Rule-based strategies for dynamic life cycle investment

Author:

den Haan T. R. B.,Chau K. W.ORCID,van der Schans M.,Oosterlee C. W.

Abstract

AbstractIn this work, we consider rule-based investment strategies for managing a defined contribution pension savings scheme, under the Dutch pension fund testing model. We find that dynamic, rule-based investment strategies can outperform traditional static strategies, by which we mean that the investor may achieve the target retirement income with a higher probability or limit the shortfall when the target is not met. In comparison with dynamic programming-based strategies, the rule-based strategies have more stable asset allocations throughout time and avoid excessive transactions that may be hard to explain to an investor. We also study a combined strategy of a rule-based target with dynamic programming. A key feature of our setting is that there is no risk-free asset, instead, a matching portfolio is introduced for the investor to avoid unnecessary risk.

Funder

University of Groningen

Publisher

Springer Science and Business Media LLC

Subject

Statistics, Probability and Uncertainty,Economics and Econometrics,Statistics and Probability

Reference20 articles.

1. Arnott R, Sherrerd K, Wu L (2013) The glidepath illusion... and potential solutions. J Retire 1(2):13–28 . https://doi.org/10.3905/jor.2013.1.2.013

2. Basu A, Byrne A, Drew M (2011) Dynamic lifecycle strategies for target dateretirement funds. J Portf Manag 37(2):83–96. https://doi.org/10.3905/jpm.2011.37.2.083

3. Bellman R (1957) Dynamic programming. Dover Publications. https://www.bibsonomy.org/bibtex/29cdd821222218ded252c8ba5cd712666/pcbouman

4. Blanchett D, Kowara M, Chen P (2012) Optimal withdrawal strategy for retirement income portfolios. Morningstar Research Paper. https://www.morningstar.com/content/dam/marketing/shared/research/methodology/677951-Optimal_Withdrawal_Strategy_for_Retirement_Income_Portfolios.pdf

5. Bogle J (1994) Bogle on mutual funds: new perspectives for the intelligent investor. A Dell trade paperback. Random House Publishing Group. https://books.google.nl/books?id=6A9sYcGT92sC

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