目标收益养老金计划的最优vix挂钩结构

IF 16.4 1区化学 Q1 CHEMISTRY, MULTIDISCIPLINARY

Accounts of Chemical Research Pub Date : 2023-10-18 DOI:10.1017/asb.2023.33

Lv Chen, Danping Li, Yumin Wang, Xiaobai Zhu

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引用次数: 0

摘要

摘要本文研究了最优VIX-linked target benefit (TB)养老金设计。通过应用动态规划方法，我们发现福利支付的最佳风险分担结构呈现线性形式，由三个组成部分组成:(1)模型稳健的绩效调整，(2)依赖于VIX指数的反周期波动率调整，以及(3)结核病水平部分与生活成本调整挂钩。我们的结果和以前的文献之间的差异是通过理论推导和数值说明突出。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Optimal VIX-linked structure for the target benefit pension plan

Abstract In this paper, we study the optimal VIX-linked target benefit (TB) pension design. By applying the dynamic programming approach, we show the optimal risk-sharing structure for the benefit payment exhibits a linear form that consists of three components: (1) a model-robust performance adjustment, (2) a counter-cyclical volatility adjustment that depends on the VIX index, and (3) a TB level that is partially indexed to the cost-of-living adjustment. Differences between our results and the previous literature are highlighted via both theoretical derivations and numerical illustrations.

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来源期刊

Accounts of Chemical Research 化学-化学综合

CiteScore

31.40

自引率

1.10%

发文量

312

审稿时长

2 months

期刊介绍： Accounts of Chemical Research presents short, concise and critical articles offering easy-to-read overviews of basic research and applications in all areas of chemistry and biochemistry. These short reviews focus on research from the author’s own laboratory and are designed to teach the reader about a research project. In addition, Accounts of Chemical Research publishes commentaries that give an informed opinion on a current research problem. Special Issues online are devoted to a single topic of unusual activity and significance. Accounts of Chemical Research replaces the traditional article abstract with an article "Conspectus." These entries synopsize the research affording the reader a closer look at the content and significance of an article. Through this provision of a more detailed description of the article contents, the Conspectus enhances the article's discoverability by search engines and the exposure for the research.