A study of asset and liability management applied to Brazilian pension funds

Asset and Liability Management (ALM) is a critical framework for pension funds, ensuring they have sufficient assets to meet future liabilities (pension payments) while managing investment risks effectively. This paper utilizes Brazilian data to develop an ALM model specifically for pension funds in the country. The model employs an optimization strategy that minimizes expected contributions made by individuals throughout their working lives. This optimization adheres to cash flow limitations and regulatory restrictions. The objective function leverages a min–max robust optimization approach based on a three-scenario planning scheme inspired by Brazil’s Interbank Rate. We incorporate a machine learning approach based on CMARS to predict confidence intervals for the key stochastic model parameters, particularly those related to the real returns of Brazilian investment classes. The findings empower pension fund managers to formulate well-informed investment strategies. We highlight allocation strategies that can reduce contribution rates without jeopardizing fund solvency, even for managers with a more aggressive risk profile favoring higher stock market allocations. Additionally, the study is enriched by an empirical analysis using data from a Brazilian pension fund, demonstrating the model’s practical application. In short, this model offers valuable insights that can benefit a wide range of pension funds in the Brazilian market, and it could also be applied to similar situations globally.