Portfolio Optimization for Pension Purposes: Literature Review
ABSTRACT This systematic review identifies persistent challenges and gaps in the literature on pension portfolio optimization models. We searched, selected, and critically analyzed 82 articles from three major academic databases published over the past decade to investigate the barriers to the effective implementation of these models. Most studies primarily focus on traditional portfolio optimization approaches, often overlooking recent innovations and the unique structural characteristics of pension systems. While the number of publications has grown steadily over the past 10 years, reflecting increasing academic interest in the topic, our analysis reveals a continued need for substantive research advances to bridge existing gaps. Key challenges include the lack of models tailored to the specific features of pension funds, limited attention to longevity and sustainability constraints, and insufficient application of innovative methods to address sector‐specific demands. This study highlights the importance of future research that incorporates advanced machine learning techniques, develops ESG‐aligned and sustainability‐oriented optimization frameworks, and more effectively models regulatory and demographic constraints. These directions are essential for enhancing the robustness and relevance of pension portfolio models and to support more effective, long‐term pension fund management.
Authors
- Pedro Henrique González (ORCID: https://orcid.org/0000-0003-0057-7670)
- Igor Leão dos Santos (ORCID: https://orcid.org/0000-0002-9473-3728)
- Leonardo Marmo Moreira (ORCID: https://orcid.org/0000-0003-4967-1377)
Institutions
- Universidade Federal do Rio de Janeiro (BR)
- Federal Center for Technological Education Celso Suckow da Fonseca (BR)
Publication Details
- Journal
- Journal of Economic Surveys
- Published
- 2025-05-05
- DOI
- https://doi.org/10.1111/joes.12702
- Citations
- 3
- Primary Topic
- Insurance, Mortality, Demography, Risk Management
- Type
- article
- Field-Weighted Citation Impact
- 16.78
Funders
- Coordenação de Aperfeiçoamento de Pessoal de Nível Superior
- Conselho Nacional de Desenvolvimento Científico e Tecnológico
- Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro
- Universidade Federal do Rio de Janeiro