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Corporate distress prediction in China: a machine learning approach

Citations

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Cited by:

  1. Yue Qiu & Jiabei He & Zhensong Chen & Yinhong Yao & Yi Qu, 2024. "A novel semisupervised learning method with textual information for financial distress prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2478-2494, November.
  2. Lin, Yu-Cheng & Padliansyah, Roni & Lu, Yu-Hsin & Liu, Wen-Rang, 2025. "Bankruptcy prediction: Integration of convolutional neural networks and explainable artificial intelligence techniques," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
  3. Xiaobo Tang & Shixuan Li & Mingliang Tan & Wenxuan Shi, 2020. "Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 769-787, August.
  4. Asyrofa Rahmi & Chia‐chi Lu & Deron Liang & Ayu Nur Fadilah, 2024. "Splitting long‐term and short‐term financial ratios for improved financial distress prediction: Evidence from Taiwanese public companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2886-2903, November.
  5. Geoffrey Frost & Stewart Jones & Muchen Yu, 2023. "Voluntary Carbon Reporting Prediction: A Machine Learning Approach," Abacus, Accounting Foundation, University of Sydney, vol. 59(4), pages 1116-1166, December.
  6. Ylinen, Mika & Ranta, Mikko, 2025. "Predicting corporate innovation using machine learning and social media data," Technovation, Elsevier, vol. 148(C).
  7. Zhao, Qi & Xu, Weijun & Ji, Yucheng, 2023. "Predicting financial distress of Chinese listed companies using machine learning: To what extent does textual disclosure matter?," International Review of Financial Analysis, Elsevier, vol. 89(C).
  8. Zhang, Zejun & Wang, Zhao & Cai, Lixin, 2025. "Predicting financial fraud in Chinese listed companies: An enterprise portrait and machine learning approach," Pacific-Basin Finance Journal, Elsevier, vol. 90(C).
  9. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
  10. Cynthia W. Cai & Martina K. Linnenluecke & Mauricio Marrone & Abhay K. Singh, 2019. "Machine Learning and Expert Judgement: Analyzing Emerging Topics in Accounting and Finance Research in the Asia–Pacific," Abacus, Accounting Foundation, University of Sydney, vol. 55(4), pages 709-733, December.
  11. Ken Li, 2024. "Liquidity ratios and corporate failures," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 1111-1134, March.
  12. Philip Sinnadurai & Norashikin Ismail & Noor Marini Haji-Abdullah, 2022. "Prediction of corporate recovery in Malaysia," Review of Quantitative Finance and Accounting, Springer, vol. 59(4), pages 1303-1334, November.
  13. Guanping Zhou, 2019. "Financial distress prevention in China: Does gender of board of directors matter?," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 9(6), pages 1-8.
  14. Salman Bahoo & Marco Cucculelli & Xhoana Goga & Jasmine Mondolo, 2024. "Artificial intelligence in Finance: a comprehensive review through bibliometric and content analysis," SN Business & Economics, Springer, vol. 4(2), pages 1-46, February.
  15. Luca Ianni & Gianluca Marullo & Stefania Migliori & Francesco De Luca, 2021. "I modelli predittivi della crisi e dell?insolvenza aziendale. Una systematic review," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(2), pages 127-146.
  16. Jakub Horak & Petr Suler & Jaroslav Kollmann & Jan Marecek, 2020. "Credit Absorption Capacity of Businesses in the Construction Sector of the Czech Republic—Analysis Based on the Difference in Values of EVA Entity and EVA Equity," Sustainability, MDPI, vol. 12(21), pages 1-16, October.
  17. Mohammad Shamsu Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib & Kunpeng Yuan, 2022. "Modeling credit risk with a multi‐stage hybrid model: An alternative statistical approach," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(7), pages 1386-1415, November.
  18. Hui Li & Ting Sun & Jinquan Zhang, 2024. "Prediction of corporate financial distress based on corporate social responsibility: New evidence from DANP, VWP and MEOWA weights methodologies," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(5), pages 4537-4565, December.
  19. Ying Zhou & Xia Lin & Guotai Chi & Peng Jin & Mengtong Li, 2024. "EWT‐SMOTE to improve default prediction performance in imbalanced data: Analysis of Chinese data," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 615-643, April.
  20. Yinghua Song & Minzhe Jiang & Shixuan Li & Shengzhe Zhao, 2024. "Class‐imbalanced financial distress prediction with machine learning: Incorporating financial, management, textual, and social responsibility features into index system," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(3), pages 593-614, April.
  21. Zhensong Chen & Yanxin Liu & Xueyong Liu & Jipeng Dong, 2026. "Forecasting Corporate Bankruptcy Through Class‐Rebalanced Self‐Training Semi‐Constrained Matrix Factorization," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 45(2), pages 530-546, March.
  22. Lin Zhu & Zhihua Zhang & M. James C. Crabbe, 2025. "Exploring small-scale optimization coupling learning approaches for enterprises’ financial health forecasts," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 11(1), pages 1-18, December.
  23. Kunpeng Yuan & Mohammad Zoynul Abedin & Petr Hajek, 2025. "An Ensemble Model Minimising Misjudgment Cost: Empirical Evidence From Chinese Listed Companies," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 30(4), pages 3875-3900, October.
  24. Dawen Yan & Guotai Chi & Kin Keung Lai, 2020. "Financial Distress Prediction and Feature Selection in Multiple Periods by Lassoing Unconstrained Distributed Lag Non-linear Models," Mathematics, MDPI, vol. 8(8), pages 1-27, August.
  25. Mika Ylinen & Mikko Ranta, 2024. "Employer ratings in social media and firm performance: Evidence from an explainable machine learning approach," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 64(1), pages 247-276, March.
  26. Liu, Wanan & Zou, Yao & Liu, Baokang & Tao, Jiacheng & Lan, Xingyu & Xia, Meng, 2026. "Explainable adaptive ensemble learning with imbalance mitigation for manufacturing sector financial risk warning," Chaos, Solitons & Fractals, Elsevier, vol. 202(P2).
  27. Stewart Jones & Nurul Alam, 2019. "A machine learning analysis of citation impact among selected Pacific Basin journals," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 59(4), pages 2509-2552, December.
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