The Spectral Stress VaR (SSVaR)

D. Guégan, Bertrand K. Hassani, Kehan Li
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引用次数: 2

Abstract

One of the key lessons of the crisis which began in 2007 has been the need to strengthen the risk coverage of the capital framework. In response, the Basel Committee in July 2009 completed a number of critical reforms to the Basel II framework which will raise capital requirements for the trading book and complex securitisation exposures, a major source of losses for many international active banks. One of the reforms is to introduce a stressed value-at-risk (VaR) capital requirement based on a continuous 12-month period of significant financial stress (Basel III (2011)). However the Basel framework does not specify a model to calculate the stressed VaR and leaves it up to the banks to develop an appropriate internal model to capture material risks they face. Consequently we propose a forward stress risk measure ``spectral stress VaR" (SSVaR) as an implementation model of stressed VaR, by exploiting the asymptotic normality property of the distribution of estimator of VaR_p. In particular to allow SSVaR incorporating the tail structure information we perform the spectral analysis to build it. Using a data set composed of operational risk factors we fit a panel of distributions to construct the SSVaR in order to stress it. Additionally we show how the SSVaR can be an indicator regarding the inner model robustness for the bank.
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应力谱VaR (SSVaR)
始于2007年的这场危机的一个关键教训是,有必要加强资本框架的风险覆盖。作为回应,巴塞尔委员会于2009年7月完成了对巴塞尔协议II框架的一系列关键改革,这些改革将提高交易簿和复杂证券化敞口的资本要求,这是许多国际活跃银行的主要损失来源。其中一项改革是根据连续12个月的重大财务压力(巴塞尔协议III(2011))引入压力风险价值(VaR)资本要求。然而,巴塞尔框架并未指定计算压力风险值的模型,而是让银行自行开发适当的内部模型,以捕捉它们面临的重大风险。因此,我们利用VaR_p估计量分布的渐近正态性,提出了一种正演应力风险测度“谱应力VaR”(SSVaR)作为应力VaR的实现模型。特别是为了允许SSVaR结合尾部结构信息,我们执行光谱分析来构建它。使用由操作风险因素组成的数据集,我们拟合了一个分布面板来构建SSVaR,以便强调它。此外,我们还展示了SSVaR如何成为银行内部模型稳健性的指标。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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