集体固定缴款养老金计划的投资组合优化和代际风险分担

IF 1.9 3区 工程技术 Q3 MANAGEMENT
Suxin Wang;Peiqi Wang;Shuhua Zhang
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引用次数: 0

摘要

在本文中,我们使用连续时间随机模型来研究一个集体固定缴款养老金计划,当利率是随机的,福利水平根据计划的绩效进行调整,并且不同世代之间的风险分担。名义利率以Vasicek模型为特征,养老基金投资于由三种资产组成的金融市场:一种无风险资产、一种债券和一种风险资产。养老金计划的参与者是风险承担者,该计划为计划发起人和参与者寻求最佳投资和风险分担安排,以最大限度地提高中间福利调整和最终财富的预期累积贴现效用。在相对风险规避效用函数不变的情况下,通过随机最优控制方法得到了闭式解。数值结果显示了金融市场参数对最优投资策略的影响,以及最优收益如何随着不同的风险规避和工资增长率而变化。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Portfolio optimization and intergenerational risk sharing for a collective defined contribution pension plan
In this paper, we use a continuous time stochastic model to study a collective defined contribution pension plan when the interest rate is stochastic, and where the benefit levels are adjusted depending on the performance of the plan, and with risk sharing between different generations. The nominal interest rate is characterized by the Vasicek model, and the pension fund is invested in a financial market consisting of three assets: one risk-free asset, one bond and one risky asset. The participants of the pension plan are the risk bearers, and the plan seeks optimal investment and risk-sharing arrangements for plan sponsors and participants that maximize the expected accumulated discount utility of intermediate benefit adjustments and terminal wealth. Closed-form solutions are derived via the stochastic optimal control approach under constant relative risk aversion utility function. Numerical results show the effects of financial market parameters on the optimal investment strategy and how the optimal benefit changes with respect to different risk aversions and wage increase rates.
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来源期刊
IMA Journal of Management Mathematics
IMA Journal of Management Mathematics OPERATIONS RESEARCH & MANAGEMENT SCIENCE-MATHEMATICS, INTERDISCIPLINARY APPLICATIONS
CiteScore
4.70
自引率
17.60%
发文量
15
审稿时长
>12 weeks
期刊介绍: The mission of this quarterly journal is to publish mathematical research of the highest quality, impact and relevance that can be directly utilised or have demonstrable potential to be employed by managers in profit, not-for-profit, third party and governmental/public organisations to improve their practices. Thus the research must be quantitative and of the highest quality if it is to be published in the journal. Furthermore, the outcome of the research must be ultimately useful for managers. The journal also publishes novel meta-analyses of the literature, reviews of the "state-of-the art" in a manner that provides new insight, and genuine applications of mathematics to real-world problems in the form of case studies. The journal welcomes papers dealing with topics in Operational Research and Management Science, Operations Management, Decision Sciences, Transportation Science, Marketing Science, Analytics, and Financial and Risk Modelling.
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