Bankruptcy prediction by generalized additive models

FINANCIAL RATIOS, DISCRIMINANT ANALYSIS AND THE PREDICTION OF CORPORATE BANKRUPTCY

Altman, E. I. (1968) · The Journal of Finance · doi:10.1111/j.1540-6261.1968.tb00843.x · Cited by 14,888 · see citing works

Generalized Additive Models

Hastie, T., & Tibshirani, R. (1986) · Statistical Science · doi:10.1214/ss/1177013604 · Cited by 12,575 · see citing works

Generalized Additive Models.

Brown, R. A., Hastie, T. J., & Tibshirani, R. J. (1991) · Biometrics · doi:10.2307/2532174 · Cited by 8,262 · see citing works

Pattern Recognition and Neural Networks

Ripley, B. D. (1996) · Cambridge University Press eBooks · doi:10.1017/cbo9780511812651 · Cited by 6,446 · see citing works

Financial Ratios and the Probabilistic Prediction of Bankruptcy

Ohlson, J. A. (1980) · Journal of Accounting Research · doi:10.2307/2490395 · Cited by 6,166 · see citing works

Financial Ratios As Predictors of Failure

Beaver, W. H. (1966) · Journal of Accounting Research · doi:10.2307/2490171 · Cited by 4,882 · see citing works

Assessing the Probability of Bankruptcy

Hillegeist, S. A., Keating, E. K., Cram, D. P., & Lundstedt, K. G. (2004) · Review of Accounting Studies · doi:10.1023/b:rast.0000013627.90884.b7 · Cited by 1,357 · see citing works

Managerial Applications of Neural Networks: The Case of Bank Failure Predictions

Tam, K. Y., & Kiang, M. Y. (1992) · Management Science · doi:10.1287/mnsc.38.7.926 · Cited by 1,122 · see citing works

Statistical Classification Methods in Consumer Credit Scoring: A Review

Hand, D. J., & Henley, W. E. (1997) · Journal of the Royal Statistical Society Series A: Statistics in Society · doi:10.1111/j.1467-985x.1997.00078.x · Cited by 1,042 · see citing works

Bankruptcy prediction using neural networks

Wilson, R. L., & Sharda, R. (1994) · Decision Support Systems · doi:10.1016/0167-9236(94)90024-8 · Cited by 727 · see citing works

Bankruptcy prediction for credit risk using neural networks: A survey and new results

Atiya, A. F. (2001) · IEEE Transactions on Neural Networks · doi:10.1109/72.935101 · Cited by 699 · see citing works

A survey of business failures with an emphasis on prediction methods and industrial applications

Dimitras, A. I., Zanakis, S. H., & Zopounidis, C. (1996) · European Journal of Operational Research · doi:10.1016/0377-2217(95)00070-4 · Cited by 591 · see citing works

An Introduction to Statistical Modelling.

Williams, D. A., & Dobson, A. J. (1984) · Biometrics · doi:10.2307/2530940 · Cited by 300 · see citing works

Neural network models and the prediction of bank bankruptcy

Tam, K. S. (1991) · Omega · doi:10.1016/0305-0483(91)90060-7 · Cited by 300 · see citing works

A barrier option framework for corporate security valuation

Brockman, P., & Turtle, H. J. (2003) · Journal of Financial Economics · doi:10.1016/s0304-405x(02)00260-x · Cited by 289 · see citing works

An International Survey of Business Failure Classification Models

Altman, E. I., & Narayanan, P. (1997) · Financial Markets Institutions and Instruments · doi:10.1111/1468-0416.00010 · Cited by 249 · see citing works

Introduction to Statistical Modelling

Dobson, A. J. (1983) · Springer eBooks · doi:10.1007/978-1-4899-3174-0 · Cited by 204 · see citing works

Benchmarking Quantitative Default Risk Models: A Validation Methodology

SOBEHART, J. R., Keenan, S. C., & Stein, R. M. (2000) · Cited by 167 · see citing works

A Multicriteria Discrimination Method for the Prediction of Financial Distress: The Case of Greece

Doumpos, M., & Zopounidis, C. (1999) · Multinational Finance Journal · doi:10.17578/3-2-1 · Cited by 94 · see citing works

A model of bankruptcy prediction

Bernhardsen, E. (2001) · BIBSYS Brage (BIBSYS (Norway)) · Cited by 62 · see citing works

Statistics and neural networks: advances at the interface

Kay, J., & Titterington, D. M. (2000) · Cited by 51 · see citing works

Statistics and Neural Networks

Rojas, R. (1996) · Springer eBooks · doi:10.1007/978-3-642-61068-4_9 · Cited by 12 · see citing works

Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI

Barredo Arrieta, A., Díaz-Rodríguez, N., Del Ser, J., Bennetot, A., Tabik, S., Barbado, A., Garcia, S., Gil-Lopez, S., Molina, D., Benjamins, R., et al. (2020) · Information Fusion · doi:10.1016/j.inffus.2019.12.012 · Cited by 10,423 · see citing works

Machine Learning in Financial Crisis Prediction: A Survey

Lin, W.-Y., Hu, Y., & Tsai, C. (2011) · IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) · doi:10.1109/tsmcc.2011.2170420 · Cited by 325 · see citing works

Comparative analysis of data mining methods for bankruptcy prediction

Olson, D. L., Delen, D., & Meng, Y. (2011) · Decision Support Systems · doi:10.1016/j.dss.2011.10.007 · Cited by 323 · see citing works

Applications of Explainable Artificial Intelligence in Finance—a systematic review of Finance, Information Systems, and Computer Science literature

Weber, P., Carl, K. V., & Hinz, O. (2024) · Management Review Quarterly · doi:10.1007/s11301-023-00320-0 · Cited by 292 · see citing works

Bankruptcy prediction using terminal failure processes

du Jardin, P. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2014.09.059 · Cited by 152 · see citing works

Predicting bankruptcy using neural networks and other classification methods: The influence of variable selection techniques on model accuracy

du Jardin, P. (2010) · Neurocomputing · doi:10.1016/j.neucom.2009.11.034 · Cited by 151 · see citing works

An empirical comparison of classification algorithms for mortgage default prediction: evidence from a distressed mortgage market

Fitzpatrick, T., & Mues, C. (2015) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.09.014 · Cited by 113 · see citing works

Using partial least squares and support vector machines for bankruptcy prediction

Yang, Z., You, W., & Ji, G. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.01.021 · Cited by 102 · see citing works

Dynamics of firm financial evolution and bankruptcy prediction

du Jardin, P. (2017) · Expert Systems with Applications · doi:10.1016/j.eswa.2017.01.016 · Cited by 103 · see citing works

Corporate financial distress an empirical analysis of distress risk

Outecheva, N. (2007) · Cited by 93 · see citing works

Intelligent data analysis approaches to churn as a business problem: a survey

García, D. L., Àngela Nebot, B., & Vellido, A. (2016) · Knowledge and Information Systems · doi:10.1007/s10115-016-0995-z · Cited by 77 · see citing works

Reconciling performance and interpretability in customer churn prediction using ensemble learning based on generalized additive models

Bock, K. W. D., & den Poel, D. V. (2012) · Expert Systems with Applications · doi:10.1016/j.eswa.2012.01.014 · Cited by 73 · see citing works

Ensemble classification based on generalized additive models

Bock, K. W. D., Coussement, K., & den Poel, D. V. (2010) · Computational Statistics & Data Analysis · doi:10.1016/j.csda.2009.12.013 · Cited by 71 · see citing works

Explaining Deep Learning Models for Tabular Data Using Layer-Wise Relevance Propagation

Ullah, I., Rios, A., Gala, V., & McKeever, S. (2021) · Applied Sciences · doi:10.3390/app12010136 · Cited by 81 · see citing works

Bankruptcy prediction of small and medium enterprises using a flexible binary generalized extreme value model

Calabrese, R., Marra, G., & Osmetti, S. A. (2013) · Journal of the Operational Research Society · doi:10.1057/jors.2015.64 · Cited by 69 · see citing works

Taking the Twists into Account: Predicting Firm Bankruptcy Risk with Splines of Financial Ratios

Giordani, P. E., Jacobson, T., von Schedvin, E. L., & Villani, M. (2014) · Journal of Financial and Quantitative Analysis · doi:10.1017/s0022109014000623 · Cited by 61 · see citing works

Impacts of Extreme Weather Events on Mortgage Risks and Their Evolution under Climate Change: A Case Study on Florida

Calabrese, R., Dombrowski, T., Mandel, A., Pace, R. K., & Zanin, L. (2021) · European Journal of Operational Research · doi:10.1016/j.ejor.2023.11.022 · Cited by 60 · see citing works

Bankruptcy prediction in Norway: a comparison study

Dakovic, R., Czado, C., & Berg, D. (2010) · Applied Economics Letters · doi:10.1080/13504850903299594 · Cited by 57 · see citing works

A Hybrid Model for Bankruptcy prediction Using Genetic Algorithm,Fuzzy C-Means and Mars

Martin, A., Gayathri, V., Saranya, G., Gayathri, P., & Venkatesan, P. (2011) · International Journal on Soft Computing · doi:10.5121/ijsc.2011.2102 · Cited by 55 · see citing works

Financial distress prediction of Islamic banks using tree-based stochastic techniques

Halteh, K., Kumar, K., & Gepp, A. (2018) · Managerial Finance · doi:10.1108/mf-12-2016-0372 · Cited by 54 · see citing works

A tuning method for the architecture of neural network models incorporating GAM and GA as applied to bankruptcy prediction

Jeong, C., Min, J. H., & Kim, M. (2011) · Expert Systems with Applications · doi:10.1016/j.eswa.2011.09.056 · Cited by 52 · see citing works

Which Characteristics Predict the Survival of Insolvent Firms? An SME Reorganization Prediction Model

Camacho‐Miñano, M., Vargas, M. J. S., & Pascual‐Ezama, D. (2013) · Journal of Small Business Management · doi:10.1111/jsbm.12076 · Cited by 52 · see citing works

A literature survey of corporate failure prediction models

Jones, S. (2023) · Journal of Accounting Literature · doi:10.1108/jal-08-2022-0086 · Cited by 49 · see citing works

Using a naive Bayesian classifier methodology for loan risk assessment

Krichene, A. (2017) · Journal of Economics Finance and Administrative Science · doi:10.1108/jefas-02-2017-0039 · Cited by 47 · see citing works

Solvency prediction for small and medium enterprises in banking

Figini, S., Bonelli, F., & Giovannini, E. (2017) · Decision Support Systems · doi:10.1016/j.dss.2017.08.001 · Cited by 45 · see citing works

A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value models

Andreeva, G., Calabrese, R., & Osmetti, S. (2014) · European Journal of Operational Research · doi:10.1016/j.ejor.2015.07.062 · Cited by 44 · see citing works

The JT Index as an Indicator of Financial Stability of Corporate Sector

Jakubík, P., & Teplý, P. (2011) · Prague Economic Papers · doi:10.18267/j.pep.394 · Cited by 38 · see citing works

Temporal-Spatial Distribution of Chlorophyll-a and Impacts of Environmental Factors in the Bohai Sea and Yellow Sea

Zhao, N., Zhang, G., Zhang, S., Bai, Y., Ali, S., & Zhang, J. (2019) · IEEE Access · doi:10.1109/access.2019.2950833 · Cited by 35 · see citing works

Long-range forecasting of intermittent streamflow

van Ogtrop, F., Vervoort, W., Heller, G. Z., Stasinopoulos, D., & Rigby, R. A. (2011) · Hydrology and earth system sciences · doi:10.5194/hess-15-3343-2011 · Cited by 35 · see citing works

Greybox XAI: A Neural-Symbolic learning framework to produce interpretable predictions for image classification

Bennetot, A., Franchi, G., Ser, J. D., Chatila, R., & Díaz-Rodríguez, N. (2022) · Knowledge-Based Systems · doi:10.1016/j.knosys.2022.109947 · Cited by 33 · see citing works

Financial risk assessment in shipping: a holistic machine learning based methodology

Clintworth, M., Lyridis, D. V., & Boulougouris, E. K. (2021) · Maritime Economics & Logistics · doi:10.1057/s41278-020-00183-2 · Cited by 33 · see citing works

Bankruptcy prediction of small- and medium-sized enterprises in Poland based on the LDA and SVM methods

Ptak-Chmielewska, A. (2021) · Statistics in Transition New Series · doi:10.21307/stattrans-2021-010 · Cited by 31 · see citing works

Statistical inference for generalized additive models: simultaneous confidence corridors and variable selection

Zheng, S., Liu, R., Yang, L., & Härdle, W. K. (2016) · Test · doi:10.1007/s11749-016-0480-8 · Cited by 31 · see citing works

Identifying hidden patterns in credit risk survival data using Generalised Additive Models

Djeundje, V. B., & Crook, J. N. (2019) · European Journal of Operational Research · doi:10.1016/j.ejor.2019.02.006 · Cited by 30 · see citing works

Analysis of influencing factors on soil Zn content using generalized additive model

Jiang, Y., Gao, W., Zhao, J., Chen, Q., Dong, L., Xu, C., Huang, L., & Ruan, L. (2018) · Scientific Reports · doi:10.1038/s41598-018-33745-9 · Cited by 24 · see citing works

Commodity demand forecasting using modulated rank reduction for humanitarian logistics planning

Fuqua, D., & Hespeler, S. C. (2022) · Expert Systems with Applications · doi:10.1016/j.eswa.2022.117753 · Cited by 24 · see citing works

Nonlinear relationships in bankruptcy prediction and their effect on the profitability of bankruptcy prediction models

Lohmann, C., Möllenhoff, S., & Ohliger, T. (2022) · Journal of Business Economics · doi:10.1007/s11573-022-01130-8 · Cited by 24 · see citing works

Variable selection in high‐dimensional regression: a nonparametric procedure for business failure prediction

Amendola, A., Giordano, F., Parrella, M. L., & Restaino, M. (2017) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.2240 · Cited by 24 · see citing works

The total cost of misclassification in credit scoring: A comparison of generalized linear models and generalized additive models

Lohmann, C., & Ohliger, T. (2018) · Journal of Forecasting · doi:10.1002/for.2545 · Cited by 19 · see citing works

Assessment of Financial Distress Conditions of Commercial Banks in Ethiopia: A Case study of Selected Private Commercial Banks

Gebreslassie, E. (2015) · Cited by 18 · see citing works

Bankruptcy prediction and the discriminatory power of annual reports: empirical evidence from financially distressed German companies

Lohmann, C., & Ohliger, T. (2019) · Journal of Business Economics · doi:10.1007/s11573-019-00938-1 · Cited by 17 · see citing works

Bankruptcy Risk Management of a Machine Builder

Телипенко, Е. В., & Zakharova, A. A. (2014) · Applied Mechanics and Materials · doi:10.4028/www.scientific.net/amm.682.617 · Cited by 16 · see citing works

Impacts of Strong ENSO Events on Fish Communities in an Overexploited Ecosystem in the South China Sea

Li, M., Xu, Y., Sun, M., Li, J., Zhou, X., Chen, Z., & Zhang, K. (2023) · Biology · doi:10.3390/biology12070946 · Cited by 16 · see citing works

CREDIT-RISK ASSESSMENT USING SUPPORT VECTORS MACHINE AND MULTILAYER NEURAL NETWORK MODELS: A COMPARATIVE STUDY CASE OF A TUNISIAN BANK

Karaa, A. (2012) · RePEc: Research Papers in Economics · Cited by 15 · see citing works

Generalized additive model with embedded variable selection for bankruptcy prediction: Prediction versus interpretation

Valencia, C., Cabrales, S. A., Garcia, L., Ramirez, J., & Calderona, D. (2019) · Cogent Economics & Finance · doi:10.1080/23322039.2019.1597956 · Cited by 14 · see citing works

Pricing credit derivatives under stochastic recovery in a hybrid model

Höcht, S., & Zagst, R. (2009) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.792 · Cited by 14 · see citing works

Bankruptcy prediction using data mining techniques

Wagle, M., Yang, Z., & Benslimane, Y. (2017) · International Conference of Information and Communication Technology for Embedded Systems (IC-ICTES) · doi:10.1109/ictemsys.2017.7958771 · Cited by 13 · see citing works

Nonlinear Relationships and Their Effect on the Bankruptcy Prediction

Lohmann, C., & Ohliger, T. (2017) · Schmalenbach Business Review · doi:10.1007/s41464-017-0034-y · Cited by 12 · see citing works

Modelling credit risk in the enterprise sector - further development of the SEBRA model

Bernhardsen, E., & Larsen, K. R. (2007) · NORA - Norwegian Open Research Archives · Cited by 12 · see citing works

Measuring Satisfaction with Transit and Car Trips with Use of One Logistic Regression Model

Papaioannou, D., & Martínez, L. (2016) · Transportation Research Record Journal of the Transportation Research Board · doi:10.3141/2543-11 · Cited by 11 · see citing works

Using A Neural Network-Based Methodology for Credit–Risk Evaluation of A Tunisian BankPreprint

Matoussi, H., & Krichene, A. (2008) · RePEc: Research Papers in Economics · Cited by 11 · see citing works

Loan Recovery Determinants -- A Pan-European StudyPreprint

HHcht, S., & Zagst, R. (2010) · SSRN Electronic Journal · doi:10.2139/ssrn.2443724 · Cited by 10 · see citing works

Forecasting Corporate Bankruptcy with an Ensemble of Classifiers

Deligianni, D., & Kotsiantis, S. B. (2012) · Lecture notes in computer science · doi:10.1007/978-3-642-30448-4_9 · Cited by 9 · see citing works

Model comparison for generalized linear models with dependent observations

Eguchi, S. (2017) · Econometrics and Statistics · doi:10.1016/j.ecosta.2017.04.003 · Cited by 8 · see citing works

Forecasting of Power Corporations’ Default Probability With Nonlinear Kalman Filtering

Rigatos, G. G., & Siano, P. (2016) · IEEE Systems Journal · doi:10.1109/jsyst.2016.2610320 · Cited by 8 · see citing works

Explaining Deep Learning Models for Structured Data using Layer-Wise Relevance PropagationPreprint

Ullah, I., Rios, A., Gala, V., & McKeever, S. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2011.13429 · Cited by 8 · see citing works

Lost in a black‐box? Interpretable machine learning for assessing Italian SMEs default

Crosato, L., Liberati, C., & Repetto, M. (2023) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.2803 · Cited by 7 · see citing works

A Comprehensive Review on Explainable AI Techniques, Challenges, and Future Scope

Patil, A. B., & Patil, M. (2023) · Lecture notes in networks and systems · doi:10.1007/978-981-99-3177-4_39 · Cited by 7 · see citing works

Using accounting‐based information on young firms to predict bankruptcy

Lohmann, C., & Ohliger, T. (2019) · Journal of Forecasting · doi:10.1002/for.2586 · Cited by 7 · see citing works

The prediction of corporate bankruptcy and Czech economy's financial stability through logit analysis

Jakubík, P., & Teplý, P. (2008) · Econstor (Econstor) · Cited by 7 · see citing works

Early Warning System for Bankruptcy: Bankruptcy Prediction

Aktan, S. (2012) · Repository KITopen (Karlsruhe Institute of Technology) · doi:10.5445/ir/1000025642 · Cited by 7 · see citing works

Riesgos financieros en el sector manufacturero del Ecuador

del Azuay, U., Orellana-Osorio, I. F., Tonon, L., del Azuay, U., Reyes, M., del Azuay, U., Pinos-Luzuriaga, L. G., del Azuay, U., Rodríguez, E. D. R. C., & del Azuay, U. (2020) · doi:10.33324/ceuazuay.131 · Cited by 6 · see citing works

Forecasting retained earnings of privately held companies with PCA and L1 regression

Bhat, H. S., & Zaelit, D. (2013) · Applied Stochastic Models in Business and Industry · doi:10.1002/asmb.1972 · Cited by 6 · see citing works

Comparison of generalised additive models and neural networks in applications: A systematic review

Doohan, J., Kook, L., & Burke, K. (2026) · Expert Systems with Applications · doi:10.1016/j.eswa.2025.131082 · Cited by 5 · see citing works

Hazai vállalkozások csődjének előrejelzése a csődeseményt megelőző egy, két, illetve három évvel korábbi pénzügyi beszámolók adatai alapján

Nyitrai, T. (2015) · Vezetéstudomány / Budapest Management Review · doi:10.14267/veztud.2015.05.06 · Cited by 5 · see citing works

Can Machine Learning Models Capture Correlations in Corporate Distresses?Preprint

Christoffersen, B., Matin, R., & Mølgaard, P. (2018) · SSRN Electronic Journal · doi:10.2139/ssrn.3273985 · Cited by 5 · see citing works

Interpretable Learning-to-Rank with Generalized Additive ModelsPreprint

Zhuang, H., Wang, X., Bendersky, M., Grushetsky, A., Wu, Y., Mitrichev, P., Sterling, E., Bell, N., Ravina, W., & Qian, H. (2020) · arXiv (Cornell University) · doi:10.48550/arxiv.2005.02553 · Cited by 5 · see citing works

Combining individual- and population-level data to develop a Bayesian parity-specific fertility projection model

Ellison, J., Berrington, A. M., Dodd, E., & Forster, J. J. (2023) · Journal of the Royal Statistical Society Series C (Applied Statistics) · doi:10.1093/jrsssc/qlad095 · Cited by 5 · see citing works

Revealing the structure of prediction models through feature interaction detection

Zhang, X., Zhang, H., Zhu, J., & Li, Z. (2021) · Knowledge-Based Systems · doi:10.1016/j.knosys.2021.107737 · Cited by 4 · see citing works

Modelling the Financial Failure of Romanian Stock Companies

Fejér-Király, G., Ágoston, N., & Varga, J. (2019) · Acta Universitatis Sapientiae Economics and Business · doi:10.1515/auseb-2019-0005 · Cited by 4 · see citing works

Estimación de la probabilidad de riesgo de quiebra en las empresas colombianas a partir de un modelo para eventos raros.

García, J. I. P., Castaño, M. L., & Bedoya, F. A. V. (2018) · Cuadernos de Administración · doi:10.11144/javeriana.cao30-54.eprqe · Cited by 4 · see citing works

Dinamikus pénzügyi mutatószámok alkalmazása a csődelőrejelzésben

Nyitrai, T. (2016) · doi:10.14267/phd.2016045 · Cited by 4 · see citing works

Designing Ensemble-Based Models Using Neural Networks and Temporal Financial Profiles to Forecast Firms’ Financial Failure

du Jardin, P. (2024) · Computational Economics · doi:10.1007/s10614-024-10579-4 · Cited by 3 · see citing works

Corporations’ Default Probability Forecasting Using the Derivative-Free Nonlinear Kalman Filter

Rigatos, G. G. (2017) · Intelligent systems reference library · doi:10.1007/978-3-319-52866-3_8 · Cited by 3 · see citing works

Külföldi csődelőrejelző módszerek szisztematikus irodalomelemzése

Ágoston, N. (2022) · Vezetéstudomány / Budapest Management Review · doi:10.14267/veztud.2022.01.06 · Cited by 3 · see citing works

BANK DEFAULT PREDICTION MODELS

van der Ploeg, S. (2010) · Cited by 3 · see citing works

Using accounting‐based and loan‐related information to estimate the cure probability of a defaulted company

Lohmann, C., & Ohliger, T. (2020) · European Financial Management · doi:10.1111/eufm.12279 · Cited by 3 · see citing works

Quantification of model risk that is caused by model misspecification

Seitshiro, M. B., & Mashele, H. P. (2020) · Journal of Applied Statistics · doi:10.1080/02664763.2020.1849055 · Cited by 3 · see citing works

A pénzügyi mutatók időbeli tendenciájának figyelembevétele logisztikus regresszióra épülő csődelőrejelző modellekben

Nyitrai, T., & Virág, M. (2017) · Statisztikai Szemle · doi:10.20311/stat2017.01.hu0005 · Cited by 3 · see citing works

Capital Structure and Monitoring Bank FailurePreprint

Baek, S., Balasubramanian, S. K., & Lee, K. Y. (2015) · SSRN Electronic Journal · Cited by 3 · see citing works

Sustainability of the Hungarian Social Cooperatives

Bozsik, S., Lipták, K., Szemán, J., & Musinszki, Z. (2022) · Eurasian studies in business and economics · doi:10.1007/978-3-030-94036-2_10 · Cited by 2 · see citing works

Modeling Frailty Correlated Defaults With Multivariate Latent FactorsPreprint

Christoffersen, B., & Matin, R. (2019) · SSRN Electronic Journal · doi:10.2139/ssrn.3339981 · Cited by 2 · see citing works

Privacy Estimation on Twitter: Modelling the Effect of Latent Topics on Privacy by Integrating XGBoost, Topic and Generalized Additive Models

Tillmann, A., Kqiku, L., Reinhardt, D., Weisser, C., Säfken, B., & Kneib, T. (2022) · IEEE Smart World Congress (SWC) · doi:10.1109/smartworld-uic-atc-scalcom-digitaltwin-pricomp-metaverse56740.2022.00365 · Cited by 1 · see citing works

A Quantification Approach of Changes in Firms' Financial Situation Using Neural Networks for Predicting Bankruptcy

du Jardin, P. (2024) · Journal of Forecasting · doi:10.1002/for.3227 · Cited by 1 · see citing works

Отбор факторов риска банкротства предприятия на основе метода главных компонент

Захарова, А. А., & Телипенко, Е. В. (2014) · Journal of Corporate Finance Research / Корпоративные Финансы · doi:10.17323/j.jcfr.2073-0438.8.1.2014.64-72 · Cited by 1 · see citing works

Análisis de cierre empresarial en el sector manufacturero de Ecuador, periodo 1901 - 2018

Orellana-Osorio, I. F., Pinos-Luzuriaga, L. G., Ordóñez, L. B. T., Reyes, M., & Rodríguez, E. D. R. C. (2020) · Ecos de Economía · doi:10.17230/ecos.2020.50.3 · Cited by 1 · see citing works

A Systematic Review of Enterprise Bankruptcy Forecasting Models

Kanyhin, S. (2023) · Business Inform · doi:10.32983/2222-4459-2023-10-149-161 · Cited by 1 · see citing works

Airline Performance PredictionPreprint

Gudmundsson, S. V. (2011) · SSRN Electronic Journal · Cited by 1 · see citing works

Simultaneous Confidence Corridors and Variable Selection for Generalized Additive ModelsPreprint

Zheng, S., Liu, R., Yang, L., & Härdle, W. K. (2014) · RePEc: Research Papers in Economics · doi:10.18452/4495 · Cited by 1 · see citing works

Comparison Studies of Hybrid and Non-hybrid Forecasting Models for Seasonal and Trend Time Series Data

Jeong, C., & Kim, M. (2013) · Journal of Intelligence and Information Systems · doi:10.13088/jiis.2013.19.1.001

A portfolio approach to improving market and credit risk management

Botha, M. (2009)

MODEL COMPARISON FOR DEPENDENT GENERALIZED LINEAR MODELPreprint

Eguchi, S. (2016) · arXiv (Cornell University)

Classification and Analysis of Management and Marketing Data

Facca, T. M. (2010) · doi:10.53846/goediss-3531

A Method of Pricing European Style Equity Options

Harris, D. E. (2014) · doi:10.33915/etd.5767

Through the crisis : UK SMEs performance during the 'credit crunch'

Ma, M. (2017) · ERA

A comparative analysis of the UK and Italian small businesses using Generalised Extreme Value modelsPreprint

Andreeva, G., Calabrese, R., & Osmetti, S. A. (2014) · RePEc: Research Papers in Economics · doi:10.48550/arxiv.1412.5351

Corporate Default Models: Empirical Evidence and Methodological Contributions

Christoffersen, B. (2019) · Econstor (Econstor)

Nonlinear and Semi-Parametric Modelling of Personal Loan Credit ScoringPreprint

Sopitpongstorn, N., Fenech, J.-P., & Silvapulle, P. (2013) · SSRN Electronic Journal · doi:10.2139/ssrn.2310402

Improving the predictive performance of longitudinal risk models for UK SMEs

Liang, H. (2020) · ERA · doi:10.7488/era/625

Valuation of initial margin and model risk

Seitshiro, M. B. (2020) · Boloka Institutional Repository (North-west University)

Bankruptcy prediction in Norway: a comparison study

Dakovic, R., Czado, C., & Berg, D. (2010) · Applied Economics Letters · doi:10.1080/13504850903299594 · Cited by 57 · see citing works

Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline

Pompe, P. P. M., & Bilderbeek, J. (2005) · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management · doi:10.1002/isaf.259 · Cited by 46 · see citing works

Prediction power of accounting-based bankruptcy prediction models : evidence from Dutch and Belgian public and large private firms

Bouwmeester, A. (2020)

Bankruptcy prediction: the influence of the year prior to failure selected for model building and the effects in a period of economic decline: Research Articles

Pompe, P. P. M., & Bilderbeek, J. (2005) · Intelligent systems in accounting, finance and management/Intelligent systems in accounting, finance & management · Cited by 1 · see citing works

The actual predictive power of bankruptcy models in terms of time use

Kuběnka, M., Honková, I., Sejkora, F., & Mlázovský, M. (2024) · Business and management · doi:10.3846/bm.2024.1302