Multi-stage Stochastic Programming Asset/Liability Management Model with VaR Constraint at the Social Security Organization

Optimizing asset allocation at the asset class level and measuring the insolvency risk of the Social Security Organization (SSO)by considering the value at risk constraint.

At first we hand-collect the book value of assets for the SSO using its financial statements from 2001 through 2015 and categorize assets into three asset classes: stocks, real estate and bonds. We then estimate the market value of assets using returns for the corresponding market during this period. Subsequently, we generate 300 forecasts for each market return over a 75-year horizon by the Monte Carlo simulation method. These efforts, Combined with the predictions of expenditures and contributions of the SSO from the International Labor Organization (ILO), for helping us have sufficient data to design and solve a multi-stage stochastic programming model. Also, we have adequate data to calculate the probability of insolvency in the SSO by counting the number of infeasible solutions through all forecasts in the model.

We obtain optimal allocation for all three asset classes and propose the types of reforms required for decreasing the insolvency risk in the SSO throughout the long term mending period in the way that imposes minimum pressure on pensioners and contributors simultaneously.

Despite the constraints faced by the SSO in terms of asset allocation, our results indicate that certain allocations are capable of resolving the underfunding problem for the SSO over the studied horizon. This solution involves implementing a set of gradual parametric reforms and optimal asset allocation. In a way that could meet stakeholders' purpose. We consider the restriction that the state is facing in payback its debt to the SSO whereby securitize them. After all, legislation reforms in running an independent regulator organization are essential. These exercises make us impose an excellent government for pension funds and construct an investment policy for them to reduce harmful intervention