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Predicting corporate failure: empirical evidence for the UK

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  1. CIOTINA Daniela & CIOTINA Ioan Marius, 2013. "Symptoms of Bankruptcy and Prediction Models of Bankruptcy Risk," Anale. Seria Stiinte Economice. Timisoara, Faculty of Economics, Tibiscus University in Timisoara, vol. 0, pages 114-121, May.
  2. 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.
  3. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, Sciendo, vol. 5(2), pages 23-45, September.
  4. Kristóf, Tamás, 2008. "A csődelőrejelzés és a nem fizetési valószínűség számításának módszertani kérdéseiről [Some methodological questions of bankruptcy prediction and probability of default estimation]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 441-461.
  5. du Jardin, Philippe & Séverin, Eric, 2012. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," European Journal of Operational Research, Elsevier, vol. 221(2), pages 378-396.
  6. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
  7. Apostolos G. Christopoulos & Ioannis G. Dokas & Iraklis Kollias & John Leventides, 2019. "An implementation of Soft Set Theory in the Variables Selection Process for Corporate Failure Prediction Models. Evidence from NASDAQ Listed Firms," Bulletin of Applied Economics, Risk Market Journals, vol. 6(1), pages 1-20.
  8. Simone Poli & Marco Gatti, 2024. "The relevance of cash flow information in predicting corporate bankruptcy in Italian private companies," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2024(1), pages 179-202.
  9. Wu, Chloe Yu-Hsuan & Hsu, Hwa-Hsien & Haslam, Jim, 2016. "Audit committees, non-audit services, and auditor reporting decisions prior to failure," The British Accounting Review, Elsevier, vol. 48(2), pages 240-256.
  10. Beattie, Vivien, 2005. "Moving the financial accounting research front forward: the UK contribution," The British Accounting Review, Elsevier, vol. 37(1), pages 85-114.
  11. P. Du Jardin & E. Séverin, 2011. "Predicting Corporate Bankruptcy Using Self-Organising map: An empirical study to Improve the Forecasting horizon of financial failure model," Post-Print hal-00801878, HAL.
  12. Michael Filletti & Aaron Grech, 2020. "Using News Articles and Financial Data to predict the likelihood of bankruptcy," Papers 2003.13414, arXiv.org.
  13. Oz, Ibrahim Onur & Simga-Mugan, Can, 2018. "Bankruptcy prediction models' generalizability: Evidence from emerging market economies," Advances in accounting, Elsevier, vol. 41(C), pages 114-125.
  14. Ha Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," Working Papers hal-04133309, HAL.
  15. Li, Xia & Gupta, Jairaj & Bu, Ziwen & Kannothra, Chacko George, 2023. "Effect of cash flow risk on corporate failures, and the moderating role of earnings management and abnormal compensation," International Review of Financial Analysis, Elsevier, vol. 89(C).
  16. Şaban Çelik & Bora Aktan & Bruce Burton, 2022. "Firm dynamics and bankruptcy processes: A new theoretical model," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(3), pages 567-591, April.
  17. Adilah Azhari* & Hanita Kadir, 2018. "The Effects of Liquidity, Profitability and Board Characteristics on Debt Restructuring Likelihood Among Malaysian GLCs," The Journal of Social Sciences Research, Academic Research Publishing Group, pages 942-950:6.
  18. García-Gallego, Ana & Mures-Quintana, María-Jesús, 2013. "La muestra de empresas en los modelos de predicción del fracaso: influencia en los resultados de clasificación || The Sample of Firms in Business Failure Prediction Models: Influence on Classification," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 15(1), pages 133-150, June.
  19. Pasiouras, Fotios & Gaganis, Chrysovalantis & Zopounidis, Constantin, 2007. "Multicriteria decision support methodologies for auditing decisions: The case of qualified audit reports in the UK," European Journal of Operational Research, Elsevier, vol. 180(3), pages 1317-1330, August.
  20. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
  21. 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.
  22. George Giannopoulos & Sophia Ali Sardar & Rebecca Salti & Nicos Sykianakis, 2022. "Analyzing Insolvency Prediction Models in the Period Before and After the Financial Crisis: A Case Study on the Example of US Firms," International Journal of Finance, Insurance and Risk Management, International Journal of Finance, Insurance and Risk Management, vol. 12(3), pages 23-45.
  23. Elisa Ughetto & Andrea Vezzulli, 2011. "What role can mutual guarantee consortia play for financing innovation? A firm-level study for Italy," International Journal of Banking, Accounting and Finance, Inderscience Enterprises Ltd, vol. 3(4), pages 294-319.
  24. Ilyes Abid & Rim Ayadi & Khaled Guesmi & Farid Mkaouar, 2022. "A new approach to deal with variable selection in neural networks: an application to bankruptcy prediction," Annals of Operations Research, Springer, vol. 313(2), pages 605-623, June.
  25. Eleimon Gonis & Salima Paul & Jon Tucker, 2012. "Rating or no rating? That is the question: an empirical examination of UK companies," The European Journal of Finance, Taylor & Francis Journals, vol. 18(8), pages 709-735, September.
  26. Şaban Çelik, 2013. "Micro Credit Risk Metrics: A Comprehensive Review," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 20(4), pages 233-272, October.
  27. Grammenos, Costas Th. & Papapostolou, Nikos C., 2012. "US shipping initial public offerings: Do prospectus and market information matter?," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 48(1), pages 276-295.
  28. Jairaj Gupta & Nicholas Wilson & Andros Gregoriou & Jerome Healy, 2014. "The value of operating cash flow in modelling credit risk for SMEs," Applied Financial Economics, Taylor & Francis Journals, vol. 24(9), pages 649-660, May.
  29. Christian Lohmann & Thorsten Ohliger, 2020. "Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies," Journal of Business Economics, Springer, vol. 90(1), pages 137-172, February.
  30. Ha-Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," EconomiX Working Papers 2014-26, University of Paris Nanterre, EconomiX.
  31. Fayçal Mraihi & Inane Kanzari, 2019. "Predicting financial distress of companies: Comparison between multivariate discriminant analysis and multilayer perceptron for Tunisian case," Working Papers 1328, Economic Research Forum, revised 21 Aug 2019.
  32. Juraini Zainol Abidin & Nur Adiana Hiau Abdullah & Karren Lee-Hwei Khaw, 2020. "Predicting SMEs Failure: Logistic Regression vs Artificial Neural Network Models," Capital Markets Review, Malaysian Finance Association, vol. 28(2), pages 29-41.
  33. Hamid Waqas & Rohani Md-Rus, 2018. "Predicting financial distress: Applicability of O-score model for Pakistani firms," Business and Economic Horizons (BEH), Prague Development Center, vol. 14(2), pages 389-401, April.
  34. Khoja, Layla & Chipulu, Maxwell & Jayasekera, Ranadeva, 2019. "Analysis of financial distress cross countries: Using macroeconomic, industrial indicators and accounting data," International Review of Financial Analysis, Elsevier, vol. 66(C).
  35. Josep Patau & Antonio Somoza & Salvador Torra, 2020. "Diagnosis of the Domino Effect in Bankruptcy Situations Through Positioning Maps and Their Evolution 10 Years Later," SAGE Open, , vol. 10(4), pages 21582440209, December.
  36. Timotej Jagric & Vita Jagric & Davorin Kracun, 2011. "Does Non-linearity Matter in Retail Credit Risk Modeling?," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 61(4), pages 384-402, August.
  37. Yossavadee Pugpaichit & Phassawan Suntrauk, 2014. "The Prediction Model of Bankruptcy: Evidence from the Small and Medium Enterprises (SMEs) in Thailand," International Journal of Management Sciences, Research Academy of Social Sciences, vol. 3(10), pages 788-796.
  38. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
  39. Manjusha Senapathi & Saptarshi Ghosal, 2016. "Modelling Corporate Sector Distress in India," Working Papers id:11540, eSocialSciences.
  40. Jane Haider & Zhirong Ou & Stephen Pettit, 2019. "Predicting corporate failure for listed shipping companies," Maritime Economics & Logistics, Palgrave Macmillan;International Association of Maritime Economists (IAME), vol. 21(3), pages 415-438, September.
  41. Balcaen, Sofie & Ooghe, Hubert, 2006. "35 years of studies on business failure: an overview of the classic statistical methodologies and their related problems," The British Accounting Review, Elsevier, vol. 38(1), pages 63-93.
  42. Pasiouras, Fotios & Tanna, Sailesh & Zopounidis, Constantin, 2007. "The identification of acquisition targets in the EU banking industry: An application of multicriteria approaches," International Review of Financial Analysis, Elsevier, vol. 16(3), pages 262-281.
  43. Fayçal Mraihi & Inane Kanzari & Mohamed Tahar Rajhi, 2015. "Development of a Prediction Model of Failure in Tunisian Companies: Comparison between Logistic Regression and Support Vector Machines," International Journal of Empirical Finance, Research Academy of Social Sciences, vol. 4(3), pages 184-205.
  44. Karen Peursem & Yi Chiann Chan, 2014. "Forecasting New Zealand Corporate Failures 2001–10: Opportunity Lost?," Australian Accounting Review, CPA Australia, vol. 24(3), pages 276-288, September.
  45. Casado Yusta, Silvia & Nœ–ez Letamendía, Laura & Pacheco Bonrostro, Joaqu’n Antonio, 2018. "Predicting Corporate Failure: The GRASP-LOGIT Model || Predicci—n de la quiebra empresarial: el modelo GRASP-LOGIT," Revista de Métodos Cuantitativos para la Economía y la Empresa = Journal of Quantitative Methods for Economics and Business Administration, Universidad Pablo de Olavide, Department of Quantitative Methods for Economics and Business Administration, vol. 26(1), pages 294-314, Diciembre.
  46. Alessandra Amendola & Francesco Giordano & Maria Lucia Parrella & Marialuisa Restaino, 2017. "Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction," Applied Stochastic Models in Business and Industry, John Wiley & Sons, vol. 33(4), pages 355-368, August.
  47. Elsayed, Mohamed & Elshandidy, Tamer, 2020. "Do narrative-related disclosures predict corporate failure? Evidence from UK non-financial publicly quoted firms," International Review of Financial Analysis, Elsevier, vol. 71(C).
  48. Jorge E. Galán, 2021. "CREWS: a CAMELS-based early warning system of systemic risk in the banking sector," Occasional Papers 2132, Banco de España.
  49. Scalzer, Rodrigo S. & Rodrigues, Adriano & Macedo, Marcelo Álvaro da S. & Wanke, Peter, 2019. "Financial distress in electricity distributors from the perspective of Brazilian regulation," Energy Policy, Elsevier, vol. 125(C), pages 250-259.
  50. Saoussen Boujelben & Hela Khemakhem-Feki & Ahmad Alqatan, 2020. "Real earnings management and the relevance of operating cash flows: A study of french listed firms," International Journal of Disclosure and Governance, Palgrave Macmillan, vol. 17(4), pages 218-229, December.
  51. Díez-Esteban, José María & García-Gómez, Conrado Diego & López-Iturriaga, Félix Javier & Santamaría-Mariscal, Marcos, 2017. "Corporate risk-taking, returns and the nature of major shareholders: Evidence from prospect theory," Research in International Business and Finance, Elsevier, vol. 42(C), pages 900-911.
  52. Evžen Kocenda & Martin Vojtek, 2011. "Default Predictors in Retail Credit Scoring: Evidence from Czech Banking Data," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 47(6), pages 80-98, November.
  53. Citterio, Alberto, 2024. "Bank failure prediction models: Review and outlook," Socio-Economic Planning Sciences, Elsevier, vol. 92(C).
  54. 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.
  55. Varadraj Bapat & Abhay Nagale, 2014. "Comparison of Bankruptcy Prediction Models: Evidence from India," Accounting and Finance Research, Sciedu Press, vol. 3(4), pages 1-91, August.
  56. 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.
  57. Bahiraie , Alireza & Arshadi , Ali, 2012. "Bankruptcy Prediction: Dynamic Geometric Genetic Programming (DGGP) Approach," Journal of Money and Economy, Monetary and Banking Research Institute, Central Bank of the Islamic Republic of Iran, vol. 6(4), pages 101-132, July.
  58. Hernandez Tinoco, Mario & Holmes, Phil & Wilson, Nick, 2018. "Polytomous response financial distress models: The role of accounting, market and macroeconomic variables," International Review of Financial Analysis, Elsevier, vol. 59(C), pages 276-289.
  59. du Jardin, Philippe, 2008. "Bankruptcy prediction and neural networks: The contribution of variable selection methods," MPRA Paper 44384, University Library of Munich, Germany.
  60. Lana Ivicic & Sasa Cerovac, 2009. "Credit Risk Assessment of Corporate Sector in Croatia," Financial Theory and Practice, Institute of Public Finance, vol. 33(4), pages 373-399.
  61. Yusuf Ali Al-Hroot, 2016. "A Comparison of Jordanian Bankruptcy Models: Multilayer Perceptron Neural Network and Discriminant Analysis," International Business Research, Canadian Center of Science and Education, vol. 9(12), pages 121-130, December.
  62. Fen-May Liou, 2008. "Fraudulent financial reporting detection and business failure prediction models: a comparison," Managerial Auditing Journal, Emerald Group Publishing, vol. 23(7), pages 650-662, July.
  63. Camacho-Miñano, María-del-Mar & Muñoz-Izquierdo, Nora & Pincus, Morton & Wellmeyer, Patricia, 2024. "Are key audit matter disclosures useful in assessing the financial distress level of a client firm?," The British Accounting Review, Elsevier, vol. 56(2).
  64. Jose Eduardo Gomez-Gonzalez & Nidia Ruth Reyes, 2013. "Firm failure and relationship lending in an emerging economy: new evidence from small businesses," Macroeconomics and Finance in Emerging Market Economies, Taylor & Francis Journals, vol. 6(1), pages 131-145, March.
  65. Nisansala Wijekoon & A. Abdul Azeez, 2015. "An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka," International Journal of Business and Social Research, MIR Center for Socio-Economic Research, vol. 5(7), pages 1-14, July.
  66. A. Mendes & R. L. Cardoso & P. C. Mário & A. L. Martinez & F. R. Ferreira, 2014. "Insolvency Prediction In The Presence Of Data Inconsistencies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 21(3), pages 155-167, July.
  67. Hyeongjun Kim & Hoon Cho & Doojin Ryu, 2020. "Corporate Default Predictions Using Machine Learning: Literature Review," Sustainability, MDPI, vol. 12(16), pages 1-11, August.
  68. Weidong Guo & Zach Zhizhong Zhou, 2022. "A comparative study of combining tree‐based feature selection methods and classifiers in personal loan default prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(6), pages 1248-1313, September.
  69. Ali Asgary & Ali Sadeghi Naini, 2011. "Modelling The Adaptation Of Business Continuity Planning By Businesses Using Neural Networks," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(2-3), pages 89-104, April.
  70. Kennedy Mwengei B. Ombaba & David Kosgei, 2017. "Board Composition and Financial Distress of Listed Firms in Kenya. An Empirical Analysis," Journal of Finance and Investment Analysis, SCIENPRESS Ltd, vol. 6(4), pages 1-4.
  71. Layla Khoja & Maxwell Chipulu & Ranadeva Jayasekera, 2016. "Analysing corporate insolvency in the Gulf Cooperation Council using logistic regression and multidimensional scaling," Review of Quantitative Finance and Accounting, Springer, vol. 46(3), pages 483-518, April.
  72. Elsayed, Mohamed & Elshandidy, Tamer & Ahmed, Yousry, 2022. "Corporate failure in the UK: An examination of corporate governance reforms," International Review of Financial Analysis, Elsevier, vol. 82(C).
  73. Liang, Deron & Tsai, Chih-Fong & Lu, Hung-Yuan (Richard) & Chang, Li-Shin, 2020. "Combining corporate governance indicators with stacking ensembles for financial distress prediction," Journal of Business Research, Elsevier, vol. 120(C), pages 137-146.
  74. Laurentiu DROJ & Goran KARANOVIC & Ioan Gheorghe TARA, 2021. "The Impact Of The Covid-19 Pandemics Over The Financial Performance At The Level Of The Main Pharmaceutical Operating In Central And Eastern Europe," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 30(2), pages 283-290, December.
  75. Jarmila Horváthová & Martina Mokrišová & Martin Bača, 2023. "Bankruptcy Prediction for Sustainability of Businesses: The Application of Graph Theoretical Modeling," Mathematics, MDPI, vol. 11(24), pages 1-20, December.
  76. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
  77. Bole, Velimir & Prašnikar, Janez & Trobec, Domen, 2014. "Policy measures in the deleveraging process: A macroprudential evaluation," Journal of Policy Modeling, Elsevier, vol. 36(2), pages 410-432.
  78. Onofrei, Mihaela & Lupu, Dan, 2014. "The modelling of forecasting the bankruptcy in Romania," MPRA Paper 95511, University Library of Munich, Germany.
  79. Ha Thu Nguyen, 2014. "Default Predictors in Credit Scoring - Evidence from France’s Retail Banking Institution," Working Papers hal-04141336, HAL.
  80. Kavussanos, Manolis G. & Tsouknidis, Dimitris A., 2016. "Default risk drivers in shipping bank loans," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 94(C), pages 71-94.
  81. Jackson, Richard H.G. & Wood, Anthony, 2013. "The performance of insolvency prediction and credit risk models in the UK: A comparative study," The British Accounting Review, Elsevier, vol. 45(3), pages 183-202.
  82. du Jardin, Philippe, 2010. "Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy," MPRA Paper 44375, University Library of Munich, Germany.
  83. Reza Monem, 2011. "The One.Tel Collapse: Lessons for Corporate Governance," Australian Accounting Review, CPA Australia, vol. 21(4), pages 340-351, December.
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  85. Fayçal Mraihi, 2016. "Distressed Company Prediction Using Logistic Regression: Tunisian’s Case," Quarterly Journal of Business Studies, Research Academy of Social Sciences, vol. 2(1), pages 34-54.
  86. 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.
  87. Nisansala Wijekoon & A. Abdul Azeez, 2015. "An Integrated Model to Predict Corporate Failure of Listed Companies in Sri Lanka," International Journal of Business and Social Research, LAR Center Press, vol. 5(7), pages 1-14, July.
  88. Denis Kušter & Bojana Vuković & Sunčica Milutinović & Kristina Peštović & Teodora Tica & Dejan Jakšić, 2023. "Early Insolvency Prediction as a Key for Sustainable Business Growth," Sustainability, MDPI, vol. 15(21), pages 1-24, October.
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