In contrast to decision models which use in-sample scenarios we use out-of-sample scenarios to conduct simulation and decision evaluation including backtesting. We propose two simulation methodologies and describe six decision evaluation techniques that can be applied to test the performance of liability-driven investment (LDI) models. A good practice of evaluating the performance of funds is to apply risk-adjusted performance measures; we have chosen two widely applied ratios: the Sortino ratio and the funding ratio. We perform statistical tests and establish the quality of the portfolios. We report our empirical ! endings by testing an asset and liability management model for pension funds where we propose one deterministic linear programing and three stochastic programming models.
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