利用参与者数据改善目标日期基金配置

Q3 Social Sciences Social Security Bulletin Pub Date : 2012-09-01 DOI:10.2139/ssrn.2149092
Zhenyu Li, A. Webb
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引用次数: 0

摘要

经济理论认为,401(k)计划的参与者应该在临近退休时逐步调整投资组合,从股票转向风险较低的债券。传统的目标日期基金试图通过定期自动调整家庭投资组合来实现这一目标,但它们只考虑了个人的一个方面:他的预期退休年龄。本文调查了计划提供者是否可以通过利用雇主已知的信息,即每个雇员的收入、401(k)余额和储蓄率,来改进这种“一刀切”的方法。使用随机动态优化模型,结合劳动力和金融市场风险,它计算了一个家庭在采用三种选择(典型的、“一刀切”的或“半个性化”的投资组合配置)后的最佳投资组合配置所需的补偿。
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Using Participant Data to Improve Target Date Fund Allocations
Economic theory says that participants in 401(k) plans should gradually rebalance their portfolios away from stocks and toward less risky bonds as they approach retirement. Conventional target date funds attempt to do so by automatically rebalancing the household’s portfolio periodically, but they take account of only one aspect of the individual: his expected retirement age. This paper investigates whether plan providers could improve on this “one-size-fits-all” approach by making use of information that is known to the employer, namely each employee’s income, 401(k) balance, and saving rate. Using a stochastic dynamic optimization model, incorporating both labor- and financial-market risk, it calculates the compensation a household following an optimal portfolio allocation would require for adopting three alternatives: a typical, a “one-size-fits-all,” or a “semi-personalized” portfolio allocation.
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来源期刊
Social Security Bulletin
Social Security Bulletin Social Sciences-Social Sciences (miscellaneous)
CiteScore
0.70
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