Asymmetric Effects of Pension Fund Asset Allocation on Financial Performance: Evidence from Nigeria
DOI:
https://doi.org/10.53909/rms.07.01.0316Keywords:
Pension Funds, Asset Allocation, Return on Investment, NARDL, DiversificationAbstract
Purpose
This study investigates the asymmetric effects of pension fund asset allocation on the returns on investment (ROI) of pension fund administrators in Nigeria, to understand how different asset classes influence fund performance in an emerging market context.
Methodology
The study employs the Nonlinear Autoregressive Distributed Lag (NARDL) model using monthly data spanning 2007–2023. The analysis covers pension fund investments in federal government securities, equities, corporate bonds, money market instruments, mortgage funds, and real estate assets to assess both short- and long-run effects on ROI.
Findings
The results show that government securities dominate pension fund portfolios; however, their long-term returns are constrained by inflation and interest rate volatility. Investments in equities, corporate bonds, and real estate exhibit positive but statistically insignificant effects on ROI in both the short and long run. Symmetry tests indicate no significant differences between positive and negative asset allocation shocks, suggesting that diversification strategies perform consistently across market conditions.
Conclusion
The study concludes that achieving a balance between investment safety and diversification is crucial for enhancing pension fund performance. It recommends gradual regulatory liberalization, market deepening, and innovative portfolio management approaches to improve returns, safeguard retirees’ welfare, and support Nigeria’s broader economic development.
Downloads
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2025 Authors retain copyright to the content of the articles. Open access articles can be published under the Creative Commons Attribution (CC BY) 4.0

This work is licensed under a Creative Commons Attribution 4.0 International License.
The open-access articles in this journal are licensed under the terms of the Creative Commons licenses (CC BY 4.0).