Support Vector Machines Based Methodology for Credit Risk Analysis

DOI10.1142/9789811202391_0020zbMATH Open1454.91330OpenAlexW3080692607MaRDI QIDQ5139412

Mingxi Liu, Cheng-Few Lee, Dengsheng Wu, Jian-ping Li

Publication date: 9 December 2020

Published in: Handbook of Financial Econometrics, Mathematics, Statistics, and Machine Learning (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1142/9789811202391_0020

zbMATH Keywords

feature extractionsupport vector machineshyperparameter optimizationkernel function selectioncredit risk classification

Mathematics Subject Classification ID

Applications of statistics to actuarial sciences and financial mathematics (62P05) Learning and adaptive systems in artificial intelligence (68T05) Credit risk (91G40)

Related Items (5)

Value-at-risk support vector machine: stability to outliers ⋮ Credit risk analysis using boosting methods ⋮ Prediction of banking systemic risk based on support vector machine ⋮ Application of Discriminant Analysis, Factor Analysis, Logistic Regression, and KMV-Merton Model in Credit Risk Analysis ⋮ Support Vector Machines for Credit Scoring: Extension to Non Standard Cases

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