从分值函数的风险规避随机优化出发的风险测量方法

IF 1.9 2区经济学 Q2 ECONOMICS

Insurance Mathematics & Economics Pub Date : 2024-11-15 DOI:10.1016/j.insmatheco.2024.11.005

Marcelo Brutti Righi, Fernanda Maria Müller, Marlon Ruoso Moresco

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引用次数: 0

摘要

我们提出了一种风险规避随机问题的风险测量方法。我们提供的结果保证了问题解的存在性。我们描述并探讨了作为风险度量的 argmin 和作为广义偏差度量的最小值的特性。我们举例说明了我们方法的具体应用。此外，我们还提供了一个解决问题的数字示例，以说明我们的方法在风险管理分析中的实用性。

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A risk measurement approach from risk-averse stochastic optimization of score functions

We propose a risk measurement approach for a risk-averse stochastic problem. We provide results that guarantee the existence of a solution to our problem. We characterize and explore the properties of the argmin as a risk measure and the minimum as a generalized deviation measure. We provide an example to demonstrate a specific application of our approach. Additionally, we present a numerical example of the problem's solution to illustrate the usefulness of our approach in risk management analysis.

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来源期刊

Insurance Mathematics & Economics 管理科学-数学跨学科应用

CiteScore

3.40

自引率

15.80%

发文量

审稿时长

17.3 weeks

期刊介绍： Insurance: Mathematics and Economics publishes leading research spanning all fields of actuarial science research. It appears six times per year and is the largest journal in actuarial science research around the world. Insurance: Mathematics and Economics is an international academic journal that aims to strengthen the communication between individuals and groups who develop and apply research results in actuarial science. The journal feels a particular obligation to facilitate closer cooperation between those who conduct research in insurance mathematics and quantitative insurance economics, and practicing actuaries who are interested in the implementation of the results. To this purpose, Insurance: Mathematics and Economics publishes high-quality articles of broad international interest, concerned with either the theory of insurance mathematics and quantitative insurance economics or the inventive application of it, including empirical or experimental results. Articles that combine several of these aspects are particularly considered.