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https://www.diw.de/documents/dokumentenarchiv/17/diw_01.c.88240.de/haerdle_moro_schaefer_svm_vfs_paper.pdf
method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data. In particular we discuss the selection of variables and give a
https://www.researchgate.net/publication/5101486_Estimating_Probabilities_of_Default_With_Support_Vector_Machines
Request PDF Estimating Probabilities of Default With Support Vector Machines This paper proposes a rating methodology that is based on a non-linear classification method, the support vector ...
https://papers.ssrn.com/sol3/papers.cfm?abstract_id=2794004
Jun 08, 2016 · This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data.Cited by: 11
https://ideas.repec.org/p/zbw/bubdp2/6930.html
Downloadable! This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data.
https://www.researchgate.net/publication/45133229_Estimation_of_Default_Probabilities_with_Support_Vector_Machines
Support vector machines is widely adopted classification technique with performance comparable to neural network classifiers; yet, they help to avoid some of their problems such as overtraining ...
http://sfb649.wiwi.hu-berlin.de/papers/pdf/SFB649DP2007-035.pdf
non-linear classification method, the support vector machine (SVM), and a non-parametric technique for mapping rating scores into probabilities of de-fault (see the Appendix and Chapter 5). The SVM is based on the principle of a safe separation of solvent and insolvent companies in such a way that the dis-
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.399.2268
This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on Deutsche Bundesbank data.
http://www.defaultrisk.com/pp_score_06.htm
Abstract: This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. We give an introduction to underlying statistical models and represent the results of testing our approach on German Bundesbank data.
http://citeseerx.ist.psu.edu/viewdoc/summary?doi=10.1.1.632.9559
A company score is computed as a value of that function. In the case of the probit and logit models the score can be directly transformed into a probability of default (PD), which denotes the probability with which a company can go bankrupt within a certain period.
https://core.ac.uk/display/23678699
Estimating Probabilities of Default With Support Vector Machines ⋆ By W. K. Härdle A, R. A. Moro B and D. Schäfer C. Abstract. This paper proposes a rating methodology that is based on a non-linear classification method, the support vector machine, and a non-parametric technique for mapping rating scores into probabilities of default. ...Author: W. K. Härdle A, R. A. Moro B and D. Schäfer C
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