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Are hazard models superior to traditional bankruptcy prediction approaches? A comprehensive test

Citations

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Cited by:

  1. Yoshiyuki ARATA, 2018. "Bankruptcy propagation on a customer-supplier network: An empirical analysis in Japan," Discussion papers 18040, Research Institute of Economy, Trade and Industry (RIETI).
  2. Michał Thor & Łukasz Postek, 2024. "Gated recurrent unit network: A promising approach to corporate default prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1131-1152, August.
  3. Koresh Galil & Neta Gilat, 2019. "Predicting Default More Accurately: To Proxy or Not to Proxy for Default?," International Review of Finance, International Review of Finance Ltd., vol. 19(4), pages 731-758, December.
  4. Kalak, Izidin El & Azevedo, Alcino & Hudson, Robert & Karim, Mohamad Abd, 2017. "Stock liquidity and SMEs’ likelihood of bankruptcy: Evidence from the US market," Research in International Business and Finance, Elsevier, vol. 42(C), pages 1383-1393.
  5. 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.
  6. Alam, Nurul & Gao, Junbin & Jones, Stewart, 2021. "Corporate failure prediction: An evaluation of deep learning vs discrete hazard models," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 75(C).
  7. Li, Keming & Nishikawa, Takeshi & Rao, Ramesh P., 2025. "Does the threat of short selling discipline management? Evidence from default risk changes around regulation SHO," Journal of Financial Markets, Elsevier, vol. 73(C).
  8. Serena Fatica & Tommaso Oliviero & Michela Rancan, 2025. "Judicial inefficiency and the default of zombie firms," CSEF Working Papers 747, Centre for Studies in Economics and Finance (CSEF), University of Naples, Italy.
  9. Taoushianis, Zenon, 2025. "Bankruptcy prediction with fractional polynomial transformation of financial ratios," European Journal of Operational Research, Elsevier, vol. 327(2), pages 690-702.
  10. 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.
  11. Mohammad Mahdi Mousavi & Jamal Ouenniche & Kaoru Tone, 2023. "A dynamic performance evaluation of distress prediction models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 42(4), pages 756-784, July.
  12. Christoph Braunsberger & Ewald Aschauer, 2025. "Corporate Failure Prediction: A Literature Review of Altman Z-Score and Machine Learning Models Within a Technology Adoption Framework," JRFM, MDPI, vol. 18(8), pages 1-32, August.
  13. 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.
  14. Li, Huan & Wu, Weixing, 2024. "Loan default predictability with explainable machine learning," Finance Research Letters, Elsevier, vol. 60(C).
  15. Floros, Ioannis & White, Joshua T., 2016. "Qualified residential mortgages and default risk," Journal of Banking & Finance, Elsevier, vol. 70(C), pages 86-104.
  16. Stef, Nicolae & Zenou, Emmanuel, 2021. "Management-to-staff ratio and a firm's exit," Journal of Business Research, Elsevier, vol. 125(C), pages 252-260.
  17. Nico Dewaelheyns & Cynthia Van Hulle & Yannick Van Landuyt & Mathias Verreydt, 2021. "Labor Contracts, Wages and SME Failure," Sustainability, MDPI, vol. 13(14), pages 1-15, July.
  18. Pooja Singh & Anindita Chakraborty, 2023. "How Indian Pharma Industry Performed in the Last Decade? Impact of a Non-macroeconomic Variable and Financial Distress," Jindal Journal of Business Research, , vol. 12(2), pages 143-159, December.
  19. Ruben Loaiza-Maya & Michael Stanley Smith, 2017. "Variational Bayes Estimation of Discrete-Margined Copula Models with Application to Time Series," Papers 1712.09150, arXiv.org, revised Jul 2018.
  20. Miguel Ampudia & Filippo Busetto & Fabio Fornari, 2022. "Chronicle of a death foretold: does higher volatility anticipate corporate default?," Bank of England working papers 1001, Bank of England.
  21. De Bock, Koen W. & Coussement, Kristof & Lessmann, Stefan, 2020. "Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach," European Journal of Operational Research, Elsevier, vol. 285(2), pages 612-630.
  22. Simone Pizzi & Fabio Caputo & Andrea Venturelli, 2020. "Does it pay to be an honest entrepreneur? Addressing the relationship between sustainable development and bankruptcy risk," Corporate Social Responsibility and Environmental Management, John Wiley & Sons, vol. 27(3), pages 1478-1486, May.
  23. Mohammad Mahdi Mousavi & Jamal Ouenniche, 2018. "Multi-criteria ranking of corporate distress prediction models: empirical evaluation and methodological contributions," Annals of Operations Research, Springer, vol. 271(2), pages 853-886, December.
  24. 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.
  25. Avino, Davide E. & Conlon, Thomas & Cotter, John, 2019. "Credit default swaps as indicators of bank financial distress," Journal of International Money and Finance, Elsevier, vol. 94(C), pages 132-139.
  26. Datta, Pratik & Surya Prakash B. S. & Sane, Renuka, 2017. "Understanding Judicial Delay at the Income Tax Appellate Tribunal in India," Working Papers 17/208, National Institute of Public Finance and Policy.
  27. Evangelos C. Charalambakis & Ian Garrett, 2019. "On corporate financial distress prediction: What can we learn from private firms in a developing economy? Evidence from Greece," Review of Quantitative Finance and Accounting, Springer, vol. 52(2), pages 467-491, February.
  28. Li, Zhiyong & Li, Aimin & Bellotti, Anthony & Yao, Xiao, 2023. "The profitability of online loans: A competing risks analysis on default and prepayment," European Journal of Operational Research, Elsevier, vol. 306(2), pages 968-985.
  29. Li, Tangrong & Lin, Hui, 2021. "Credit risk and equity returns in China," International Review of Economics & Finance, Elsevier, vol. 76(C), pages 588-613.
  30. 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.
  31. El Kalak, Izidin & Hudson, Robert, 2016. "The effect of size on the failure probabilities of SMEs: An empirical study on the US market using discrete hazard model," International Review of Financial Analysis, Elsevier, vol. 43(C), pages 135-145.
  32. Boratyńska, Katarzyna & Grzegorzewska, Emilia, 2018. "Bankruptcy prediction in the agribusiness sector: Lessons from quantitative and qualitative approaches," Journal of Business Research, Elsevier, vol. 89(C), pages 175-181.
  33. Daniel Boos & Nikolaos Karampatsas & Wolfgang Garn & Lampros K. Stergioulas, 2024. "Predicting corporate restructuring and financial distress in banks: The case of the Swiss banking industry," Journal of Financial Research, Southern Finance Association;Southwestern Finance Association, vol. 47(2), pages 497-533, June.
  34. Grodecka-Messi, Anna & Kenny, Seán & Ögren, Anders, 2021. "Predictors of bank distress: The 1907 crisis in Sweden," Explorations in Economic History, Elsevier, vol. 80(C).
  35. 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.
  36. Rachid Maghniwi & Mustapha Oukassi, 2024. "Rating model for assessing the credit risk of SMEs in the construction sector in Morocco [Modèle de rating pour l'évaluation du risque de crédit des PME du secteur BTP au Maroc]," Post-Print hal-04791887, HAL.
  37. Afik, Zvika & Arad, Ohad & Galil, Koresh, 2016. "Using Merton model for default prediction: An empirical assessment of selected alternatives," Journal of Empirical Finance, Elsevier, vol. 35(C), pages 43-67.
  38. Cathcart, Lara & Dufour, Alfonso & Rossi, Ludovico & Varotto, Simone, 2020. "The differential impact of leverage on the default risk of small and large firms," Journal of Corporate Finance, Elsevier, vol. 60(C).
  39. Ugur, Mehmet & Solomon, Edna & Zeynalov, Ayaz, 2022. "Leverage, competition and financial distress hazard: Implications for capital structure in the presence of agency costs," Economic Modelling, Elsevier, vol. 108(C).
  40. Gila Burde, 2018. "Improved Methods for Predicting the Financial Vulnerability of Nonprofit Organizations," Administrative Sciences, MDPI, vol. 8(1), pages 1-8, February.
  41. Hesse, Matthies & Loy, Thomas, 2025. "Unlocking bankruptcy clues: A novel sentence-based machine learning approach," International Journal of Accounting Information Systems, Elsevier, vol. 56(C).
  42. Christopoulos, Andreas D. & Barratt, Joshua G., 2016. "Credit risk findings for commercial real estate loans using the reduced form," Finance Research Letters, Elsevier, vol. 19(C), pages 228-234.
  43. Jarmila Horváthová & Martina Mokrišová, 2018. "Risk of Bankruptcy, Its Determinants and Models," Risks, MDPI, vol. 6(4), pages 1-22, October.
  44. Bátiz-Zuk Enrique & Mohamed Abdulkadir & Sánchez-Cajal Fátima, 2021. "Exploring the sources of loan default clustering using survival analysis with frailty," Working Papers 2021-14, Banco de México.
  45. Jahanzaib Alvi & Imtiaz Arif, 2025. "Credit Scorecards & Forecasting Default Events – A Novel Story of Non-financial Listed Companies in Pakistan," Asia-Pacific Financial Markets, Springer;Japanese Association of Financial Economics and Engineering, vol. 32(4), pages 1459-1485, December.
  46. M. Simona Andreano & Roberto Benedetti & Andrea Mazzitelli & Federica Piersimoni, 2018. "Spatial autocorrelation and clusters in modelling corporate bankruptcy of manufacturing firms," Economia e Politica Industriale: Journal of Industrial and Business Economics, Springer;Associazione Amici di Economia e Politica Industriale, vol. 45(4), pages 475-491, December.
  47. Christophe Schalck & Meryem Yankol-Schalck, 2021. "Predicting French SME failures: new evidence from machine learning techniques," Applied Economics, Taylor & Francis Journals, vol. 53(51), pages 5948-5963, November.
  48. Trushin, Eshref & Ugur, Mehmet, 2018. "Ecosystem complexity, firm learning and survival: UK evidence on intra-industry age and size diversity as exit hazards," Greenwich Papers in Political Economy 19095, University of Greenwich, Greenwich Political Economy Research Centre.
  49. 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.
  50. Christopoulos, Andreas D., 2017. "The composition of CMBS risk," Journal of Banking & Finance, Elsevier, vol. 76(C), pages 215-239.
  51. Surbhi Bhatia & Manish K. Singh, 2022. "Fifty years since Altman (1968): Performance of financial distress prediction models," Working Papers 12, xKDR.
  52. Iwanicz-Drozdowska, Małgorzata & Jackowicz, Krzysztof & Kozłowski, Łukasz, 2018. "SMEs' near-death experiences. Do local banks extend a helping hand?," Emerging Markets Review, Elsevier, vol. 37(C), pages 47-65.
  53. 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.
  54. 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.
  55. Bitetto, Alessandro & Filomeni, Stefano & Modina, Michele, 2025. "Machine Learning for the Unlisted: Enhancing MSME Default Prediction with Public Market Signals," Journal of Corporate Finance, Elsevier, vol. 94(C).
  56. Yukiko Konno & Yuki Itoh, 2016. "An alternative to the standardized approach for assessing credit risk under the Basel Accords," Cogent Economics & Finance, Taylor & Francis Journals, vol. 4(1), pages 1220119-122, December.
  57. Peng, Michael & Stern, Elisheva R. & Hu, Hanwen, 2025. "Forecasting China bond default with severe class-imbalanced data: A simple learning model with causal inference," Economic Modelling, Elsevier, vol. 144(C).
  58. Christian Lohmann & Steffen Möllenhoff & Thorsten Ohliger, 2023. "Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models," Journal of Business Economics, Springer, vol. 93(9), pages 1661-1690, November.
  59. Adriana Csikosova & Maria Janoskova & Katarina Culkova, 2020. "Application of Discriminant Analysis for Avoiding the Risk of Quarry Operation Failure," JRFM, MDPI, vol. 13(10), pages 1-14, September.
  60. 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.
  61. Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
  62. Qin, Zhaohui & Wang, Xiaowan & Chen, Yijie & Fan, Yali & Andrianarimanana, Mihasina Harinaivo & Gai, Dhornor Tarir Duok, 2024. "Time-varying default risk of Chinese-listed companies: From empirical test to theoretical conjecture," Finance Research Letters, Elsevier, vol. 67(PA).
  63. Koen W. de Bock & Kristof Coussement & Stefan Lessmann, 2020. "Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach," Post-Print hal-02863245, HAL.
  64. Stefano Filomeni & Udichibarna Bose & Anastasios Megaritis & Athanasios Triantafyllou, 2024. "Can market information outperform hard and soft information in predicting corporate defaults?," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 29(3), pages 3567-3592, July.
  65. Ahmad, Abd Halim, 2019. "What factors discriminate reorganized and delisted distressed firms: Evidence from Malaysia," Finance Research Letters, Elsevier, vol. 29(C), pages 50-56.
  66. Brezigar-Masten, Arjana & Masten, Igor & Volk, Matjaž, 2021. "Modelin-g credit risk with a Tobit model of days past due," Journal of Banking & Finance, Elsevier, vol. 122(C).
  67. Yang Liu & Qingguo Zeng & Bobo Li & Lili Ma & Joaquín Ordieres‐Meré, 2022. "Anticipating financial distress of high‐tech startups in the European Union: A machine learning approach for imbalanced samples," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1131-1155, September.
  68. Li, Tangrong & Sun, Xuchu, 2023. "Predicting stock market returns using aggregate credit risk," International Review of Economics & Finance, Elsevier, vol. 88(C), pages 1087-1103.
  69. Leccadito, Arturo & Tunaru, Radu S. & Urga, Giovanni, 2015. "Trading strategies with implied forward credit default swap spreads," Journal of Banking & Finance, Elsevier, vol. 58(C), pages 361-375.
  70. Ampudia, Miguel & Busetto, Filippo & Fornari, Fabio, 2022. "Chronicle of a death foretold: does higher volatility anticipate corporate default?," Working Paper Series 2749, European Central Bank.
  71. John Nkwoma Inekwe, 2016. "Financial Distress, Employees’ Welfare and Entrepreneurship Among SMEs," Social Indicators Research: An International and Interdisciplinary Journal for Quality-of-Life Measurement, Springer, vol. 129(3), pages 1135-1153, December.
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