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Predicting financial distress using current reports: A novel deep learning method based on user-response-guided attention
16 references·2 citing·40 second hopsampled
Predicting financial distress using current reports: A novel deep learning method based on user-response-guided attention (2024)Predicting financial distress using curre…The Role of Social Media Content Format and Platform in Users’ Engagement Behavior (2020)The Role of Social Media Cont…Deep learning for detecting financial statement fraud (2020)Deep learning for detecting f…Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection (2020)Bankruptcy prediction for SME…Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting (2019)Class-imbalanced dynamic fina…Leveraging Financial Social Media Data for Corporate Fraud Detection (2018)Leveraging Financial Social M…Deep learning models for bankruptcy prediction using textual disclosures (2018)Deep learning models for bank…Bankruptcy prediction using imaged financial ratios and convolutional neural networks (2018)Bankruptcy prediction using i…Decision support from financial disclosures with deep neural networks and transfer learning (2017)Decision support from financi…Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study (2016)Financial ratios and corporat…Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction (2016)Ensemble boosted trees with s…Beyond likes and tweets: Consumer engagement behavior and movie box office in social media (2016)Beyond likes and tweets: Cons…The Determinants and Consequences of Information Acquisition via EDGAR (2014)The Determinants and Conseque…Prediction of financial distress: An empirical study of listed Chinese companies using data mining (2014)Prediction of financial distr…When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks (2011)When Is a Liability Not a Lia…Comparative analysis of data mining methods for bankruptcy prediction (2011)Comparative analysis of data …In Search of Distress Risk (2008)In Search of Distress RiskPredicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework (2025)Predicting financial distress…Financial distress prediction with annual reports-based deep textual feature extraction: A hybrid approach (2024)Financial distress prediction…Financial Ratios As Predictors of Failure (1966)FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY (1968)Financial Ratios and the Probabilistic Prediction of Bankruptcy (1980)Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering (2022)Risk, Return, and Equilibrium: Empirical Tests (1973)Common risk factors in the returns on stocks and bonds (1993)Disappearing dividends: changing firm characteristics or lower propensity to pay? (2001)In Search of Attention (2011)Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts (2013)Textual Analysis in Accounting and Finance: A Survey (2016)Corporate Ownership Around the World (1999)CatBoost model and artificial intelligence techniques for corporate failure prediction (2021)Financial applications of machine learning: A literature review (2023)Content Analysis: An Introduction to its Methodology. (1984)Co-Integration and Error Correction: Representation, Estimation, and Testing (1987)Users of the world, unite! 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(2021)Cryptocurrency trading: a comprehensive survey (2022)Survey of feature selection and extraction techniques for stock market prediction (2023)Editor's Choice Digesting Anomalies: An Investment ApproachAdvances in prospect theory: Cumulative representation of uncertainty (1992)On Persistence in Mutual Fund Performance (1997)Forecasting Default with the Merton Distance to Default Model (2008)… and the Cross-Section of Expected Returns (2015)An Empirical Evaluation of Accounting Income Numbers (1968)On the Impossibility of Informationally Efficient Markets (1980)A Simple Model of Capital Market Equilibrium with Incomplete Information (1987)Search-based peer firms: Aggregating investor perceptions through internet co-searches (2015)SEC comment letters and firm disclosure (2017)Investor Attention and Stock Returns (2018)A comparative study on base classifiers in ensemble methods for credit scoring (2016)Predicting failure in the U.S. banking sector: An extreme gradient boosting approach (2018)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)
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References

  • 2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks6,003 cited
  • 2008In Search of Distress Risk2,232 cited
  • 2020The Role of Social Media Content Format and Platform in Users’ Engagement Behavior665 cited
  • 2018Deep learning models for bankruptcy prediction using textual disclosures480 cited
  • 2014Prediction of financial distress: An empirical study of listed Chinese companies using data mining479 cited
  • 2016Ensemble boosted trees with synthetic features generation in application to bankruptcy prediction419 cited
  • 2016Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study399 cited
  • 2020Bankruptcy prediction for SMEs using transactional data and two-stage multiobjective feature selection381 cited
  • 2019Class-imbalanced dynamic financial distress prediction based on Adaboost-SVM ensemble combined with SMOTE and time weighting363 cited
  • 2014The Determinants and Consequences of Information Acquisition via EDGAR351 cited
  • 2011Comparative analysis of data mining methods for bankruptcy prediction323 cited
  • 2018Bankruptcy prediction using imaged financial ratios and convolutional neural networks322 cited
  • 2017Decision support from financial disclosures with deep neural networks and transfer learning316 cited
  • 2020Deep learning for detecting financial statement fraud

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291 cited
  • 2016Beyond likes and tweets: Consumer engagement behavior and movie box office in social media259 cited
  • 2018Leveraging Financial Social Media Data for Corporate Fraud Detection239 cited
  • Cited by

    • 2024Financial distress prediction with annual reports-based deep textual feature extraction: A hybrid approach31 cited
    • 2025Predicting financial distress in high-dimensional imbalanced datasets: a multi-heterogeneous self-paced ensemble learning framework30 cited