Predicting China’s SME Credit Risk in Supply Chain Financing by Logistic Regression, Artificial Neural Network and Hybrid Models
Download full text from publisher
References listed on IDEAS
- Jiancheng Jiang & Xuejun Jiang & Xinyuan Song, 2014. "Weighted composite quantile regression estimation of DTARCH models," Econometrics Journal, Royal Economic Society, vol. 17(1), pages 1-23, February.
- Edward Altman & Gabriele Sabato, 2005. "Effects of the New Basel Capital Accord on Bank Capital Requirements for SMEs," Journal of Financial Services Research, Springer;Western Finance Association, vol. 28(1), pages 15-42, October.
- Edward I. Altman & Gabriele Sabato, 2007. "Modelling Credit Risk for SMEs: Evidence from the U.S. Market," Abacus, Accounting Foundation, University of Sydney, vol. 43(3), pages 332-357.
- 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.
- Sopranzetti, Ben J., 1999. "Selling accounts receivable and the underinvestment problem," The Quarterly Review of Economics and Finance, Elsevier, vol. 39(2), pages 291-301.
- Chiara Pederzoli & Costanza Torricelli, 2010. "A parsimonious default prediction model for Italian SMEs," Centro Studi di Banca e Finanza (CEFIN) (Center for Studies in Banking and Finance) 10061, Universita di Modena e Reggio Emilia, Dipartimento di Economia "Marco Biagi".
- Gutiérrez, P.A. & Segovia-Vargas, M.J. & Salcedo-Sanz, S. & Hervás-Martínez, C. & Sanchis, A. & Portilla-Figueras, J.A. & Fernández-Navarro, F., 2010. "Hybridizing logistic regression with product unit and RBF networks for accurate detection and prediction of banking crises," Omega, Elsevier, vol. 38(5), pages 333-344, October.
- Greta Falavigna, 2006. "Models for Default Risk Analysis: Focus on Artificial Neural Networks, Model Comparisons, Hybrid Frameworks," CERIS Working Paper 200610, Institute for Economic Research on Firms and Growth - Moncalieri (TO) ITALY -NOW- Research Institute on Sustainable Economic Growth - Moncalieri (TO) ITALY.
- Jiancheng Jiang, 2014. "Multivariate functional-coefficient regression models for nonlinear vector time series data," Biometrika, Biometrika Trust, vol. 101(3), pages 689-702.
CitationsCitations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
- repec:gam:jsusta:v:9:y:2017:i:6:p:1057-:d:101868 is not listed on IDEAS
- repec:gam:jsusta:v:9:y:2017:i:9:p:1588-:d:111035 is not listed on IDEAS
More about this item
Keywordssupply chain financing (SCF); credit risk; small and medium-sized enterprises (SMEs); core enterprises (CEs); financial institutions (FIs); logistic regression (LR); artificial neural network (ANN); two-stage hybrid model;
- Q - Agricultural and Natural Resource Economics; Environmental and Ecological Economics
- Q0 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - General
- Q2 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Renewable Resources and Conservation
- Q3 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Nonrenewable Resources and Conservation
- Q5 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics
- Q56 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Environmental Economics - - - Environment and Development; Environment and Trade; Sustainability; Environmental Accounts and Accounting; Environmental Equity; Population Growth
- O13 - Economic Development, Innovation, Technological Change, and Growth - - Economic Development - - - Agriculture; Natural Resources; Environment; Other Primary Products
StatisticsAccess and download statistics
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jsusta:v:8:y:2016:i:5:p:433-:d:69335. See general information about how to correct material in RePEc.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: (XML Conversion Team). General contact details of provider: http://www.mdpi.com/ .
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
Please note that corrections may take a couple of weeks to filter through the various RePEc services.