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首页> 外文期刊>Journal of applied statistics >A new financial stress index model based on support vector regression and control chart
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A new financial stress index model based on support vector regression and control chart

机译:基于支持向量回归和控制图的新财务压力指数模型

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Financial stress index (FSI) is considered to be an important risk management tool to quantify financial vulnerabilities. This paper proposes a new framework based on a hybrid classifier model that integrates rough set theory (RST), FSI, support vector regression (SVR) and a control chart to identify stressed periods. First, the RST method is applied to select variables. The outputs are used as input data for FSI-SVR computation. Empirical analysis is conducted based on monthly FSI of the Federal Reserve Bank of Saint Louis from January 1992 to June 2011. A comparison study is performed between FSI based on the principal component analysis and FSI-SVR. A control chart based on FSI-SVR and extreme value theory is proposed to identify the extremely stressed periods. Our approach identified different stressed periods including internet bubble, subprime crisis and actual financial stress episodes, along with the calmest periods, agreeing with those given by Federal Reserve System reports.
机译:财务压力指数(FSI)被认为是量化财务漏洞的重要风险管理工具。本文提出了一个基于混合分类器模型的新框架,该模型结合了粗糙集理论(RST),FSI,支持向量回归(SVR)和控制图来识别压力周期。首先,将RST方法应用于选择变量。输出用作FSI-SVR计算的输入数据。基于1992年1月至2011年6月圣路易斯联邦储备银行的每月FSI进行实证分析。基于主成分分析的FSI与FSI-SVR进行了比较研究。提出了一种基于FSI-SVR和极值理论的控制图来识别极端压力时期。我们的方法确定了包括互联网泡沫,次贷危机和实际财务压力事件在内的不同压力时期,以及最平静的时期,与美联储报告中给出的一致。

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