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Variable selection and corporate bankruptcy forecasts

Citations

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Cited by:

  1. Eduard Sariev & Guido Germano, 2020. "Bayesian regularized artificial neural networks for the estimation of the probability of default," Quantitative Finance, Taylor & Francis Journals, vol. 20(2), pages 311-328, February.
  2. Li, Chunyu & Lou, Chenxin & Luo, Dan & Xing, Kai, 2021. "Chinese corporate distress prediction using LASSO: The role of earnings management," International Review of Financial Analysis, Elsevier, vol. 76(C).
  3. Fallahpour, Saeid & Lakvan, Eisa Norouzian & Zadeh, Mohammad Hendijani, 2017. "Using an ensemble classifier based on sequential floating forward selection for financial distress prediction problem," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 159-167.
  4. Xavier Brédart & Eric Séverin & David Veganzones, 2021. "Human resources and corporate failure prediction modeling: Evidence from Belgium," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 40(7), pages 1325-1341, November.
  5. Elyasiani, Elyas & Movaghari, Hadi, 2022. "Determinants of corporate cash holdings: An application of a robust variable selection technique," International Review of Economics & Finance, Elsevier, vol. 80(C), pages 967-993.
  6. Ben Jabeur, Sami, 2017. "Bankruptcy prediction using Partial Least Squares Logistic Regression," Journal of Retailing and Consumer Services, Elsevier, vol. 36(C), pages 197-202.
  7. Edward I. Altman & Marco Balzano & Alessandro Giannozzi & Stjepan Srhoj, 2023. "Revisiting SME default predictors: The Omega Score," Journal of Small Business Management, Taylor & Francis Journals, vol. 61(6), pages 2383-2417, November.
  8. Giovanni Bonaccolto & Massimiliano Caporin & Sandra Paterlini, 2018. "Asset allocation strategies based on penalized quantile regression," Computational Management Science, Springer, vol. 15(1), pages 1-32, January.
  9. Modina, Michele & Pietrovito, Filomena & Gallucci, Carmen & Formisano, Vincenzo, 2023. "Predicting SMEs’ default risk: Evidence from bank-firm relationship data," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 254-268.
  10. Basim Alzugaiby & Jairaj Gupta & Andrew Mullineux & Rizwan Ahmed, 2021. "Relevance of size in predicting bank failures," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 26(3), pages 3504-3543, July.
  11. Eduard Sariev & Guido Germano, 2019. "An innovative feature selection method for support vector machines and its test on the estimation of the credit risk of default," Review of Financial Economics, John Wiley & Sons, vol. 37(3), pages 404-427, July.
  12. O’Sullivan, Conall & Papavassiliou, Vassilios G. & Wafula, Ronald Wekesa & Boubaker, Sabri, 2024. "New insights into liquidity resiliency," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 90(C).
  13. Ho-Chang Chae, 2024. "In search of gazelles: machine learning prediction for Korean high-growth firms," Small Business Economics, Springer, vol. 62(1), pages 243-284, January.
  14. Bai, Qing & Tian, Shaonan, 2020. "Innovate or die: Corporate innovation and bankruptcy forecasts," Journal of Empirical Finance, Elsevier, vol. 59(C), pages 88-108.
  15. Sigrist, Fabio & Hirnschall, Christoph, 2019. "Grabit: Gradient tree-boosted Tobit models for default prediction," Journal of Banking & Finance, Elsevier, vol. 102(C), pages 177-192.
  16. 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.
  17. Quesenberry, Keith A. & Coolsen, Michael K., 2019. "Drama Goes Viral: Effects of Story Development on Shares and Views of Online Advertising Videos," Journal of Interactive Marketing, Elsevier, vol. 48(C), pages 1-16.
  18. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2022. "Corporate Bankruptcy Prediction Using Machine Learning Methodologies with a Focus on Sequential Data," Computational Economics, Springer;Society for Computational Economics, vol. 59(3), pages 1231-1249, March.
  19. Alex Coad & Stjepan Srhoj, 2020. "Catching Gazelles with a Lasso: Big data techniques for the prediction of high-growth firms," Small Business Economics, Springer, vol. 55(3), pages 541-565, October.
  20. Sigrist, Fabio & Leuenberger, Nicola, 2023. "Machine learning for corporate default risk: Multi-period prediction, frailty correlation, loan portfolios, and tail probabilities," European Journal of Operational Research, Elsevier, vol. 305(3), pages 1390-1406.
  21. Elena Gregova & Katarina Valaskova & Peter Adamko & Milos Tumpach & Jaroslav Jaros, 2020. "Predicting Financial Distress of Slovak Enterprises: Comparison of Selected Traditional and Learning Algorithms Methods," Sustainability, MDPI, vol. 12(10), pages 1-17, May.
  22. Marui Du & Yue Ma & Zuoquan Zhang, 2021. "A Meta Path Based Evaluation Method for Enterprise Credit Risk," Papers 2110.11594, arXiv.org, revised May 2022.
  23. Gianfranco Lombardo & Mattia Pellegrino & George Adosoglou & Stefano Cagnoni & Panos M. Pardalos & Agostino Poggi, 2022. "Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks," Future Internet, MDPI, vol. 14(8), pages 1-23, August.
  24. Tian, Shaonan & Yu, Yan, 2017. "Financial ratios and bankruptcy predictions: An international evidence," International Review of Economics & Finance, Elsevier, vol. 51(C), pages 510-526.
  25. Xing, Kai & Luo, Dan & Liu, Lanlan, 2023. "Macroeconomic conditions, corporate default, and default clustering," Economic Modelling, Elsevier, vol. 118(C).
  26. Croux, Christophe & Jagtiani, Julapa & Korivi, Tarunsai & Vulanovic, Milos, 2020. "Important factors determining Fintech loan default: Evidence from a lendingclub consumer platform," Journal of Economic Behavior & Organization, Elsevier, vol. 173(C), pages 270-296.
  27. Akarsh Kainth & Ranik Raaen Wahlstrøm, 2021. "Do IFRS Promote Transparency? Evidence from the Bankruptcy Prediction of Privately Held Swedish and Norwegian Companies," JRFM, MDPI, vol. 14(3), pages 1-15, March.
  28. Yi Cao & Xiaoquan Liu & Jia Zhai & Shan Hua, 2022. "A two‐stage Bayesian network model for corporate bankruptcy prediction," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(1), pages 455-472, January.
  29. Dong, Manh Cuong & Tian, Shaonan & Chen, Cathy W.S., 2018. "Predicting failure risk using financial ratios: Quantile hazard model approach," The North American Journal of Economics and Finance, Elsevier, vol. 44(C), pages 204-220.
  30. Alberto Tron & Maurizio Dallocchio & Salvatore Ferri & Federico Colantoni, 2023. "Corporate governance and financial distress: lessons learned from an unconventional approach," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(2), pages 425-456, June.
  31. Lenka Papíková & Mário Papík, 2022. "Effects of classification, feature selection, and resampling methods on bankruptcy prediction of small and medium‐sized enterprises," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 29(4), pages 254-281, October.
  32. ARATA Yoshiyuki, 2018. "Bankruptcy propagation on a customer-supplier network: An empirical analysis in Japan," Discussion papers 18040, Research Institute of Economy, Trade and Industry (RIETI).
  33. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2020. "Corporate Default Predictions Using Machine Learning: Literature Review," Sustainability, MDPI, vol. 12(16), pages 1-11, August.
  34. Zhou, Ying & Shen, Long & Ballester, Laura, 2023. "A two-stage credit scoring model based on random forest: Evidence from Chinese small firms," International Review of Financial Analysis, Elsevier, vol. 89(C).
  35. Serrano-Cinca, Carlos & Gutiérrez-Nieto, Begoña & Bernate-Valbuena, Martha, 2019. "The use of accounting anomalies indicators to predict business failure," European Management Journal, Elsevier, vol. 37(3), pages 353-375.
  36. Duarte Trigueiros, 2019. "Improving the effectiveness of predictors in accounting-based models," Journal of Applied Accounting Research, Emerald Group Publishing Limited, vol. 20(2), pages 207-226, June.
  37. Caglayan, Mustafa & Pham, Tho & Talavera, Oleksandr & Xiong, Xiong, 2020. "Asset mispricing in peer-to-peer loan secondary markets," Journal of Corporate Finance, Elsevier, vol. 65(C).
  38. Wei Li & Wolfgang Karl Hardle & Stefan Lessmann, 2022. "A Data-driven Case-based Reasoning in Bankruptcy Prediction," Papers 2211.00921, arXiv.org.
  39. Hoang, Daniel & Wiegratz, Kevin, 2022. "Machine learning methods in finance: Recent applications and prospects," Working Paper Series in Economics 158, Karlsruhe Institute of Technology (KIT), Department of Economics and Management.
  40. Ahmad Hammami & Mohammad Hendijani Zadeh, 2022. "Predicting earnings management through machine learning ensemble classifiers," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(8), pages 1639-1660, December.
  41. Katarina Valaskova & Tomas Kliestik & Lucia Svabova & Peter Adamko, 2018. "Financial Risk Measurement and Prediction Modelling for Sustainable Development of Business Entities Using Regression Analysis," Sustainability, MDPI, vol. 10(7), pages 1-15, June.
  42. Youssef Zizi & Mohamed Oudgou & Abdeslam El Moudden, 2020. "Determinants and Predictors of SMEs’ Financial Failure: A Logistic Regression Approach," Risks, MDPI, vol. 8(4), pages 1-21, October.
  43. Koresh Galil & Margalit Samuel & Offer Moshe Shapir & Wolf Wagner, 2023. "Bailouts and the modeling of bank distress," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 46(1), pages 7-30, February.
  44. Nazemi, Abdolreza & Fabozzi, Frank J., 2018. "Macroeconomic variable selection for creditor recovery rates," Journal of Banking & Finance, Elsevier, vol. 89(C), pages 14-25.
  45. Sohrabi, Narges & Movaghari, Hadi, 2020. "Reliable factors of Capital structure: Stability selection approach," The Quarterly Review of Economics and Finance, Elsevier, vol. 77(C), pages 296-310.
  46. Wilms, Ines & Rombouts, Jeroen & Croux, Christophe, 2021. "Multivariate volatility forecasts for stock market indices," International Journal of Forecasting, Elsevier, vol. 37(2), pages 484-499.
  47. Katarina Valaskova & Dominika Gajdosikova & Jaroslav Belas, 2023. "Bankruptcy prediction in the post-pandemic period: A case study of Visegrad Group countries," Oeconomia Copernicana, Institute of Economic Research, vol. 14(1), pages 253-293, March.
  48. Alex Kim & Sangwon Yoon, 2023. "Corporate Bankruptcy Prediction with Domain-Adapted BERT," Papers 2312.03194, arXiv.org.
  49. Madhura Dasgupta & Samarth Gupta, 2024. "What Determines Enterprise Borrowing from Self Help Groups? An Interpretable Supervised Machine Learning Approach," Journal of Financial Services Research, Springer;Western Finance Association, vol. 66(1), pages 77-99, August.
  50. Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
  51. Tan, Yuanyue & Wang, Zhiqiang & Xiong, Haifang & Liu, Yue, 2022. "Fundamental momentum and enhanced fundamental momentum: Evidence from the Chinese stock market," International Review of Economics & Finance, Elsevier, vol. 79(C), pages 680-693.
  52. Tomasz Korol, 2019. "Dynamic Bankruptcy Prediction Models for European Enterprises," JRFM, MDPI, vol. 12(4), pages 1-15, December.
  53. Eric Séverin & David Veganzones, 2021. "Can earnings management information improve bankruptcy prediction models?," Annals of Operations Research, Springer, vol. 306(1), pages 247-272, November.
  54. Sermpinis, Georgios & Tsoukas, Serafeim & Zhang, Ping, 2018. "Modelling market implied ratings using LASSO variable selection techniques," Journal of Empirical Finance, Elsevier, vol. 48(C), pages 19-35.
  55. Esther Calderon-Monge & Ivan Pastor-Sanz & Pilar Huerta-Zavala, 2017. "Economic Sustainability in Franchising: A Model to Predict Franchisor Success or Failure," Sustainability, MDPI, vol. 9(8), pages 1-16, August.
  56. Azizpour, S & Giesecke, K. & Schwenkler, G., 2018. "Exploring the sources of default clustering," Journal of Financial Economics, Elsevier, vol. 129(1), pages 154-183.
  57. Zanka Mikhail, 2020. "A Comparison of Variables Selection Methods and their Sequential Application: A Case Study of the Bankruptcy of Polish Companies," Folia Oeconomica Stetinensia, Sciendo, vol. 20(1), pages 531-543, June.
  58. Ding, Yi & Kambouroudis, Dimos & McMillan, David G., 2021. "Forecasting realised volatility: Does the LASSO approach outperform HAR?," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 74(C).
  59. Caraiani, Petre, 2022. "Using LASSO-family models to estimate the impact of monetary policy on corporate investments," Economics Letters, Elsevier, vol. 210(C).
  60. Michal Karas & Mária Režňáková, 2017. "The Potential of Dynamic Indicator in Development of the Bankruptcy Prediction Models: the Case of Construction Companies," Acta Universitatis Agriculturae et Silviculturae Mendelianae Brunensis, Mendel University Press, vol. 65(2), pages 641-652.
  61. Lucey, Brian & Urquhart, Andrew & Zhang, Hanxiong, 2022. "UK Vice Chancellor compensation: Do they get what they deserve?," The British Accounting Review, Elsevier, vol. 54(4).
  62. Wen-Kuo Chen & Dalianus Riantama & Long-Sheng Chen, 2020. "Using a Text Mining Approach to Hear Voices of Customers from Social Media toward the Fast-Food Restaurant Industry," Sustainability, MDPI, vol. 13(1), pages 1-17, December.
  63. Alessandro Bitetto & Stefano Filomeni & Michele Modina, 2021. "Understanding corporate default using Random Forest: The role of accounting and market information," DEM Working Papers Series 205, University of Pavia, Department of Economics and Management.
  64. Mestiri, Sami, 2024. "Financial applications of machine learning using R software," MPRA Paper 119998, University Library of Munich, Germany.
  65. Georgios Sermpinis & Serafeim Tsoukas & Ping Zhang, 2019. "What influences a bank's decision to go public?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 24(4), pages 1464-1485, October.
  66. Mestiri, Sami, 2023. "How to use machine learning in finance," MPRA Paper 120045, University Library of Munich, Germany.
  67. Hirk, Rainer & Vana, Laura & Hornik, Kurt, 2022. "A corporate credit rating model with autoregressive errors," Journal of Empirical Finance, Elsevier, vol. 69(C), pages 224-240.
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