用拼凑copula在Solvency II下生成不利的VaR情景

IF 0.6 Q4 STATISTICS & PROBABILITY
Dietmar Pfeifer, O. Ragulina
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引用次数: 3

摘要

摘要本文的中心思想是为多变量copula提出一个通用的简单拼凑构造原理,该原理在保持给定边际分布的同时产生不利的VaR(即风险价值)情景。这对于欧盟偿付能力II下保险业内部模型的构建尤其重要。除此之外,欧盟委员会的授权条例要求所有受监管的保险公司在其风险管理系统中考虑不同的风险情景,以进行公司自身的风险评估。由于假设公司将出现潜在的最坏情况是不合理的,我们认为本文中描述的各种不利情况的模型也是合适的。我们的显式copula方法可以被认为是序数和的一种特殊情况,在二维中,它甚至会导致技术上最差的VaR场景。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generating unfavourable VaR scenarios under Solvency II with patchwork copulas
Abstract The central idea of the paper is to present a general simple patchwork construction principle for multivariate copulas that create unfavourable VaR (i.e. Value at Risk) scenarios while maintaining given marginal distributions. This is of particular interest for the construction of Internal Models in the insurance industry under Solvency II in the European Union. Besides this, the Delegated Regulation by the European Commission requires all insurance companies under supervision to consider different risk scenarios in their risk management system for the company’s own risk assessment. Since it is unreasonable to assume that the potential worst case scenario will materialize in the company, we think that a modelling of various unfavourable scenarios as described in this paper is likewise appropriate. Our explicit copula approach can be considered as a special case of ordinal sums, which in two dimensions even leads to the technically worst VaR scenario.
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来源期刊
Dependence Modeling
Dependence Modeling STATISTICS & PROBABILITY-
CiteScore
1.00
自引率
0.00%
发文量
18
审稿时长
12 weeks
期刊介绍: The journal Dependence Modeling aims at providing a medium for exchanging results and ideas in the area of multivariate dependence modeling. It is an open access fully peer-reviewed journal providing the readers with free, instant, and permanent access to all content worldwide. Dependence Modeling is listed by Web of Science (Emerging Sources Citation Index), Scopus, MathSciNet and Zentralblatt Math. The journal presents different types of articles: -"Research Articles" on fundamental theoretical aspects, as well as on significant applications in science, engineering, economics, finance, insurance and other fields. -"Review Articles" which present the existing literature on the specific topic from new perspectives. -"Interview articles" limited to two papers per year, covering interviews with milestone personalities in the field of Dependence Modeling. The journal topics include (but are not limited to):  -Copula methods -Multivariate distributions -Estimation and goodness-of-fit tests -Measures of association -Quantitative risk management -Risk measures and stochastic orders -Time series -Environmental sciences -Computational methods and software -Extreme-value theory -Limit laws -Mass Transportations
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