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Credible risk measures with applications in actuarial sciences and finance

机译:可信的风险度量及其在精算科学和金融中的应用

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In this paper, we introduce a general framework for obtaining a new type of risk measures, the so called credible risk measures, as a result of incorporating credibility methodology with some well known risk measures, such as the value at risk (VaR) and the conditional tail expectation (CTE). The resulting credible risk measures are more informative than the usual risk measures (i.e. VaR, CM) in capturing the risk of individual insurer's contract (or returns of an individual asset) as well as the portfolio risk consisting of several similar but not identical contracts (or returns of a portfolio of similar assets), which are grouped together to share the risk. These credible risk measures are: the credible value at risk, the credible conditional tail expectation, the credible tail conditional median and the credible quantile tail expectation. Two examples of credible risks measures are presented, one with insurance loss data and the other with industry financial data. The advantages and disadvantages of these new credible measures are also discussed. (C) 2016 Elsevier B.V. All rights reserved.
机译:在本文中,我们引入了一种通用的框架,以获取一种新型的风险度量,即所谓的可信风险度量,这是将可信度方法与一些众所周知的风险度量(例如风险价值(VaR)和有条件的尾巴期望(CTE)。由此产生的可信风险度量在捕获单个保险人的合同(或单个资产的收益)以及由数个相似但不相同的合同组成的投资组合风险方面,比通常的风险度量(即VaR,CM)更具信息性(或类似资产的投资组合的收益),将它们组合在一起以分担风险。这些可信的风险度量包括:可信的风险值,可信的条件尾部期望值,可信的条件尾部中位数和可信的分位数期望值。给出了两个可靠的风险度量示例,一个带有保险损失数据,另一个带有行业财务数据。还讨论了这些新的可靠措施的优缺点。 (C)2016 Elsevier B.V.保留所有权利。

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