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Corporate failure prediction in the European energy sector: A multicriteria approach and the effect of country characteristics

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Cited by:

  1. Yue Qiu & Jiabei He & Zhensong Chen & Yinhong Yao & Yi Qu, 2024. "A novel semisupervised learning method with textual information for financial distress prediction," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(7), pages 2478-2494, November.
  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. Katsafados, Apostolos G. & Leledakis, George N. & Panagiotou, Nikolaos P. & Pyrgiotakis, Emmanouil G., 2024. "Can central bankers’ talk predict bank stock returns? A machine learning approach," MPRA Paper 122899, University Library of Munich, Germany.
  4. Sebastian Klaudiusz Tomczak & Anna Skowrońska-Szmer & Jan Jakub Szczygielski, 2021. "Is It Possible to Make Money on Investing in Companies Manufacturing Solar Components? A Panel Data Approach," Energies, MDPI, vol. 14(12), pages 1-20, June.
  5. Silvia Angilella & Maria Rosaria Pappalardo, 2022. "Performance assessment of energy companies employing Hierarchy Stochastic Multi-Attribute Acceptability Analysis," Operational Research, Springer, vol. 22(1), pages 299-370, March.
  6. Wei Xu & Yuchen Pan & Wenting Chen & Hongyong Fu, 2019. "Forecasting Corporate Failure in the Chinese Energy Sector: A Novel Integrated Model of Deep Learning and Support Vector Machine," Energies, MDPI, vol. 12(12), pages 1-20, June.
  7. Sebastian Klaudiusz Tomczak & Anna Skowrońska-Szmer & Jan Jakub Szczygielski, 2020. "Is Investing in Companies Manufacturing Solar Components a Lucrative Business? A Decision Tree Based Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
  8. Diana Barro & Marco Corazza & Gianni Filograsso, 2023. "A ESG rating model for European SMEs using multi-criteria decision aiding," Working Papers 2023: 27, Department of Economics, University of Venice "Ca' Foscari".
  9. Koen W. de Bock, 2017. "The best of two worlds: Balancing model strength and comprehensibility in business failure prediction using spline-rule ensembles," Post-Print hal-01588059, HAL.
  10. Manthoulis, Georgios & Doumpos, Michalis & Zopounidis, Constantin & Galariotis, Emilios, 2020. "An ordinal classification framework for bank failure prediction: Methodology and empirical evidence for US banks," European Journal of Operational Research, Elsevier, vol. 282(2), pages 786-801.
  11. Zoltán Csedő & József Magyari & Máté Zavarkó, 2022. "Dynamic Corporate Governance, Innovation, and Sustainability: Post-COVID Period," Sustainability, MDPI, vol. 14(6), pages 1-21, March.
  12. Salwa Kessioui & Michalis Doumpos & Constantin Zopounidis, 2023. "A Bibliometric Overview of the State-of-the-Art in Bankruptcy Prediction Methods and Applications," World Scientific Book Chapters, in: Emilios Galariotis & Alexandros Garefalakis & Christos Lemonakis & Marios Menexiadis & Constantin Zo (ed.), Governance and Financial Performance Current Trends and Perspectives, chapter 6, pages 123-153, World Scientific Publishing Co. Pte. Ltd..
  13. Lifang Zhang & Mohammad Zoynul Abedin & Zhenkun Liu, 2024. "Incorporating media news to predict financial distress: Case study on Chinese listed companies," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 43(5), pages 1374-1398, August.
  14. Sebastian Klaudiusz Tomczak, 2019. "Comparison of the Financial Standing of Companies Generating Electricity from Renewable Sources and Fossil Fuels: A New Hybrid Approach," Energies, MDPI, vol. 12(20), pages 1-20, October.
  15. 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.
  16. Katsafados, Apostolos G. & Androutsopoulos, Ion & Chalkidis, Ilias & Fergadiotis, Manos & Leledakis, George N. & Pyrgiotakis, Emmanouil G., 2020. "Textual Information and IPO Underpricing: A Machine Learning Approach," MPRA Paper 103813, University Library of Munich, Germany.
  17. Apostolos G. Katsafados & Dimitris Anastasiou, 2024. "Short-term prediction of bank deposit flows: do textual features matter?," Annals of Operations Research, Springer, vol. 338(2), pages 947-972, July.
  18. Koen W. de Bock & Kristof Coussement & Stefan Lessmann, 2020. "Cost-sensitive business failure prediction when misclassification costs are uncertain: A heterogeneous ensemble selection approach," Post-Print hal-02863245, HAL.
  19. Borchert, Philipp & Coussement, Kristof & De Caigny, Arno & De Weerdt, Jochen, 2023. "Extending business failure prediction models with textual website content using deep learning," European Journal of Operational Research, Elsevier, vol. 306(1), pages 348-357.
  20. 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.
  21. Flori, Andrea & Borghesi, Simone & Marin, Giovanni, 2024. "The environmental-financial performance nexus of EU ETS firms: A quantile regression approach," Energy Economics, Elsevier, vol. 131(C).
  22. Katsafados, Apostolos G. & Leledakis, George N. & Pyrgiotakis, Emmanouil G. & Androutsopoulos, Ion & Fergadiotis, Manos, 2024. "Machine learning in bank merger prediction: A text-based approach," European Journal of Operational Research, Elsevier, vol. 312(2), pages 783-797.
  23. Mai, Feng & Tian, Shaonan & Lee, Chihoon & Ma, Ling, 2019. "Deep learning models for bankruptcy prediction using textual disclosures," European Journal of Operational Research, Elsevier, vol. 274(2), pages 743-758.
  24. Makridou, Georgia & Doumpos, Michalis & Galariotis, Emilios, 2019. "The financial performance of firms participating in the EU emissions trading scheme," Energy Policy, Elsevier, vol. 129(C), pages 250-259.
  25. 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.
  26. Eskantar, Marianna & Zopounidis, Constantin & Doumpos, Michalis & Galariotis, Emilios & Guesmi, Khaled, 2024. "Navigating ESG complexity: An in-depth analysis of sustainability criteria, frameworks, and impact assessment," International Review of Financial Analysis, Elsevier, vol. 95(PA).
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