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Financial distress drivers in Brazilian banks: A dynamic slacks approach

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  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. Mattia Pellegrino & Gianfranco Lombardo & George Adosoglou & Stefano Cagnoni & Panos M. Pardalos & Agostino Poggi, 2024. "A Multi-Head LSTM Architecture for Bankruptcy Prediction with Time Series Accounting Data," Future Internet, MDPI, vol. 16(3), pages 1-20, February.
  3. Imad Bou-Hamad & Abdel Latef Anouze & Denis Larocque, 2017. "An integrated approach of data envelopment analysis and boosted generalized linear mixed models for efficiency assessment," Annals of Operations Research, Springer, vol. 253(1), pages 77-95, June.
  4. Gianfranco Lombardo & Mattia Pellegrino & George Adosoglou & Stefano Cagnoni & Panos M. Pardalos & Agostino Poggi, 2022. "Machine Learning for Bankruptcy Prediction in the American Stock Market: Dataset and Benchmarks," Future Internet, MDPI, vol. 14(8), pages 1-23, August.
  5. Yu, Hang & Zhang, Yahua & Zhang, Anming & Wang, Kun & Cui, Qiang, 2019. "A comparative study of airline efficiency in China and India: A dynamic network DEA approach," Research in Transportation Economics, Elsevier, vol. 76(C).
  6. Shaddady, Ali & Moore, Tomoe, 2019. "Investigation of the effects of financial regulation and supervision on bank stability: The application of CAMELS-DEA to quantile regressions," Journal of International Financial Markets, Institutions and Money, Elsevier, vol. 58(C), pages 96-116.
  7. Barboza, Flavio & Altman, Edward, 2024. "Predicting financial distress in Latin American companies: A comparative analysis of logistic regression and random forest models," The North American Journal of Economics and Finance, Elsevier, vol. 72(C).
  8. Wanke, Peter & Azad, Abul Kalam & Emrouznejad, Ali, 2018. "Efficiency in BRICS banking under data vagueness: A two-stage fuzzy approach," Global Finance Journal, Elsevier, vol. 35(C), pages 58-71.
  9. Zhiyong Li & Chen Feng & Ying Tang, 2022. "Bank efficiency and failure prediction: a nonparametric and dynamic model based on data envelopment analysis," Annals of Operations Research, Springer, vol. 315(1), pages 279-315, August.
  10. Jiang, Cuiqing & Zhou, Yiru & Chen, Bo, 2023. "Mining semantic features in patent text for financial distress prediction," Technological Forecasting and Social Change, Elsevier, vol. 190(C).
  11. Mohammed Mizanur Rahman & Badar Nadeem Ashraf & Changjun Zheng & Munni Begum, 2017. "Impact of Cost Efficiency on Bank Capital and the Cost of Financial Intermediation: Evidence from BRICS Countries," IJFS, MDPI, vol. 5(4), pages 1-18, December.
  12. Jorge Antunes & Peter Wanke & Thiago Fonseca & Yong Tan, 2023. "Do ESG Risk Scores Influence Financial Distress? Evidence from a Dynamic NDEA Approach," Sustainability, MDPI, vol. 15(9), pages 1-32, May.
  13. Tsionas, Mike G. & Andrikopoulos, Athanasios, 2020. "On a High-Dimensional Model Representation method based on Copulas," European Journal of Operational Research, Elsevier, vol. 284(3), pages 967-979.
  14. Amrizah Kamaluddin & Norhafizah Ishak & Nor Farizal Mohammed, 2019. "Financial Distress Prediction Through Cash Flow Ratios Analysis," International Journal of Financial Research, International Journal of Financial Research, Sciedu Press, vol. 10(3), pages 63-76, May.
  15. Fatemeh Boloori & Jafar Pourmahmoud, 2016. "A modified SBM-NDEA approach for the efficiency measurement in bank branches," Operational Research, Springer, vol. 16(2), pages 301-326, July.
  16. Paras Arora & Suman Saurabh, 2022. "Predicting distress: a post Insolvency and Bankruptcy Code 2016 analysis," Journal of Economics and Finance, Springer;Academy of Economics and Finance, vol. 46(3), pages 604-622, July.
  17. Adriel Martins de Freitas Branco & Alexandre Pereira Salgado Junior & Patrícia Benites Cava & Eduardo Falsarella Junior & Marco Antônio Alves de Souza Junior, 2017. "Efficiency of the Brazilian Banking System in 2014: A DEA-SBM Analysis," Journal of Applied Finance & Banking, SCIENPRESS Ltd, vol. 7(5), pages 1-2.
  18. Xiaobo Tang & Shixuan Li & Mingliang Tan & Wenxuan Shi, 2020. "Incorporating textual and management factors into financial distress prediction: A comparative study of machine learning methods," Journal of Forecasting, John Wiley & Sons, Ltd., vol. 39(5), pages 769-787, August.
  19. Thyago C. C. Nepomuceno & Ana Paula C. S. Costa, 2019. "Resource allocation with Time Series DEA applied to Brazilian Federal Saving banks," Economics Bulletin, AccessEcon, vol. 39(2), pages 1384-1392.
  20. Mohammad Nourani & Irene Wei Kiong Ting & Wen-Min Lu & Qian Long Kweh, 2019. "Capital Structure And Dynamic Performance: Evidence From Asean-5 Banks," The Singapore Economic Review (SER), World Scientific Publishing Co. Pte. Ltd., vol. 64(03), pages 495-516, June.
  21. Barbosa, Alexandro & Lima, Severino Cesário de & Brusca, Isabel, 2016. "Governance and efficiency in the Brazilian water utilities: A dynamic analysis in the process of universal access," Utilities Policy, Elsevier, vol. 43(PA), pages 82-96.
  22. Yu, Ming-Miin & Lin, Chung-I & Chen, Kuan-Chen & Chen, Li-Hsueh, 2021. "Measuring Taiwanese bank performance: A two-system dynamic network data envelopment analysis approach," Omega, Elsevier, vol. 98(C).
  23. Yi-Shu Wang & Xue Jiang & Zhen-Jia-Liu, 2016. "Bank Failure Prediction Models for the Developing and Developed Countries: Identifying the Economic Value Added for Predicting Failure," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 6(9), pages 522-533, September.
  24. Degl'Innocenti, Marta & Kourtzidis, Stavros A. & Sevic, Zeljko & Tzeremes, Nickolaos G., 2017. "Bank productivity growth and convergence in the European Union during the financial crisis," Journal of Banking & Finance, Elsevier, vol. 75(C), pages 184-199.
  25. Shailesh Rastogi & Kuldeep Singh & Jagjeevan Kanoujiya, 2024. "Impact of Shareholders’ Activism on the Performance of Banks in India: A Panel Data Application," Business Perspectives and Research, , vol. 12(1), pages 83-99, January.
  26. Wanke, Peter & Barros, C.P., 2017. "Efficiency thresholds and cost structure in Senegal airports," Journal of Air Transport Management, Elsevier, vol. 58(C), pages 100-112.
  27. Cristina Gutiérrez-López & Julio Abad-González, 2020. "Sustainability in the Banking Sector: A Predictive Model for the European Banking Union in the Aftermath of the Financial Crisis," Sustainability, MDPI, vol. 12(6), pages 1-25, March.
  28. Mohamed Rochdi Keffala, 2018. "Analyzing the effect of derivatives on the financial soundness of commercial banks in Italy: An approach based on the CAMELS framework," Review of Financial Economics, John Wiley & Sons, vol. 36(3), pages 267-283, July.
  29. 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.
  30. Ayoola Tajudeen John & Obokoh Lawrence Ogechukwu, 2018. "Corporate Governance and Financial Distress in the Banking Industry: Nigerian Experience," Journal of Economics and Behavioral Studies, AMH International, vol. 10(1), pages 182-193.
  31. Sumaira Ashraf & Elisabete G. S. Félix & Zélia Serrasqueiro, 2019. "Do Traditional Financial Distress Prediction Models Predict the Early Warning Signs of Financial Distress?," JRFM, MDPI, vol. 12(2), pages 1-17, April.
  32. Fukuyama, Hirofumi & Tsionas, Mike & Tan, Yong, 2024. "The impacts of innovation and trade openness on bank market power: The proposal of a minimum distance cost function approach and a causal structure analysis," European Journal of Operational Research, Elsevier, vol. 312(3), pages 1178-1194.
  33. Ali Meftah Gerged & Mohamed Marie & Israa Elbendary, 2022. "Estimating the Risk of Financial Distress Using a Multi-Layered Governance Criterion: Insights from Middle Eastern and North African Banks," JRFM, MDPI, vol. 15(12), pages 1-22, December.
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