Modeling default risk with support vector machines
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- Maciej Zieba & Wolfgang K. Härdle, 2016. "Beta-boosted ensemble for big credit scoring data," SFB 649 Discussion Papers SFB649DP2016-052, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Ozturk, Huseyin & Namli, Ersin & Erdal, Halil Ibrahim, 2016. "Modelling sovereign credit ratings: The accuracy of models in a heterogeneous sample," Economic Modelling, Elsevier, vol. 54(C), pages 469-478.
- Wolfgang Karl HÃ¤rdle & Dedy Dwi Prastyo, 2013. "Default Risk Calculation based on Predictor Selection for the Southeast Asian Industry," SFB 649 Discussion Papers SFB649DP2013-037, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Wolgang Karl HÃ¤rdle & Li-Shan Huang, 2013. "Analysis of Deviance in Generalized Partial Linear Models," SFB 649 Discussion Papers SFB649DP2013-028, Sonderforschungsbereich 649, Humboldt University, Berlin, Germany.
- Huseyin Ozturk & Ersin Namli & Halil Ibrahim Erdal, 2016. "Reducing Overreliance on Sovereign Credit Ratings: Which Model Serves Better?," Computational Economics, Springer;Society for Computational Economics, vol. 48(1), pages 59-81, June.
- Slawomir Juszczyk & Rafal Balina, 2013. "Effectiveness of Polish and Foreign Disdcriminant Models," Diversity, Technology, and Innovation for Operational Competitiveness: Proceedings of the 2013 International Conference on Technology Innovation and Industrial Management, ToKnowPress.
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KeywordsStatistical learning theory; Applications to default risk; Capital asset pricing; Economics of risk;
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