Pension fund needs to produce a high-income return to face actuarial expectations of different kinds of benefits. An asset allocation management model of a pension fund must consider a large planning horizon because of its long-term obligations. Asset allocation controls the solvency of the fund by suitable investments and contribution policies to secure the pensioner’s future liabilities. Artificial intelligence approaches given by experts and accepted by decision-makers, provide a powerful tool for describing uncertainty. A portfolio optimization model is introduced based on variance minimization at a required return level that secures the fund against insolvency risk. This method uses an artificial Bee ColonyOptimizationApproach to the mean-variance defined by Markowitz so that future returns of the stocks are predicted where the ability of AI to improve predictive and prescriptive financial forecasting processes will change the world of finance management.
Pension Fund Asset Allocation: A Mean-Variance Model with CVaR Constraints
