ESG-integration investment strategy for TDFs with a multi-objective dynamic programming

ESG (Environmental, social, and governance) has become increasingly crucial in the investment of pension funds. This paper develops a multi-objective dynamic model to analyze the ESG-integration investment strategy of Target Date Funds (TDFs). The model optimizes three objectives: expected return, variance, and ESG score, incorporating human capital in the budget constraint and considering inflation-linked bonds as one of the candidate assets. Our model facilitates ESG into the long-term investment of pension funds and extends the multi-objective framework for ESG investment into a dynamic context. To solve the model, we propose a bipolar genetic algorithm that addresses challenges arising from the varying magnitudes of objectives and time inconsistency. In the numerical experiments, we compare our model to the non-ESG model, demonstrating the benefits of ESG in the long term. Our findings show that, unlike the traditional glide path of TDFs, the ESG-integration glide path prefers equity assets and achieves superior performance. Additionally, the glide paths and TDFs’ performance are associated with human capital and preferences among the three objectives, highlighting the need for customized glide paths of different investors. This study provides insights for TDFs fund managers to incorporate ESG into investment decisions and develop strategies accommodating investor heterogeneity.