IDEAS home Printed from https://ideas.repec.org/r/eee/jebusi/v46y1994i4p269-286.html
   My bibliography  Save this item

Predicting corporate bankruptcy and financial distress: Information value added by multinomial logit models

Citations

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


Cited by:

  1. Marco Bisogno, 2012. "The Accessibility Of The Italian Bankruptcy Procedures: An Empirical Analysis," Eurasian Business Review, Springer;Eurasia Business and Economics Society, vol. 2(2), pages 1-24, December.
  2. Premachandra, I.M. & Bhabra, Gurmeet Singh & Sueyoshi, Toshiyuki, 2009. "DEA as a tool for bankruptcy assessment: A comparative study with logistic regression technique," European Journal of Operational Research, Elsevier, vol. 193(2), pages 412-424, March.
  3. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
  4. Gander, James P., 2013. "Integrating bank profit and risk-avoidance decisions for selected European countries: A micro–macro analysis," Economic Modelling, Elsevier, vol. 31(C), pages 717-722.
  5. Foreman, R. Dean, 2003. "A logistic analysis of bankruptcy within the US local telecommunications industry," Journal of Economics and Business, Elsevier, vol. 55(2), pages 135-166.
  6. 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.
  7. 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.
  8. Sunti Tirapat & Aekkachai Nittayagasetwat, 1999. "An Investigation of Thai Listed Firms' Financial Distress Using Macro and Micro Variables," Multinational Finance Journal, Multinational Finance Journal, vol. 3(2), pages 103-125, June.
  9. Lili Li & Jun Yang & Xin Zou, 2016. "A study of credit risk of Chinese listed companies: ZPP versus KMV," Applied Economics, Taylor & Francis Journals, vol. 48(29), pages 2697-2710, June.
  10. Eduardo Acosta-González & Fernando Fernández-Rodríguez & Hicham Ganga, 2019. "Predicting Corporate Financial Failure Using Macroeconomic Variables and Accounting Data," Computational Economics, Springer;Society for Computational Economics, vol. 53(1), pages 227-257, January.
  11. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5-6), pages 677-710.
  12. Mathur MAYANK, 2020. "Macroeconomic View of Mergers and Acquisitions in the Technology Industry," Economics and Applied Informatics, "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration, issue 1, pages 147-155.
  13. Marek Gruszczynski, 2004. "Financial distress of companies in Poland," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 10(4), pages 249-256, November.
  14. Reynolds, Stephen E. & Ratanakomut, Somchai & Gander, James, 2000. "Bank financial structure in pre-crisis East and Southeast Asia," Journal of Asian Economics, Elsevier, vol. 11(3), pages 319-331, December.
  15. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "DEA-DA for bankruptcy-based performance assessment: Misclassification analysis of Japanese construction industry," European Journal of Operational Research, Elsevier, vol. 199(2), pages 576-594, December.
  16. 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).
  17. Evi Neophytou & Cecilio Mar Molinero, 2004. "Predicting Corporate Failure in the UK: A Multidimensional Scaling Approach," Journal of Business Finance & Accounting, Wiley Blackwell, vol. 31(5‐6), pages 677-710, June.
  18. Sueyoshi, Toshiyuki & Goto, Mika, 2009. "Can R&D expenditure avoid corporate bankruptcy? Comparison between Japanese machinery and electric equipment industries using DEA-discriminant analysis," European Journal of Operational Research, Elsevier, vol. 196(1), pages 289-311, July.
  19. 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.
  20. 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.
  21. Westgaard, Sjur & van der Wijst, Nico, 2001. "Default probabilities in a corporate bank portfolio: A logistic model approach," European Journal of Operational Research, Elsevier, vol. 135(2), pages 338-349, December.
  22. Andreas Charitou & Evi Neophytou & Chris Charalambous, 2004. "Predicting corporate failure: empirical evidence for the UK," European Accounting Review, Taylor & Francis Journals, vol. 13(3), pages 465-497.
  23. Agata Lozinskaia & Andreas Merikas & Anna Merika & Henry Penikas, 2017. "Determinants of the probability of default: the case of the internationally listed shipping corporations," Maritime Policy & Management, Taylor & Francis Journals, vol. 44(7), pages 837-858, October.
  24. Pasaribu, Rowland Bismark Fernando, 2008. "Penggunaan Binary Logit untuk Prediksi Financial Distress Perusahaan Yang Tercatat Di Bursa Efek Jakarta [Financial Distress Prediction In Indonesian Stock Exchange]," MPRA Paper 36980, University Library of Munich, Germany.
  25. Sorokina, Nonna & Thornton, John H., 2016. "Reactions of equity markets to recent financial reforms," Journal of Economics and Business, Elsevier, vol. 87(C), pages 50-69.
  26. Oda, Nobuyuki & Muranaga, Jun, 1997. "A New Framework for Measuring the Credit Risk of a Portfolio: The "ExVaR" Model," Monetary and Economic Studies, Institute for Monetary and Economic Studies, Bank of Japan, vol. 15(2), pages 27-62, December.
  27. Zhichao Luo & Pingyu Hsu & Ni Xu, 2020. "SME Default Prediction Framework with the Effective Use of External Public Credit Data," Sustainability, MDPI, vol. 12(18), pages 1-18, September.
  28. MAHMOOD H. AL-OSAIMY & Ahmed S. Bamakhramah, 2004. "An Early Warning System for Islamic Banks Performance نظام الإنذار المبكر لأداء البنوك الإسلامية," Journal of King Abdulaziz University: Islamic Economics, King Abdulaziz University, Islamic Economics Institute., vol. 17(1), pages 3-14, January.
  29. Ana Paula Matias Gama & Helena Susana Amaral Geraldes, 2012. "Credit risk assessment and the impact of the New Basel Capital Accord on small and medium‐sized enterprises," Management Research Review, Emerald Group Publishing Limited, vol. 35(8), pages 727-749, July.
  30. Sohn, So Young & Kim, Hong Sik, 2007. "Random effects logistic regression model for default prediction of technology credit guarantee fund," European Journal of Operational Research, Elsevier, vol. 183(1), pages 472-478, November.
  31. Qunfeng LIAO & Seyed MEHDIAN, 2016. "Measuring Financial Distress And Predicting Corporate Bankruptcy: An Index Approach," Review of Economic and Business Studies, Alexandru Ioan Cuza University, Faculty of Economics and Business Administration, issue 17, pages 33-51, June.
  32. Pinder, Jonathan P., 1996. "Decision analysis using multinomial logit models: Mortgage portfolio valuation," Journal of Economics and Business, Elsevier, vol. 48(1), pages 67-77, February.
  33. Peter J. Carey & Marshall A. Geiger & Brendan T. O’Connell, 2008. "Costs Associated With Going‐Concern‐Modified Audit Opinions: An Analysis of the Australian Audit Market," Abacus, Accounting Foundation, University of Sydney, vol. 44(1), pages 61-81, March.
  34. Antonio Pelaez-Verdet & Pilar Loscertales-Sanchez, 2021. "Key Ratios for Long-Term Prediction of Hotel Financial Distress and Corporate Default: Survival Analysis for an Economic Stagnation," Sustainability, MDPI, vol. 13(3), pages 1-17, January.
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.