arXivDaily arXiv每日学术速递 周一至周五更新
arXiv周末暂无论文更新,休息一下吧,周末愉快~~
arXiv 2212.04848q-fin.RM
收藏

依赖不确定性下非负多元风险联合风险评估研究

On evaluation of joint risk for non-negative multivariate risks under dependence uncertainty

Shuo Gong, Yijun Hu, Linxiao Wei

AI总结:

本文针对依赖不确定性下的非负多元风险,提出标量与向量值扭曲联合风险度量,通过新公理体系进行刻画,并与现有多元风险度量进行比较,为联合风险评估提供理论基础。

摘要:

本文提出了一种新颖的公理化方法,用于在依赖不确定性下评估多个保险风险的联合风险。受期望效用理论和Cobb-Dauglas效用函数的启发,我们为非负多元风险建立了一种联合风险度量,称之为标量扭曲联合风险度量。在研究其基本性质之后,我们通过提出一组新的公理对其进行了公理化刻画。其中最具新意的公理是分量正齐次性。随后,基于所得到的扭曲联合风险度量,我们还为非负多元风险提出了一类新的向量值扭曲联合风险度量。最后,我们与文献中已知的一些向量值多元风险度量进行了比较,例如多元下正交价值风险、多元上正交条件尾部期望、多元尾部条件期望和多元尾部扭曲风险度量。结果表明,这些向量值多元风险度量分别具有向量值扭曲联合风险度量的形式。本文主要给出了依赖不确定性下联合风险评估的一些理论结果,有望对联合风险的度量有所帮助。

英文摘要:

In this paper, we propose a novel axiomatic approach to evaluating the joint risk of multiple insurance risks under dependence uncertainty. Motivated by both the theory of expected utility and the Cobb-Dauglas utility function, we establish a joint risk measure for non-negative multivariate risks, which we refer to as a scalar distortion joint risk measure. After having studied its fundamental properties, we provide an axiomatic characterization of it by proposing a set of new axioms. The most novel axiom is the component-wise positive homogeneity. Then, based on the resulting distortion joint risk measures, we also propose a new class of vector-valued distortion joint risk measures for non-negative multivariate risks. Finally, we make comparisons with some vector-valued multivariate risk measures known in the literature, such as multivariate lower-orthant value at risk, multivariate upper-orthant conditional-tail-expectation, multivariate tail conditional expectation and multivariate tail distortion risk measures. It turns out that those vector-valued multivariate risk measures have forms of vector-valued distortion joint risk measures, respectively. This paper mainly gives some theoretical results about the evaluation of joint risk under dependence uncertainty, and it is expected to be helpful for measuring joint risk.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

↑