IDEAS home Printed from https://ideas.repec.org/r/bla/jbfnac/v44y2017i1-2p3-34.html
   My bibliography  Save this item

Predicting Corporate Bankruptcy: An Evaluation of Alternative Statistical Frameworks

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Chen, Dangxing & Ye, Jiahui & Ye, Weicheng, 2023. "Interpretable selective learning in credit risk," Research in International Business and Finance, Elsevier, vol. 65(C).
  2. 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.
  3. Salvatore Ferri & Alberto Tron & Federico Colantoni & Riccardo Savio, 2023. "Sustainability Disclosure and IPO Performance: Exploring the Impact of ESG Reporting," Sustainability, MDPI, vol. 15(6), pages 1-15, March.
  4. 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).
  5. 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.
  6. Oz, Ibrahim Onur & Yelkenci, Tezer & Meral, Gorkem, 2021. "The role of earnings components and machine learning on the revelation of deteriorating firm performance," International Review of Financial Analysis, Elsevier, vol. 77(C).
  7. Beiqi Lin & Chelsea Liu & Kelvin Jui Keng Tan & Qing Zhou, 2020. "CEO turnover and bankrupt firms’ emergence," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 47(9-10), pages 1238-1267, October.
  8. Nawaf Almaskati, 2022. "Machine learning in finance: Major applications, issues, metrics, and future trends," International Journal of Financial Engineering (IJFE), World Scientific Publishing Co. Pte. Ltd., vol. 9(03), pages 1-32, September.
  9. Lucia Svabova & Lucia Michalkova & Marek Durica & Elvira Nica, 2020. "Business Failure Prediction for Slovak Small and Medium-Sized Companies," Sustainability, MDPI, vol. 12(11), pages 1-14, June.
  10. David Alaminos & Manuel Ángel Fernández, 2019. "Why do football clubs fail financially? A financial distress prediction model for European professional football industry," PLOS ONE, Public Library of Science, vol. 14(12), pages 1-15, December.
  11. Carmen Gallucci & Rosalia Santullli & Michele Modina & Vincenzo Formisano, 2023. "Financial ratios, corporate governance and bank-firm information: a Bayesian approach to predict SMEs’ default," Journal of Management & Governance, Springer;Accademia Italiana di Economia Aziendale (AIDEA), vol. 27(3), pages 873-892, September.
  12. Michele Bertoni & Bruno De Rosa & Paola Rossi, 2021. ""Early Warnings": incremento nella capacit? di risposta o perdita di rilevanza?," MANAGEMENT CONTROL, FrancoAngeli Editore, vol. 2021(1), pages 175-194.
  13. Michele Bertoni & Bruno De Rosa & Laura Peressin, 2019. "Early Warning Systems: A Risk of Increasing Managerial Myopia?," Management, University of Primorska, Faculty of Management Koper, vol. 14(4), pages 305-323.
  14. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
  15. Hoang Hiep Nguyen & Jean-Laurent Viviani & Sami Ben Jabeur, 2023. "Bankruptcy prediction using machine learning and Shapley additive explanations," Post-Print hal-04223161, HAL.
  16. Stelios Markoulis & Panagiotis Ioannou & Spiros Martzoukos, 2023. "Bank distress in the European Union 2008–2015: A closer look at capital, size and revenue diversification," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 28(1), pages 792-820, January.
  17. Abinzano, Isabel & Gonzalez-Urteaga, Ana & Muga, Luis & Sanchez, Santiago, 2020. "Performance of default-risk measures: the sample matters," Journal of Banking & Finance, Elsevier, vol. 120(C).
  18. 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.
  19. Mohammad S. Uddin & Guotai Chi & Mazin A. M. Al Janabi & Tabassum Habib, 2022. "Leveraging random forest in micro‐enterprises credit risk modelling for accuracy and interpretability," International Journal of Finance & Economics, John Wiley & Sons, Ltd., vol. 27(3), pages 3713-3729, July.
  20. Kamesh Korangi & Christophe Mues & Cristi'an Bravo, 2021. "A transformer-based model for default prediction in mid-cap corporate markets," Papers 2111.09902, arXiv.org, revised Apr 2023.
  21. Ahmed, Shamima & Alshater, Muneer M. & Ammari, Anis El & Hammami, Helmi, 2022. "Artificial intelligence and machine learning in finance: A bibliometric review," Research in International Business and Finance, Elsevier, vol. 61(C).
  22. Misankova Maria & Zvarikova Katarina & Kliestikova Jana, 2017. "Bankruptcy Practice in Countries of Visegrad Four," Economics and Culture, Sciendo, vol. 14(1), pages 108-118, June.
  23. 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.
  24. Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Business model contributions to bank profit performance: A machine learning approach," Research in International Business and Finance, Elsevier, vol. 64(C).
  25. You-Shyang Chen & Chien-Ku Lin & Chih-Min Lo & Su-Fen Chen & Qi-Jun Liao, 2021. "Comparable Studies of Financial Bankruptcy Prediction Using Advanced Hybrid Intelligent Classification Models to Provide Early Warning in the Electronics Industry," Mathematics, MDPI, vol. 9(20), pages 1-26, October.
  26. Almaskati, Nawaf & Bird, Ron & Yeung, Danny & Lu, Yue, 2021. "A horse race of models and estimation methods for predicting bankruptcy," Advances in accounting, Elsevier, vol. 52(C).
  27. Korangi, Kamesh & Mues, Christophe & Bravo, Cristián, 2023. "A transformer-based model for default prediction in mid-cap corporate markets," European Journal of Operational Research, Elsevier, vol. 308(1), pages 306-320.
  28. Ida Nervik Hjelseth & Arvid Raknerud & Bjørn H. Vatne, 2022. "A bankruptcy probability model for assessing credit risk on corporate loans with automated variable selection," Working Paper 2022/7, Norges Bank.
  29. Marek Gruszczyński, 2019. "On Unbalanced Sampling in Bankruptcy Prediction," IJFS, MDPI, vol. 7(2), pages 1-13, June.
  30. Diego Andrés Correa-Mejía & Mauricio Lopera-Castaño, 2020. "Financial ratios as a powerful instrument to predict insolvency; a study using boosting algorithms in Colombian firms," Estudios Gerenciales, Universidad Icesi, vol. 36(155), pages 229-238, June.
  31. Noora Alzayed & Rasol Eskandari & Hassan Yazdifar, 2023. "Bank failure prediction: corporate governance and financial indicators," Review of Quantitative Finance and Accounting, Springer, vol. 61(2), pages 601-631, August.
  32. Jones, Stewart & Wang, Tim, 2019. "Predicting private company failure: A multi-class analysis," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 61(C), pages 161-188.
  33. 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.
  34. Chien-Min Kang & Ming-Chieh Wang & Lin Lin, 2022. "Financial Distress Prediction of Cooperative Financial Institutions—Evidence for Taiwan Credit Unions," IJFS, MDPI, vol. 10(2), pages 1-25, April.
  35. Ho, Kung-Cheng & Yen, Huang-Ping & Lu, Canyi & Lee, Shih-Cheng, 2023. "Does information disclosure and transparency ranking system prevent the default risk of a firm?," Economic Analysis and Policy, Elsevier, vol. 78(C), pages 1089-1105.
  36. 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.
  37. Maren Forier & Nadine Lybaert & Maarten Corten & Niels Appermont & Tensie Steijvers, 2023. "The flip side of the coin: how entrepreneurship-oriented insolvency laws can complicate access to debt financing for growth firms," European Journal of Law and Economics, Springer, vol. 56(3), pages 461-495, December.
  38. David Johnstone & Stewart Jones & Oliver Jones & Steve Tulig, 2021. "Scoring Probability Forecasts by a User’s Bets Against a Market Consensus," Decision Analysis, INFORMS, vol. 18(3), pages 169-184, September.
  39. Rastin Matin & Casper Hansen & Christian Hansen & Pia M{o}lgaard, 2018. "Predicting Distresses using Deep Learning of Text Segments in Annual Reports," Papers 1811.05270, arXiv.org.
  40. 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.
  41. Königstorfer, Florian & Thalmann, Stefan, 2020. "Applications of Artificial Intelligence in commercial banks – A research agenda for behavioral finance," Journal of Behavioral and Experimental Finance, Elsevier, vol. 27(C).
  42. 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.
  43. Stewart Jones, 2017. "Corporate bankruptcy prediction: a high dimensional analysis," Review of Accounting Studies, Springer, vol. 22(3), pages 1366-1422, September.
  44. Ashraf, Sumaira & Félix, Elisabete G.S. & Serrasqueiro, Zélia, 2020. "Development and testing of an augmented distress prediction model: A comparative study on a developed and an emerging market," Journal of Multinational Financial Management, Elsevier, vol. 57.
  45. Magali Costa & Inês Lisboa & Ana Gameiro, 2022. "Is the Financial Report Quality Important in the Default Prediction? SME Portuguese Construction Sector Evidence," Risks, MDPI, vol. 10(5), pages 1-24, May.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.