Forecasting financial failure using a Kohonen map: a comparative study to improve bankruptcy model over time

Citations

Cited by:

1. 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.
2. Ángel Beade & Manuel Rodríguez & José Santos, 2024. "Business failure prediction models with high and stable predictive power over time using genetic programming," Operational Research, Springer, vol. 24(3), pages 1-41, September.
3. Tomasz Korol, 2018. "The Implementation of Fuzzy Logic in Forecasting Financial Ratios," Contemporary Economics, University of Economics and Human Sciences in Warsaw., vol. 12(2), June.
4. Kizilaslan, Recep & Freund, Steven & Iseri, Ali, 2016. "A data analytic approach to forecasting daily stock returns in an emerging marketAuthor-Name: Oztekin, Asil," European Journal of Operational Research, Elsevier, vol. 253(3), pages 697-710.
5. Youssef Zizi & Amine Jamali-Alaoui & Badreddine El Goumi & Mohamed Oudgou & Abdeslam El Moudden, 2021. "An Optimal Model of Financial Distress Prediction: A Comparative Study between Neural Networks and Logistic Regression," Risks, MDPI, vol. 9(11), pages 1-24, November.
6. Sevim, Cuneyt & Oztekin, Asil & Bali, Ozkan & Gumus, Serkan & Guresen, Erkam, 2014. "Developing an early warning system to predict currency crises," European Journal of Operational Research, Elsevier, vol. 237(3), pages 1095-1104.
7. du Jardin, Philippe, 2015. "Bankruptcy prediction using terminal failure processes," European Journal of Operational Research, Elsevier, vol. 242(1), pages 286-303.
8. Tomasz Korol, 2020. "Assessment of Trajectories of Non-bankrupt and Bankrupt Enterprises," European Research Studies Journal, European Research Studies Journal, vol. 0(4), pages 1113-1135.
9. Yehui Tong & Ramon Saladrigues, 2022. "An analysis of factors affecting the profits of new firms in Spain: Evidence from the food industry," Agricultural Economics, Czech Academy of Agricultural Sciences, vol. 68(1), pages 28-38.
10. Sami Ben Jabeur & Nicolae Stef & Pedro Carmona, 2023. "Bankruptcy Prediction using the XGBoost Algorithm and Variable Importance Feature Engineering," Computational Economics, Springer;Society for Computational Economics, vol. 61(2), pages 715-741, February.
11. Ángel Beade & Manuel Rodríguez & José Santos, 2024. "Multiperiod Bankruptcy Prediction Models with Interpretable Single Models," Computational Economics, Springer;Society for Computational Economics, vol. 64(3), pages 1357-1390, September.
12. Zeineb Affes & Rania Hentati-Kaffel, 2019. "Predicting US Banks Bankruptcy: Logit Versus Canonical Discriminant Analysis," Computational Economics, Springer;Society for Computational Economics, vol. 54(1), pages 199-244, June.
13. Pedro Duarte Silva, A., 2017. "Optimization approaches to Supervised Classification," European Journal of Operational Research, Elsevier, vol. 261(2), pages 772-788.
14. 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.
15. Man Ha & Christopher Gan & Cuong Nguyen & Patricia Anthony, 2021. "Self-Organising (Kohonen) Maps for the Vietnam Banking Industry," JRFM, MDPI, vol. 14(10), pages 1-18, October.
16. 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.
17. David Veganzones, 2022. "Corporate failure prediction using threshold‐based models," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 41(5), pages 956-979, August.
18. Nyitrai, Tamás, 2014. "Növelhető-e a csőd-előrejelző modellek előre jelző képessége az új klasszifikációs módszerek nélkül? [Can the predictive capacity of bankruptcy forecasting models be increased without new classific," Közgazdasági Szemle (Economic Review - monthly of the Hungarian Academy of Sciences), Közgazdasági Szemle Alapítvány (Economic Review Foundation), vol. 0(5), pages 566-585.
19. du Jardin, Philippe, 2021. "Forecasting corporate failure using ensemble of self-organizing neural networks," European Journal of Operational Research, Elsevier, vol. 288(3), pages 869-885.
20. Mengting Fan & Zan Mo & Qizhi Zhao & Zhouyang Liang, 2024. "Innovative Insights into Knowledge-Driven Financial Distress Prediction: a Comprehensive XAI Approach," Journal of the Knowledge Economy, Springer;Portland International Center for Management of Engineering and Technology (PICMET), vol. 15(3), pages 12554-12595, September.
21. Geng, Ruibin & Bose, Indranil & Chen, Xi, 2015. "Prediction of financial distress: An empirical study of listed Chinese companies using data mining," European Journal of Operational Research, Elsevier, vol. 241(1), pages 236-247.
22. Eric Séverin & David Veganzones, 2021. "Can earnings management information improve bankruptcy prediction models?," Annals of Operations Research, Springer, vol. 306(1), pages 247-272, November.
23. Ben Jabeur, Sami & Serret, Vanessa, 2023. "Bankruptcy prediction using fuzzy convolutional neural networks," Research in International Business and Finance, Elsevier, vol. 64(C).
24. R. J. Kuo & Y. S. Tseng & Zhen-Yao Chen, 2016. "Integration of fuzzy neural network and artificial immune system-based back-propagation neural network for sales forecasting using qualitative and quantitative data," Journal of Intelligent Manufacturing, Springer, vol. 27(6), pages 1191-1207, December.
25. Sami Ben Jabeur & Youssef Fahmi, 2018. "Forecasting financial distress for French firms: a comparative study," Empirical Economics, Springer, vol. 54(3), pages 1173-1186, May.
26. Jabeur, Sami Ben & Gharib, Cheima & Mefteh-Wali, Salma & Arfi, Wissal Ben, 2021. "CatBoost model and artificial intelligence techniques for corporate failure prediction," Technological Forecasting and Social Change, Elsevier, vol. 166(C).