Symptoms of Bankruptcy and Prediction Models of Bankruptcy Risk
Author
Abstract
Suggested Citation
Download full text from publisher
References listed on IDEAS
- 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.
- Catherine Refait, 2004.
"La prévision de la faillite fondée sur l’analyse financière de l’entreprise : un état des lieux,"
Économie et Prévision, Programme National Persée, vol. 162(1), pages 129-147.
- Catherine Refait-Alexandre, 2004. "La prévision de la faillite fondée sur l'analyse financière de l'entreprise : un état des lieux," Economie & Prévision, La Documentation Française, vol. 162(1), pages 129-147.
- Edward I. Altman, 1968. "Financial Ratios, Discriminant Analysis And The Prediction Of Corporate Bankruptcy," Journal of Finance, American Finance Association, vol. 23(4), pages 589-609, September.
- Greene, William, 1998. "Sample selection in credit-scoring models1," Japan and the World Economy, Elsevier, vol. 10(3), pages 299-316, July.
- Edward I. Altman, 1968. "The Prediction Of Corporate Bankruptcy: A Discriminant Analysis," Journal of Finance, American Finance Association, vol. 23(1), pages 193-194, March.
- Zmijewski, Me, 1984. "Methodological Issues Related To The Estimation Of Financial Distress Prediction Models," Journal of Accounting Research, Wiley Blackwell, vol. 22, pages 59-82.
- Mossman, Charles E, et al, 1998. "An Empirical Comparison of Bankruptcy Models," The Financial Review, Eastern Finance Association, vol. 33(2), pages 35-53, May.
- Altman, Edward I., 1984. "The success of business failure prediction models : An international survey," Journal of Banking & Finance, Elsevier, vol. 8(2), pages 171-198, June.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Stefanita Susu, 2014. "Analysis Model Using Robu Mironiuc In Predicting Risk Of Bankruptcy Romanian Companies," Annals - Economy Series, Constantin Brancusi University, Faculty of Economics, vol. 4, pages 80-86, August.
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- 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.
- S. Balcaen & H. Ooghe, 2004. "35 years of studies on business failure: an overview of the classical statistical methodologiesand their related problems," Working Papers of Faculty of Economics and Business Administration, Ghent University, Belgium 04/248, Ghent University, Faculty of Economics and Business Administration.
- 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.
- 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.
- Onofrei, Mihaela & Lupu, Dan, 2014. "The modelling of forecasting the bankruptcy in Romania," MPRA Paper 95511, University Library of Munich, Germany.
- 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.
- 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.
- du Jardin, Philippe & Severin, Eric, 2011. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," MPRA Paper 39935, University Library of Munich, Germany, revised 03 Apr 2012.
- 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.
- Laitinen, Erkki K., 2007. "Classification accuracy and correlation: LDA in failure prediction," European Journal of Operational Research, Elsevier, vol. 183(1), pages 210-225, November.
- Sami Ben Jabeur & Youssef Fahmi, 2014. "Les modèles de prévision de la défaillance des entreprises françaises : une approche comparative," Working Papers 2014-317, Department of Research, Ipag Business School.
- 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.
- John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2008.
"In Search of Distress Risk,"
Journal of Finance, American Finance Association, vol. 63(6), pages 2899-2939, December.
- John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2005. "In Searach of Distress Risk," Harvard Institute of Economic Research Working Papers 2081, Harvard - Institute of Economic Research.
- Campbell, John Y. & Hilscher, Jens & Szilagyi, Jan, 2005. "In search of distress risk," Discussion Paper Series 1: Economic Studies 2005,27, Deutsche Bundesbank.
- Szilagyi, Jan & Hilscher, Jens & Campbell, John, 2008. "In Search of Distress Risk," Scholarly Articles 3199070, Harvard University Department of Economics.
- John Y. Campbell & Jens Hilscher & Jan Szilagyi, 2006. "In Search of Distress Risk," NBER Working Papers 12362, National Bureau of Economic Research, Inc.
- Amin Jan & Maran Marimuthu & Muhammad Kashif Shad & Haseeb ur-Rehman & Muhammad Zahid & Ahmad Ali Jan, 2019. "Bankruptcy profile of the Islamic and conventional banks in Malaysia: a post-crisis period analysis," Economic Change and Restructuring, Springer, vol. 52(1), pages 67-87, February.
- Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
- du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
- du Jardin, Philippe, 2012. "The influence of variable selection methods on the accuracy of bankruptcy prediction models," MPRA Paper 44383, University Library of Munich, Germany.
- du Jardin, Philippe, 2009. "Bankruptcy prediction models: How to choose the most relevant variables?," MPRA Paper 44380, University Library of Munich, Germany.
- Bose, Indranil & Pal, Raktim, 2006. "Predicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach," European Journal of Operational Research, Elsevier, vol. 174(2), pages 959-982, October.
- David Alaminos & Agustín del Castillo & Manuel Ángel Fernández, 2016. "A Global Model for Bankruptcy Prediction," PLOS ONE, Public Library of Science, vol. 11(11), pages 1-18, November.
- 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.
- du Jardin, Philippe, 2008. "Bankruptcy prediction and neural networks: The contribution of variable selection methods," MPRA Paper 44384, University Library of Munich, Germany.
More about this item
Keywords
bankruptcy; MDA; symptoms; predicting models; literature review;All these keywords.
JEL classification:
- M41 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Accounting - - - Accounting
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:tdt:annals:v:xix:y:2013:p:114-121. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Ramona Violeta Vasilescu (email available below). General contact details of provider: https://edirc.repec.org/data/fettiro.html .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.