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Corporate distress diagnosis: Comparisons using linear discriminant analysis and neural networks (the Italian experience)

Citations

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Cited by:

  1. BATRANCEA Ioan & BATRANCEA Larissa & STOIA Ioan, 2013. "Statistical Study On The Risk Of Bankruptcy In Bank," Revista Economica, Lucian Blaga University of Sibiu, Faculty of Economic Sciences, vol. 65(5), pages 18-30.
  2. Matthew Smith & Francisco Alvarez, 2022. "Predicting Firm-Level Bankruptcy in the Spanish Economy Using Extreme Gradient Boosting," Computational Economics, Springer;Society for Computational Economics, vol. 59(1), pages 263-295, January.
  3. Altunbas, Yener & Binici, Mahir & Gambacorta, Leonardo, 2018. "Macroprudential policy and bank risk," Journal of International Money and Finance, Elsevier, vol. 81(C), pages 203-220.
  4. Ali Namaki & Reza Eyvazloo & Shahin Ramtinnia, 2023. "A systematic review of early warning systems in finance," Papers 2310.00490, arXiv.org.
  5. Amarda Cano, 2020. "Evolution of Public Debt in Albania during 1990-2017 and its impact on the Economic Growth," European Journal of Marketing and Economics Articles, Revistia Research and Publishing, vol. 4, January -.
  6. B. Luppi & M. Marzo & E. Scorcu, 2007. "A credit risk model for Italian SMEs," Working Papers 600, Dipartimento Scienze Economiche, Universita' di Bologna.
  7. Kolari, James & Glennon, Dennis & Shin, Hwan & Caputo, Michele, 2002. "Predicting large US commercial bank failures," Journal of Economics and Business, Elsevier, vol. 54(4), pages 361-387.
  8. Gregory S. Crawford & Nicola Pavanini & Fabiano Schivardi, 2018. "Asymmetric Information and Imperfect Competition in Lending Markets," American Economic Review, American Economic Association, vol. 108(7), pages 1659-1701, July.
  9. Alessandri, Piergiorgio & Bottero, Margherita, 2020. "Bank lending in uncertain times," European Economic Review, Elsevier, vol. 128(C).
  10. Harlan Platt & Marjorie Platt, 2002. "Predicting corporate financial distress: Reflections on choice-based sample bias," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 26(2), pages 184-199, June.
  11. Arundina, Tika & Azmi Omar, Mohd. & Kartiwi, Mira, 2015. "The predictive accuracy of Sukuk ratings; Multinomial Logistic and Neural Network inferences," Pacific-Basin Finance Journal, Elsevier, vol. 34(C), pages 273-292.
  12. 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.
  13. Zhou, Fanyin & Fu, Lijun & Li, Zhiyong & Xu, Jiawei, 2022. "The recurrence of financial distress: A survival analysis," International Journal of Forecasting, Elsevier, vol. 38(3), pages 1100-1115.
  14. Ha-Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," EconomiX Working Papers 2015-1, University of Paris Nanterre, EconomiX.
  15. Modina, Michele & Pietrovito, Filomena & Gallucci, Carmen & Formisano, Vincenzo, 2023. "Predicting SMEs’ default risk: Evidence from bank-firm relationship data," The Quarterly Review of Economics and Finance, Elsevier, vol. 89(C), pages 254-268.
  16. Bárbara Díaz & Antonio Morillas, 2005. "Minería de datos y lógica difusa.Una aplicación al estudio de la rentabilidad económica de las empresas agroalimentarias en Andalucía," GE, Growth, Math methods 0512003, University Library of Munich, Germany.
  17. 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.
  18. Haider A. Khan, 2002. "Can Banks Learn to Be Rational?," CIRJE F-Series CIRJE-F-151, CIRJE, Faculty of Economics, University of Tokyo.
  19. Bertrand Hassani & Xin Zhao, 2014. "Reconsidering Corporate Ratings," Post-Print hal-01117683, HAL.
  20. Sarbjit Singh Oberoi & Sayan Banerjee, 2023. "Bankruptcy Prediction of Indian Banks Using Advanced Analytics," Economic Studies journal, Bulgarian Academy of Sciences - Economic Research Institute, issue 4, pages 22-41.
  21. Runchi Zhang & Zhiyi Qiu, 2020. "Optimizing hyper-parameters of neural networks with swarm intelligence: A novel framework for credit scoring," PLOS ONE, Public Library of Science, vol. 15(6), pages 1-35, June.
  22. Sun, Lili & Shenoy, Prakash P., 2007. "Using Bayesian networks for bankruptcy prediction: Some methodological issues," European Journal of Operational Research, Elsevier, vol. 180(2), pages 738-753, July.
  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. Dimitras, A. I. & Slowinski, R. & Susmaga, R. & Zopounidis, C., 1999. "Business failure prediction using rough sets," European Journal of Operational Research, Elsevier, vol. 114(2), pages 263-280, April.
  25. Pompe, Paul P.M. & Bilderbeek, Jan, 2005. "The prediction of bankruptcy of small- and medium-sized industrial firms," Journal of Business Venturing, Elsevier, vol. 20(6), pages 847-868, November.
  26. Wolfgang Karl Härdle & Dedy Dwi Prastyo & Christian Hafner, 2012. "Support Vector Machines with Evolutionary Feature Selection for Default Prediction," SFB 649 Discussion Papers SFB649DP2012-030, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
  27. Balcaen S. & Ooghe H., 2004. "Alternative methodologies in studies on business failure: do they produce better results than the classic statistical methods?," Vlerick Leuven Gent Management School Working Paper Series 2004-16, Vlerick Leuven Gent Management School.
  28. Yan Zhang & Peter Trubey, 2019. "Machine Learning and Sampling Scheme: An Empirical Study of Money Laundering Detection," Computational Economics, Springer;Society for Computational Economics, vol. 54(3), pages 1043-1063, October.
  29. Fougère, D. & Golfier, C. & Horny, G. & Kremp, E., 2013. "What has been the impact of the 2008 crisis on firms’ default? (in French)," Working papers 463, Banque de France.
  30. Fabio Panetta & Fabiano Schivardi & Matthew Shum, 2009. "Do Mergers Improve Information? Evidence from the Loan Market," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 41(4), pages 673-709, June.
  31. Greta Falavigna, 2006. "Models for Default Risk Analysis: Focus on Artificial Neural Networks, Model Comparisons, Hybrid Frameworks," CERIS Working Paper 200610, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
  32. 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.
  33. Francesco Ciampi & Alessandro Giannozzi & Giacomo Marzi & Edward I. Altman, 2021. "Rethinking SME default prediction: a systematic literature review and future perspectives," Scientometrics, Springer;Akadémiai Kiadó, vol. 126(3), pages 2141-2188, March.
  34. Jun Li & Junpeng Wu & Jiaquan Lin & Can Li & Huazhong Lu & Caixia Lin, 2022. "Nondestructive Identification of Litchi Downy Blight at Different Stages Based on Spectroscopy Analysis," Agriculture, MDPI, vol. 12(3), pages 1-17, March.
  35. Beynon, Malcolm J. & Peel, Michael J., 2001. "Variable precision rough set theory and data discretisation: an application to corporate failure prediction," Omega, Elsevier, vol. 29(6), pages 561-576, December.
  36. Zhang, Guoqiang & Y. Hu, Michael & Eddy Patuwo, B. & C. Indro, Daniel, 1999. "Artificial neural networks in bankruptcy prediction: General framework and cross-validation analysis," European Journal of Operational Research, Elsevier, vol. 116(1), pages 16-32, July.
  37. Dejan JOVANOVIĆ & Mirjana TODOROVIĆ & Milka GRBIĆ, 2017. "Financial Indicators As Predictors Of Illiquidity," Journal for Economic Forecasting, Institute for Economic Forecasting, vol. 0(1), pages 128-149, March.
  38. BARANGA, Laurentiu Paul & PANAIT, Iulian, 2018. "Estimating The Credit Risk Score For Non Bank Stock Exchange Intermediaries In The Eventuality Of Changeover To Euro Currency," Studii Financiare (Financial Studies), Centre of Financial and Monetary Research "Victor Slavescu", vol. 22(4), pages 25-40, December.
  39. Jens Leker & Gerhard Schewe, 1998. "Beurteilung des Kreditausfallrisikos im Firmenkundengeschàft der Banken," Schmalenbach Journal of Business Research, Springer, vol. 50(10), pages 877-891, October.
  40. 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.
  41. Haider A. Khan, 2004. "General Conclusions: From Crisis to a Global Political Economy of Freedom," Palgrave Macmillan Books, in: Global Markets and Financial Crises in Asia, chapter 9, pages 193-211, Palgrave Macmillan.
  42. Ha Thu Nguyen, 2015. "How is credit scoring used to predict default in China?," Working Papers hal-04133309, HAL.
  43. Parag C. Pendharkar, 2011. "Probabilistic Approaches For Credit Screening And Bankruptcy Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 18(4), pages 177-193, October.
  44. Bhanu Pratap Singh & Alok Kumar Mishra, 2016. "Re-estimation and comparisons of alternative accounting based bankruptcy prediction models for Indian companies," Financial Innovation, Springer;Southwestern University of Finance and Economics, vol. 2(1), pages 1-28, December.
  45. Virág, Miklós & Kristóf, Tamás, 2005. "Az első hazai csődmodell újraszámítása neurális hálók segítségével [Recalculation of the first Hungarian bankruptcy-prediction model using neural networks]," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(2), pages 144-162.
  46. 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.
  47. Altman, Edward I. & Saunders, Anthony, 1997. "Credit risk measurement: Developments over the last 20 years," Journal of Banking & Finance, Elsevier, vol. 21(11-12), pages 1721-1742, December.
  48. Hyytinen, Ari, 2003. "Information production and lending market competition," Journal of Economics and Business, Elsevier, vol. 55(3), pages 233-253.
  49. Philip Swicegood & Jeffrey A. Clark, 2001. "Off‐site monitoring systems for predicting bank underperformance: a comparison of neural networks, discriminant analysis, and professional human judgment," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(3), pages 169-186, September.
  50. 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.
  51. de Andres, Javier & Landajo, Manuel & Lorca, Pedro, 2005. "Forecasting business profitability by using classification techniques: A comparative analysis based on a Spanish case," European Journal of Operational Research, Elsevier, vol. 167(2), pages 518-542, December.
  52. Maurice Peat & Stewart Jones, 2012. "Using Neural Nets To Combine Information Sets In Corporate Bankruptcy Prediction," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 19(2), pages 90-101, April.
  53. Elisa Letizia & Fabrizio Lillo, 2017. "Corporate payments networks and credit risk rating," Papers 1711.07677, arXiv.org, revised Sep 2018.
  54. Sebastian Steinker & Mario Pesch & Kai Hoberg, 2016. "Inventory management under financial distress: an empirical analysis," International Journal of Production Research, Taylor & Francis Journals, vol. 54(17), pages 5182-5207, September.
  55. Batrancea Ioan & Bechis Liviu & Batrancea Larissa & Stoia Ioan, 2013. "Ratios Method - A Way Of Measuring The Local Government Performance," Annals of Faculty of Economics, University of Oradea, Faculty of Economics, vol. 1(2), pages 296-304, December.
  56. Arthur Charpentier & Emmanuel Flachaire & Antoine Ly, 2017. "Econom\'etrie et Machine Learning," Papers 1708.06992, arXiv.org, revised Mar 2018.
  57. 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.
  58. Forgione, Antonio Fabio & Migliardo, Carlo, 2018. "Forecasting distress in cooperative banks: The role of asset quality," International Journal of Forecasting, Elsevier, vol. 34(4), pages 678-695.
  59. Emilia Bonaccorsi di Patti & Anil Kashyap, 2017. "Which Banks Recover From Large Adverse Shocks?," NBER Working Papers 23654, National Bureau of Economic Research, Inc.
  60. Lucia Esposito & Davide Fantino & Yeji Sung, 2020. "The impact of TLTRO2 on the Italian credit market: some econometric evidence," Temi di discussione (Economic working papers) 1264, Bank of Italy, Economic Research and International Relations Area.
  61. Thomas, Lyn C., 2000. "A survey of credit and behavioural scoring: forecasting financial risk of lending to consumers," International Journal of Forecasting, Elsevier, vol. 16(2), pages 149-172.
  62. Benetton, Matteo & Fantino, Davide, 2021. "Targeted monetary policy and bank lending behavior," Journal of Financial Economics, Elsevier, vol. 142(1), pages 404-429.
  63. Greta Falavigna, 2008. "Nouveaux instruments d’évaluation pour le risque financier d’entreprise," CERIS Working Paper 200801, CNR-IRCrES Research Institute on Sustainable Economic Growth - Torino (TO) ITALY - former Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY.
  64. 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.
  65. Van Laere, Elisabeth & Baesens, Bart, 2010. "The development of a simple and intuitive rating system under Solvency II," Insurance: Mathematics and Economics, Elsevier, vol. 46(3), pages 500-510, June.
  66. Bardos, Mireille, 1998. "Detecting the risk of company failure at the Banque de France," Journal of Banking & Finance, Elsevier, vol. 22(10-11), pages 1405-1419, October.
  67. Bronzini, Raffaello & D’Ignazio, Alessio & Revelli, Davide, 2022. "Financial structure and bank relationships of Italian multinational firms," Journal of Multinational Financial Management, Elsevier, vol. 66(C).
  68. Adli Abouzeedan & Michael Busler, 2005. "ASPEM as the New Topographic Analysis Tool for Small and Medium-Sized Enterprises (SMEs) Performance Models Utilization," Journal of International Entrepreneurship, Springer, vol. 3(1), pages 53-70, January.
  69. Platt, Harlan D. & Platt, Marjorie B., 2006. "Understanding Differences Between Financial Distress and Bankruptcy," Review of Applied Economics, Lincoln University, Department of Financial and Business Systems, vol. 2(2), pages 1-17.
  70. Daniëls, H.A.M. & Kamp, B. & Verkooijen, W.J.H., 1997. "Application of Neural Networks to House Pricing and Bond Rating," Discussion Paper 1997-96, Tilburg University, Center for Economic Research.
  71. Sancho Salcedo‐Sanz & Mario DePrado‐Cumplido & María Jesús Segovia‐Vargas & Fernando Pérez‐Cruz & Carlos Bousoño‐Calzón, 2004. "Feature selection methods involving support vector machines for prediction of insolvency in non‐life insurance companies," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 12(4), pages 261-281, October.
  72. Kolari, James W. & López-Iturriaga, Félix J. & Sanz, Ivan Pastor, 2019. "Predicting European bank stress tests: Survival of the fittest," Global Finance Journal, Elsevier, vol. 39(C), pages 44-57.
  73. Adam Fadlalla & Chien-Hua Lin, 2001. "An Analysis of the Applications of Neural Networks in Finance," Interfaces, INFORMS, vol. 31(4), pages 112-122, August.
  74. Becchetti, Leonardo & Sierra, Jaime, 2003. "Bankruptcy risk and productive efficiency in manufacturing firms," Journal of Banking & Finance, Elsevier, vol. 27(11), pages 2099-2120, November.
  75. Peresetsky, A. A., 2011. "What factors drive the Russian banks license withdrawal," MPRA Paper 41507, University Library of Munich, Germany.
  76. Leonardo Gambacorta & Paolo Emilio Mistrulli, 2014. "Bank Heterogeneity and Interest Rate Setting: What Lessons Have We Learned since Lehman Brothers?," Journal of Money, Credit and Banking, Blackwell Publishing, vol. 46(4), pages 753-778, June.
  77. Evangelos C. Charalambakis, 2014. "On corporate financial distress prediction: what can we learn from private firms in a small open economy?," Working Papers 188, Bank of Greece.
  78. Gestel, Tony Van & Baesens, Bart & Suykens, Johan A.K. & Van den Poel, Dirk & Baestaens, Dirk-Emma & Willekens, Marleen, 2006. "Bayesian kernel based classification for financial distress detection," European Journal of Operational Research, Elsevier, vol. 172(3), pages 979-1003, August.
  79. 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.
  80. Paul P. M. Pompe & Jan Bilderbeek, 2005. "Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 13(2), pages 95-112, June.
  81. Lenzu, Simone & Manaresi, Francesco, 2018. "Do Marginal Products Differ from User Costs? Micro-Level Evidence from Italian Firms," Working Papers 276, The University of Chicago Booth School of Business, George J. Stigler Center for the Study of the Economy and the State.
  82. Eleonora Bartoloni & Maurizio Baussola, 2014. "Financial Performance in Manufacturing Firms: A Comparison Between Parametric and Non-Parametric Approaches," Business Economics, Palgrave Macmillan;National Association for Business Economics, vol. 49(1), pages 32-45, January.
  83. Khurshid Kiani & Terry Kastens, 2008. "Testing Forecast Accuracy of Foreign Exchange Rates: Predictions from Feed Forward and Various Recurrent Neural Network Architectures," Computational Economics, Springer;Society for Computational Economics, vol. 32(4), pages 383-406, November.
  84. 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.
  85. Bertrand Hassani & Xin Zhao, 2014. "Reconsidering Corporate Ratings," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) hal-01117683, HAL.
  86. Mramor, Dusan & Valentincic, Aljosa, 2003. "Forecasting the liquidity of very small private companies," Journal of Business Venturing, Elsevier, vol. 18(6), pages 745-771, November.
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  88. 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.
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