人寿保险中的分数非均匀多状态模型

IF 1.6 3区 经济学 Q3 MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
Martin Bladt
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引用次数: 1

摘要

在本文中,我们通过使用矩阵演算证明了一个透明的分析分数阶非齐次马尔可夫模型的人寿保险,其中转移矩阵交换。所得公式是它们的单态对应物的直观矩阵推广,吸收时间是众所周知的标量分布的矩阵版本。这种方法的另一个优点是,它允许将分析扩展到非马尔可夫情况,其中逗留是Mittag-Leffler分布的,并且吸收时间是分数相型分布的。考虑确定性时间变换会产生分数阶非均匀相型分布作为吸收时间。后一种潜在的过程是一个例子,在这个制度中,不仅投保人的现在,而且投保人的历史也会影响其未来的演变。稳定分布的次指数性质转化为多状态保险模型,作为链的任意给定状态下的随机寿命风险。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fractional inhomogeneous multi-state models in life insurance
In this paper, we demonstrate through the use of matrix calculus a transparent analysis of fractional inhomogeneous Markov models for life insurance where transition matrices commute. The resulting formulae are intuitive matrix generalizations of their single-state counterparts, and the absorption times are matrix versions of well-known scalar distributions. A further advantage of this approach is that it allows extending the analysis to the non-Markovian case where sojourns are Mittag-Leffler distributed, and where the absorption times are fractional phase-type distributed. Considering deterministic time transforms gives rise to fractional inhomogeneous phase-type distributions as absorption times. The latter underlying processes are an example of a regime where not only the present but also the history of a policyholder influences its future evolution. The sub-exponential nature of stable distributions translates into the multi-state insurance model as a random longevity risk at any given state of the chain.
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来源期刊
Scandinavian Actuarial Journal
Scandinavian Actuarial Journal MATHEMATICS, INTERDISCIPLINARY APPLICATIONS-STATISTICS & PROBABILITY
CiteScore
3.30
自引率
11.10%
发文量
38
审稿时长
>12 weeks
期刊介绍: Scandinavian Actuarial Journal is a journal for actuarial sciences that deals, in theory and application, with mathematical methods for insurance and related matters. The bounds of actuarial mathematics are determined by the area of application rather than by uniformity of methods and techniques. Therefore, a paper of interest to Scandinavian Actuarial Journal may have its theoretical basis in probability theory, statistics, operations research, numerical analysis, computer science, demography, mathematical economics, or any other area of applied mathematics; the main criterion is that the paper should be of specific relevance to actuarial applications.
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