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Introducing Recursive Partitioning for Financial Classification: The Case of Financial Distress

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Cited by:

  1. 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.
  2. Catherine Refait, 2000. "Estimation du risque de défaut par une modélisation stochastique du bilan : Application à des firmes industrielles françaises," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-03718527, HAL.
  3. Zeineb Affes & Rania Hentati-Kaffel, 2016. "Forecast bankruptcy using a blend of clustering and MARS model - Case of US banks," Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) halshs-01314553, HAL.
  4. 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.
  5. Novak, Michael P. & LaDue, Eddy L., 1999. "Application Of Recursive Partitioning To Agricultural Credit Scoring," Journal of Agricultural and Applied Economics, Southern Agricultural Economics Association, vol. 31(1), pages 1-14, April.
  6. Misund, Bård, 2015. "Financial Ratios and Prediction on Corporate Bankruptcy in the Atlantic Salmon Industry," UiS Working Papers in Economics and Finance 2015/9, University of Stavanger.
  7. Llano Monelos Pablo De & Piñeiro Sánchez Carlos & Rodríguez López Manuel, 2014. "DEA as a business failure prediction tool. Application to the case of galician SMEs," Contaduría y Administración, Accounting and Management, vol. 59(2), pages 65-96, abril-jun.
  8. Juan Laborda & Seyong Ryoo, 2021. "Feature Selection in a Credit Scoring Model," Mathematics, MDPI, vol. 9(7), pages 1-22, March.
  9. Suzan Hol, 2006. "The influence of the business cycle on bankruptcy probability," Discussion Papers 466, Statistics Norway, Research Department.
  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. Natalia Nehrebecka, 2016. "Approach to the assessment of credit risk for non-financial corporations. Evidence from Poland," IFC Bulletins chapters, in: Bank for International Settlements (ed.), Combining micro and macro data for financial stability analysis, volume 41, Bank for International Settlements.
  12. Laborda, Ricardo & Laborda, Juan, 2017. "Can tree-structured classifiers add value to the investor?," Finance Research Letters, Elsevier, vol. 22(C), pages 211-226.
  13. Ruey-Ching Hwang & K. F. Cheng & Jack C. Lee, 2007. "A semiparametric method for predicting bankruptcy," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 26(5), pages 317-342.
  14. Novak, Michael P. & LaDue, Eddy L., 1997. "Introducing Recursive Partitioning To Agricultural Credit Scoring," Working Papers 127878, Cornell University, Department of Applied Economics and Management.
  15. 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.
  16. Situm Mario, 2014. "Inability of Gearing-Ratio as Predictor for Early Warning Systems," Business Systems Research, Sciendo, vol. 5(2), pages 23-45, September.
  17. Kim, Soo Y. & Upneja, Arun, 2014. "Predicting restaurant financial distress using decision tree and AdaBoosted decision tree models," Economic Modelling, Elsevier, vol. 36(C), pages 354-362.
  18. 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.
  19. Md Jahidur Rahman & Hongtao Zhu, 2023. "Predicting accounting fraud using imbalanced ensemble learning classifiers – evidence from China," Accounting and Finance, Accounting and Finance Association of Australia and New Zealand, vol. 63(3), pages 3455-3486, September.
  20. Jordan, Jeffrey L., 1998. "Georgia Water Series -- Issue 3: Evaluating Water System Financial Performance And Financing Options," Faculty Series 16712, University of Georgia, Department of Agricultural and Applied Economics.
  21. 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.
  22. Jiaming Liu & Chong Wu, 2017. "Dynamic forecasting of financial distress: the hybrid use of incremental bagging and genetic algorithm—empirical study of Chinese listed corporations," Risk Management, Palgrave Macmillan, vol. 19(1), pages 32-52, February.
  23. Bräuning, Michael & Malikkidou, Despo & Scricco, Giorgio & Scalone, Stefano, 2019. "A new approach to Early Warning Systems for small European banks," Working Paper Series 2348, European Central Bank.
  24. 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.
  25. Abdelghani Maddi, 2018. "Analyse scientométrique de la crise économique," CEPN Working Papers 2018-08, Centre d'Economie de l'Université de Paris Nord.
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  27. 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.
  28. De Bock, Koen W. & Coussement, Kristof & Lessmann, Stefan, 2020. "Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach," European Journal of Operational Research, Elsevier, vol. 285(2), pages 612-630.
  29. 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.
  30. Marialuisa Restaino & Marco Bisogno, 2019. "A Business Failure Index Using Rank Transformation," International Journal of Economics and Finance, Canadian Center of Science and Education, vol. 11(1), pages 56-65, January.
  31. Bastos, Joao, 2007. "Credit scoring with boosted decision trees," MPRA Paper 8034, University Library of Munich, Germany.
  32. Dimitras, A. I. & Zanakis, S. H. & Zopounidis, C., 1996. "A survey of business failures with an emphasis on prediction methods and industrial applications," European Journal of Operational Research, Elsevier, vol. 90(3), pages 487-513, May.
  33. 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.
  34. Esteban Alfaro Cortés & Matías Gámez Martínez & Noelia García Rubio, 2007. "Multiclass Corporate Failure Prediction by Adaboost.M1," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 13(3), pages 301-312, August.
  35. Fuertes, Ana-Maria & Kalotychou, Elena, 2007. "Optimal design of early warning systems for sovereign debt crises," International Journal of Forecasting, Elsevier, vol. 23(1), pages 85-100.
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  37. 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.
  38. Gang-Zhi Fan & Seow Eng Ong & Hian Chye Koh, 2006. "Determinants of House Price: A Decision Tree Approach," Urban Studies, Urban Studies Journal Limited, vol. 43(12), pages 2301-2315, November.
  39. An, Xudong & Deng, Yongheng & Gabriel, Stuart A., 2011. "Asymmetric information, adverse selection, and the pricing of CMBS," Journal of Financial Economics, Elsevier, vol. 100(2), pages 304-325, May.
  40. Nikita Moiseev & Aleksander Sorokin & Natalya Zvezdina & Alexey Mikhaylov & Lyubov Khomyakova & Mir Sayed Shah Danish, 2021. "Credit Risk Theoretical Model on the Base of DCC-GARCH in Time-Varying Parameters Framework," Mathematics, MDPI, vol. 9(19), pages 1-12, September.
  41. Min Zhu & David Philpotts & Maxwell J Stevenson, 2012. "The benefits of tree-based models for stock selection," Journal of Asset Management, Palgrave Macmillan, vol. 13(6), pages 437-448, December.
  42. Dumitru-Iulian NASTAC & Alexandru ISAIC-MANIU & Irina-Maria DRAGAN, 2017. "Analyzing the Profitability Performance of SMEs Using a Neural Model," ECONOMIC COMPUTATION AND ECONOMIC CYBERNETICS STUDIES AND RESEARCH, Faculty of Economic Cybernetics, Statistics and Informatics, vol. 51(4), pages 55-71.
  43. Paolo Angelis & Fulvio Gismondi & Riccardo Ottaviani, 1994. "A non-parametric statistical model for the control of Italian insurance companies," Decisions in Economics and Finance, Springer;Associazione per la Matematica, vol. 17(1), pages 69-84, March.
  44. Tamás Kristóf & Miklós Virág, 2020. "A Comprehensive Review of Corporate Bankruptcy Prediction in Hungary," JRFM, MDPI, vol. 13(2), pages 1-20, February.
  45. Maurice Peat, 2001. "Bankruptcy Probability: A Theoretical and Empirical Examination," PhD Thesis, Finance Discipline Group, UTS Business School, University of Technology, Sydney, number 20, July-Dece.
  46. Jie Sun & Mengjie Zhou & Wenguo Ai & Hui Li, 2019. "Dynamic prediction of relative financial distress based on imbalanced data stream: from the view of one industry," Risk Management, Palgrave Macmillan, vol. 21(4), pages 215-242, December.
  47. Josep M. Argilés, 1998. "Accounting information and the prediction of farm viability," Economics Working Papers 277, Department of Economics and Business, Universitat Pompeu Fabra.
  48. 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.
  49. William H. Beaver & Stefano Cascino & Maria Correia & Maureen F. McNichols, 2019. "Group Affiliation and Default Prediction," Management Science, INFORMS, vol. 65(8), pages 3559-3584, August.
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  53. Li-Chiu Chi & Tseng-Chung Tang, 2006. "Bankruptcy Prediction: Application of Logit Analysis in Export Credit Risks," Australian Journal of Management, Australian School of Business, vol. 31(1), pages 17-27, June.
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  56. David Feldman & Shulamith Gross, 2005. "Mortgage Default: Classification Trees Analysis," The Journal of Real Estate Finance and Economics, Springer, vol. 30(4), pages 369-396, June.
  57. Apostolos G. Christopoulos & Ioannis G. Dokas & Sofia Katsimardou & Konstantinos Vlachogiannatos, 2016. "Investigation of the relative efficiency for the Greek listed firms of the construction sector based on two DEA approaches for the period 2006–2012," Operational Research, Springer, vol. 16(3), pages 423-444, October.
  58. 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.
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