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A neural network for classifying the financial health of a firm
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- 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.
- du Jardin, Philippe & Severin, Eric, 2011. "Forecasting financial failure using a Kohonen map: A comparative study to improve model stability over time," MPRA Paper 39935, University Library of Munich, Germany, revised 03 Apr 2012.
- 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.
- Haider A. Khan, 2002. "Can Banks Learn to Be Rational?," CIRJE F-Series CIRJE-F-151, CIRJE, Faculty of Economics, University of Tokyo.
- Davalos, Sergio & Gritta, Richard D. & Adrangi, Bahram, 2007. "Deriving Rules for Forecasting Air Carrier Financial Stress and Insolvency: A Genetic Algorithm Approach," Journal of the Transportation Research Forum, Transportation Research Forum, vol. 46(2).
- 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.
- 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.
- du Jardin, Philippe & Séverin, Eric, 2011. "Predicting corporate bankruptcy using a self-organizing map: An empirical study to improve the forecasting horizon of a financial failure model," MPRA Paper 44262, University Library of Munich, Germany.
- 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.
- 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.
- Ali Taghi-Molla & Masoud Rabbani & Mohammad Hosein Karimi Gavareshki & Ehsan Dehghani, 2020. "Safety improvement in a gas refinery based on resilience engineering and macro-ergonomics indicators: a Bayesian network–artificial neural network approach," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(3), pages 641-654, June.
- 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.
- Mselmi, Nada & Lahiani, Amine & Hamza, Taher, 2017. "Financial distress prediction: The case of French small and medium-sized firms," International Review of Financial Analysis, Elsevier, vol. 50(C), pages 67-80.
- 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.
- Di Vaio, Assunta & Palladino, Rosa & Hassan, Rohail & Escobar, Octavio, 2020.
"Artificial intelligence and business models in the sustainable development goals perspective: A systematic literature review,"
Journal of Business Research, Elsevier, vol. 121(C), pages 283-314.
- A. Di Vaio & R. Palladino & R. Hassan & O. Escobar, 2020. "Artificial Intelligence and Business Models in the Sustainable Development Goals Perspective: A Systematic Literature Review," Post-Print hal-04457122, HAL.
- Baesens, Bart & Viaene, Stijn & Van den Poel, Dirk & Vanthienen, Jan & Dedene, Guido, 2002. "Bayesian neural network learning for repeat purchase modelling in direct marketing," European Journal of Operational Research, Elsevier, vol. 138(1), pages 191-211, April.
- Montagno, Ray & Sexton, Randall S. & Smith, Brien N., 2002. "Using neural networks for identifying organizational improvement strategies," European Journal of Operational Research, Elsevier, vol. 142(2), pages 382-395, October.
- Roy Cerqueti & Francesca Pampurini & Annagiulia Pezzola & Anna Grazia Quaranta, 2022. "Dangerous liasons and hot customers for banks," Review of Quantitative Finance and Accounting, Springer, vol. 59(1), pages 65-89, July.
- Javed Iqbal & Furrukh Bashir & Rashid Ahmad & Hina Arshad, 2022. "Predicting Bankruptcy through Neural Network:Case of PSX Listed Companies," iRASD Journal of Management, International Research Alliance for Sustainable Development (iRASD), vol. 4(2), pages 299-315, june.
- Davis, Jefferson T. & Massey, Anne P. & Lovell, Ronald E. R., 1997. "Supporting a complex audit judgment task: An expert network approach," European Journal of Operational Research, Elsevier, vol. 103(2), pages 350-372, December.
- Cerqueti, Roy & Pampurini, Francesca & Quaranta, Anna Grazia & Storani, Saverio, 2024. "Risk transmission, systemic fragility of banks’ interacting customers and credit worthiness assessment," Finance Research Letters, Elsevier, vol. 62(PA).
- Akkoç, Soner, 2012. "An empirical comparison of conventional techniques, neural networks and the three stage hybrid Adaptive Neuro Fuzzy Inference System (ANFIS) model for credit scoring analysis: The case of Turkish cred," European Journal of Operational Research, Elsevier, vol. 222(1), pages 168-178.
- Malhotra, Rashmi & Malhotra, D. K., 2003. "Evaluating consumer loans using neural networks," Omega, Elsevier, vol. 31(2), pages 83-96, April.
- Stijn Viaene & Bart Baesens & Dirk Van den Poel & Guido Dedene & Jan Vanthienen, 2001. "Wrapped input selection using multilayer perceptrons for repeat‐purchase modeling in direct marketing," Intelligent Systems in Accounting, Finance and Management, John Wiley & Sons, Ltd., vol. 10(2), pages 115-126, June.
- Dorota Witkowska, 2006. "Discrete Choice Model Application to the Credit Risk Evaluation," International Advances in Economic Research, Springer;International Atlantic Economic Society, vol. 12(1), pages 33-42, February.
- Chakraborty, Chiranjit & Joseph, Andreas, 2017. "Machine learning at central banks," Bank of England working papers 674, Bank of England.
- 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.
- Sajad Abdipour & Ahmad Nasseri & Mojtaba Akbarpour & Hossein Parsian & Shahrzad Zamani, 2013. "Integrating Neural Network and Colonial Competitive Algorithm: A New Approach for Predicting Bankruptcy in Tehran Security Exchange," Asian Economic and Financial Review, Asian Economic and Social Society, vol. 3(11), pages 1528-1539, November.
- Antonio Blanco-Oliver & Ana Irimia-Dieguez & María Oliver-Alfonso & Nicholas Wilson, 2015. "Systemic Sovereign Risk and Asset Prices: Evidence from the CDS Market, Stressed European Economies and Nonlinear Causality Tests," Czech Journal of Economics and Finance (Finance a uver), Charles University Prague, Faculty of Social Sciences, vol. 65(2), pages 144-166, April.
- du Jardin, Philippe, 2008. "Bankruptcy prediction and neural networks: The contribution of variable selection methods," MPRA Paper 44384, University Library of Munich, Germany.
- Ravi Kumar, P. & Ravi, V., 2007. "Bankruptcy prediction in banks and firms via statistical and intelligent techniques - A review," European Journal of Operational Research, Elsevier, vol. 180(1), pages 1-28, July.
- fernández, María t. Tascón & gutiérrez, Francisco J. Castaño, 2012. "Variables y Modelos Para La Identificación y Predicción Del Fracaso Empresarial: Revisión de La Investigación Empírica Reciente," Revista de Contabilidad - Spanish Accounting Review, Elsevier, vol. 15(1), pages 7-58.
- Bose, Indranil & Pal, Raktim, 2006. "Predicting the survival or failure of click-and-mortar corporations: A knowledge discovery approach," European Journal of Operational Research, Elsevier, vol. 174(2), pages 959-982, October.
- Liang, Deron & Tsai, Chih-Fong & Lu, Hung-Yuan (Richard) & Chang, Li-Shin, 2020. "Combining corporate governance indicators with stacking ensembles for financial distress prediction," Journal of Business Research, Elsevier, vol. 120(C), pages 137-146.
- 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.
- Francesco Ciampi & Valentina Cillo & Fabio Fiano, 2020. "Combining Kohonen maps and prior payment behavior for small enterprise default prediction," Small Business Economics, Springer, vol. 54(4), pages 1007-1039, April.
- du Jardin, Philippe, 2010. "Predicting bankruptcy using neural networks and other classification methods: the influence of variable selection techniques on model accuracy," MPRA Paper 44375, University Library of Munich, Germany.
- Malhotra, Rashmi & Malhotra, D. K., 2002. "Differentiating between good credits and bad credits using neuro-fuzzy systems," European Journal of Operational Research, Elsevier, vol. 136(1), pages 190-211, January.
- Amélia Ferreira da Silva & José Henrique Brito & Mariline Lourenço & José Manuel Pereira, 2023. "Sustainability of Transport Sector Companies: Bankruptcy Prediction Based on Artificial Intelligence," Sustainability, MDPI, vol. 15(23), pages 1-13, December.