An algorithm for moment-matching scenario generation with application to financial portfolio optimisation
Mean, covariance, average marginal third and fourth moments are matched exactly. Scenarios and corresponding probability weights are produced without optimisation. The algorithm is used in a mean-CVaR portfolio optimisation model. Results show desirable in-sample and out-of-sample stability. Good solutions can be obtained with a relatively small number of scenarios.
scenarios or in banking finance stochastic programming