Policy inprovement via inverse ALM

Traditional ALM first sets the policy parameters and then assesses the impact on some sub-set of risk and return measures. We propose a method to ‘invert’ the traditional ALM approach: first formulate the desired level of risk and return measures and then systematically search through the policy space to find the policy that ‘best’ meets the objectives and constraints. The method is more ‘open minded’ than traditional ALM as is shown in a numerical example using an ALM model for a stylized pension fund.