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Spatial Risk Measures and Rate of Spatial Diversification

机译:空间风险测度和空间多样化率

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摘要

An accurate assessment of the risk of extreme environmental events is of great importance for populations, authorities and the banking/insurance/reinsurance industry. Koch (2017) introduced a notion of spatial risk measure and a corresponding set of axioms which are well suited to analyze the risk due to events having a spatial extent, precisely such as environmental phenomena. The axiom of asymptotic spatial homogeneity is of particular interest since it allows one to quantify the rate of spatial diversification when the region under consideration becomes large. In this paper, we first investigate the general concepts of spatial risk measures and corresponding axioms further and thoroughly explain the usefulness of this theory for both actuarial science and practice. Second, in the case of a general cost field, we give sufficient conditions such that spatial risk measures associated with expectation, variance, value-at-risk as well as expected shortfall and induced by this cost field satisfy the axioms of asymptotic spatial homogeneity of order 0, ? 2 , ? 1 and ? 1 , respectively. Last but not least, in the case where the cost field is a function of a max-stable random field, we provide conditions on both the function and the max-stable field ensuring the latter properties. Max-stable random fields are relevant when assessing the risk of extreme events since they appear as a natural extension of multivariate extreme-value theory to the level of random fields. Overall, this paper improves our understanding of spatial risk measures as well as of their properties with respect to the space variable and generalizes many results obtained in Koch (2017).
机译:准确评估极端环境事件的风险对于人口,主管部门以及银行/保险/再保险行业而言至关重要。 Koch(2017)引入了空间风险测度的概念和一组相应的公理,这些公理非常适合于分析具有空间范围的事件(如环境现象)引起的风险。渐近空间同质性公理特别受关注,因为当考虑的区域变大时,它允许人们量化空间多样化的速率。在本文中,我们首先研究空间风险度量的一般概念和相应的公理,并彻底解释该理论对精算科学和实践的实用性。其次,在一般成本场的情况下,我们给出了充分的条件,使得由该成本场引起的与期望,方差,风险价值以及预期的短缺相关的空间风险度量满足了渐近空间同质性的公理。阶数0 ,? 2 ,? 1和? 1。最后但并非最不重要的一点是,在成本字段是最大稳定随机字段的函数的情况下,我们在函数和最大稳定字段上都提供了条件,以确保后者的性质。在评估极端事件的风险时,最大稳定随机字段是相关的,因为它们是多元极值理论对随机字段级别的自然扩展。总体而言,本文增进了我们对空间风险度量及其关于空间变量的属性的理解,并概括了Koch(2017)中获得的许多结果。

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