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Designing topological data to forecast bankruptcy using convolutional neural networks
16 references·1 citing·45 second hopsampled
Designing topological data to forecast bankruptcy using convolutional neural networks (2022)Designing topological data to forecast ba…Forecasting corporate failure using ensemble of self-organizing neural networks (2020)Forecasting corporate failure…Deep learning for financial applications : A survey (2020)Deep learning for financial a…Deep learning in business analytics and operations research: Models, applications and managerial implications (2019)Deep learning in business ana…Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting (2019)Can deep learning predict ris…Firm failure processes and components of failure risk: An analysis of European bankrupt firms (2018)Firm failure processes and co…Failure pattern-based ensembles applied to bankruptcy forecasting (2018)Failure pattern-based ensembl…Bankruptcy prediction using imaged financial ratios and convolutional neural networks (2018)Bankruptcy prediction using i…Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach (2018)Algorithmic financial trading…Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations (2017)Intraday prediction of Borsa …Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study (2016)Financial ratios and corporat…A two-stage classification technique for bankruptcy prediction (2016)A two-stage classification te…Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time (2012)Forecasting financial failure…Model combination for credit risk assessment: A stacked generalization approach (2006)Model combination for credit …Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review (2006)Bankruptcy prediction in bank…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…Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction (2000)Comparative Analysis of Artif…The dilemma of accuracy in bankruptcy prediction: a new approach using explainable AI techniques to predict corporate crises (2024)The dilemma of accuracy in ba…FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Managerial Applications of Neural Networks: The Case of Bank Failure Predictions (1992)Predicting Restaurant Bankruptcy: A Logit Model in Comparison with a Discriminant Model (2006)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)Early warning models against bankruptcy risk for Central European and Latin American enterprises (2012)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)Corporate Ownership Around the World (1999)Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection (2020)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Financial applications of machine learning: A literature review (2023)Methodological Issues Related to the Estimation of Financial Distress Prediction Models (1984)Banking credit worthiness: Evaluating the complex relationships (2018)No more black boxes! Explaining the predictions of a machine learning XGBoost classifier algorithm in business failure (2022)Surveying stock market forecasting techniques – Part II: Soft computing methods (2008)Predicting direction of stock price index movement using artificial neural networks and support vector machines: The sample of the Istanbul Stock Exchange (2010)A LSTM-based method for stock returns prediction: A case study of China stock market (2015)Financial time series forecasting with deep learning : A systematic literature review: 2005–2019 (2020)Forecasting Stock Prices Using a Hybrid Deep Learning Model Integrating Attention Mechanism, Multi-Layer Perceptron, and Bidirectional Long-Short Term Memory Neural Network (2020)Prediction-Based Portfolio Optimization Models Using Deep Neural Networks (2020)Time Series Analysis, Forecasting and Control. (1971)Time Series Analysis: Forecasting and Control. (1978)Deep learning with long short-term memory networks for financial market predictions (2017)A novel graph convolutional feature based convolutional neural network for stock trend prediction (2020)Portfolio optimization with return prediction using deep learning and machine learning (2020)Stock price prediction using deep learning and frequency decomposition (2020)Business Intelligence and Analytics: From Big Data to Big Impact (2012)Benchmarking state-of-the-art classification algorithms for credit scoring: An update of research (2015)Deep learning for detecting financial statement fraud (2020)Artificial intelligence applications in supply chain management (2021)Deep learning for credit scoring: Do or don’t? (2021)Proceedings of the International Joint Conference on Neural Networks, 2003. (2003)Deep learning in finance and banking: A literature review and classification (2020)How are reinforcement learning and deep learning algorithms used for big data based decision making in financial industries–A review and research agenda (2022)Textual Analysis in Accounting and Finance: A Survey (2016)Fusion in stock market prediction: A decade survey on the necessity, recent developments, and potential future directions (2020)Generación de series de tiempo financieras sintéticas para "data augmentation" usando redes neuronales generativas adversarias (GAN) (2021)Forex exchange rate forecasting using deep recurrent neural networks (2020)Forecasting mid-price movement of Bitcoin futures using machine learning (2021)LSTM-based Deep Learning Model for Stock Prediction and Predictive Optimization Model (2021)
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References

  • 2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review1,068 cited
  • 2020Deep learning for financial applications : A survey550 cited
  • 2018Algorithmic financial trading with deep convolutional neural networks: Time series to image conversion approach433 cited
  • 2016Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study399 cited
  • 2019Deep learning in business analytics and operations research: Models, applications and managerial implications391 cited
  • 2018Bankruptcy prediction using imaged financial ratios and convolutional neural networks322 cited
  • 2017Intraday prediction of Borsa Istanbul using convolutional neural networks and feature correlations188 cited
  • 2016A two-stage classification technique for bankruptcy prediction142 cited
  • 2000Comparative Analysis of Artificial Neural Network Models: Application in Bankruptcy Prediction137 cited
  • 2019Can deep learning predict risky retail investors? A case study in financial risk behavior forecasting120 cited
  • 2012Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time86 cited
  • 2018Firm failure processes and components of failure risk: An analysis of European bankrupt firms81 cited
  • 2018Failure pattern-based ensembles applied to bankruptcy forecasting65 cited

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2006
Model combination for credit risk assessment: A stacked generalization approach
61 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
  • 2020Forecasting corporate failure using ensemble of self-organizing neural networks45 cited
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    • 2024The dilemma of accuracy in bankruptcy prediction: a new approach using explainable AI techniques to predict corporate crises19 cited