Prediction of Banking Systemic Risk Based on Support Vector Machine

被引：6
|
作者：
Li, Shouwei [1 ]
Wang, Mingliang [1 ]
He, Jianmin [1 ]
机构：
[1] Southeast Univ, Sch Econ & Management, Nanjing 211189, Jiangsu, Peoples R China
来源：
MATHEMATICAL PROBLEMS IN ENGINEERING | 2013年 / 2013卷
关键词：
EARLY WARNING SYSTEMS; CRISES;
D O I：
10.1155/2013/136030
中图分类号：
T [工业技术];
学科分类号：
08 ;
摘要：
Banking systemic risk is a complex nonlinear phenomenon and has shed light on the importance of safeguarding financial stability by recent financial crisis. According to the complex nonlinear characteristics of banking systemic risk, in this paper we apply support vector machine (SVM) to the prediction of banking systemic risk in an attempt to suggest a new model with better explanatory power and stability. We conduct a case study of an SVM-based prediction model for Chinese banking systemic risk and find the experiment results showing that support vector machine is an efficient method in such case.
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页数：5
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