A Genetic Algorithm Approach to Optimal Asset Allocation of Defined Contribution Pension Funds: Evidence From India’s National Pension System

Abstract

Life cycle asset allocation has recently gained popularity and is the default option in pension funds worldwide. A line of recent studies has refuted its glory and argues that a balanced fund with a fixed allocation throughout the investment horizon may yield better results. The question arises from these studies: What should be the balanced fund’s optimum asset allocation weight? Therefore, the present study uses Genetic Algorithm to obtain the optimum asset allocation weight for India’s defined contribution pension plan subscribers. To validate our result, the study compares the results of a Genetic Algorithm to the outcomes of widely used asset allocation techniques, notably the life cycle and equally weighted strategies. This study holds important policy implications as, given the size of the pension asset and the long investment duration, even a trivial increase in return will substantially impact investment outcomes, affecting the subscribers’ well-being in old age.