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Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods

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References

2011When Is a Liability Not a Liability? Textual Analysis, Dictionaries, and 10‐Ks6,003 cited
2011Twitter mood predicts the stock market5,204 cited
1966Financial Ratios As Predictors of Failure4,753 cited
2016Textual Analysis in Accounting and Finance: A Survey2,279 cited
2006Bankruptcy prediction in banks and firms via statistical and intelligent techniques – A review1,068 cited
2006Risk reporting: A study of risk disclosures in the annual reports of UK companies774 cited
2018Manager sentiment and stock returns733 cited
2010A comparative assessment of ensemble learning for credit scoring501 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
2016Financial ratios and corporate governance indicators in bankruptcy prediction: A comprehensive study399 cited
2013Predicting financial distress and corporate failure: A review from the state-of-the-art definitions, modeling, sampling, and featuring approaches394 cited
2017Mining corporate annual reports for intelligent detection of financial statement fraud – A comparative study of machine learning methods337 cited
2011Comparative analysis of data mining methods for bankruptcy prediction

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323 cited

2017Decision support from financial disclosures with deep neural networks and transfer learning316 cited

2008Bankruptcy forecasting: An empirical comparison of AdaBoost and neural networks290 cited

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2020Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms37 cited
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2021A Literature Review on Corporate Governance Mechanisms: Past, Present, and Future*34 cited
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