FactSet Optimizer offers a multi-step optimization model based on scenario simulations from the Fat-Tail Multi-Asset Class model. This FactSet application uniquely combines Expected Tail Loss optimization based on Fat-Tail models with a multi-period extension approach. This allows for flexible inputs of the underlying stochastic models and efficiency of solving long-term, high-dimensional problems with a significant number of future decision-making points.
Download the Multi-Period Optimization white paper to review how risk-based optimization with measures for the tail losses (specifically the expected tail loss measure) can be solved using suitable objectives and constraints. Uncover how to extend the single-based optimization model to a scenario-based multiperiod optimization model where it is possible to handle cross-period constraints.
FactSet clients, read the white paper via Online Assistant. Not a FactSet client? Schedule a one-on-one demo with a FactSet specialist.