Setting Realistic Goals for Personal Retirement Planning via Micro–Macro Analyses

Q4 Economics, Econometrics and Finance
J. Mulvey, Hang-Wei Hao
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Abstract

The vulnerability of individuals planning for retirement has been growing as a result of the conversion from defined-benefit plans to defined-contribution plans, the steady increase in life longevity, and the uncertainty of asset returns under an ever-changing global environment. A serious problem is the lack of appropriate planning for retirement. How much should an individual in the United States save beyond the Social Security tax to maintain a reasonable lifestyle after retirement? The article designs a framework to facilitate the process of setting realistic goals for retirement planning, featuring the concept of agent-based simulations. Focusing on policy-rule-based investment strategies, the simulation framework includes multiple investable asset categories and explores dynamic allocation based on the investor’s age, current salary, and Social Security accumulation situation. Empirical results demonstrate a stylized application of the planning framework. TOPICS: Long-term/retirement investing, pension funds, portfolio management, retirement, Social Security Key Findings • Demonstrates the advantages of agent-based simulation models for addressing the survivability of pension plans. • Compares dynamic and adaptive strategies for integrating saving and investment decisions. • Provides a clear example of goal-based investing for individuals and for institutions such as the US Social Security System.
微观-宏观分析为个人退休规划设定现实目标
由于固定收益计划向固定缴款计划的转变,寿命的稳步增长,以及在不断变化的全球环境下资产回报的不确定性,个人退休计划的脆弱性日益增加。一个严重的问题是缺乏适当的退休计划。在美国,个人除了社会保障税之外,应该存多少钱才能在退休后维持合理的生活方式?本文设计了一个框架,以促进制定现实的退休计划目标的过程,具有基于代理的模拟的概念。仿真框架以基于政策规则的投资策略为重点,包含多种可投资资产类别,并根据投资者的年龄、当前工资和社保积累情况探索动态配置。实证结果证明了规划框架的程式化应用。主题:长期/退休投资,养老基金,投资组合管理,退休,社会保障主要发现•展示了基于代理的模拟模型在解决养老金计划的生存能力方面的优势。•比较动态和适应性策略,以整合储蓄和投资决策。•为个人和机构(如美国社会保障体系)提供了基于目标的投资的清晰示例。
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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来源期刊
Journal of Retirement
Journal of Retirement Economics, Econometrics and Finance-Finance
CiteScore
0.80
自引率
0.00%
发文量
27
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