The efficacy of optimization modeling as a retirement strategy in the presence of estimation error
DOI:
https://doi.org/10.61190/fsr.v14i4.4832Keywords:
Estimation error, Retirement portfolio, Mean variance optimization, Asset allocationAbstract
We examine the time series performance of mean variance efficient portfolios in the retirement setting. Using a rolling period optimization model we create portfolios with the same ex ante risk as several naive 1/n strategies to discern whether optimization can improve return performance. Data are simulated from TIAA-CREF retirement accounts during 1994 through 2004. We correct for estimation error using weight constraints and James-Stein adjustments. Overall results indicate optimization does outperform most naive investment strategies. The investor's terminal wealth improves 2-30%, depending on the underlying asset allocation and assumed time to retirement. Adjustments for estimation error do little to further enhance investment returns.
Downloads
Published
Issue
Section
License
Copyright (c) 2005 Academy of Financial Services
This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License.
Author(s) retain copyright and grant the Journal right of first publication with the work simultaneously licensed under a Creative Commons Attribution-NonCommercial 4.0 International License that allows to share the work with an acknowledgment of the work's authorship and initial publication in this Journal.
This license allows the author to remix, tweak, and build upon the original work non-commercially. The new work(s) must be non-commercial and acknowledge the original work.
