks using Group Method of Data Handling neural network, counter propagation neural network and fuzzy ARTMAP81 cited
  • 2012Predicting financial distress of the South Korean manufacturing industries75 cited
  • 2013Bank distress prediction: Empirical evidence from the Gulf Cooperation Council countries73 cited
  • 2007Analyzing the financial distress of Chinese public companies using probabilistic neural networks and multivariate discriminate analysis66 cited
  • 2010Failure prediction of dotcom companies using neural network–genetic programming hybrids

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  • 2020A Comparative Analysis of Machine Learning Classifiers and Ensemble Techniques in Financial Distress Prediction22 cited