Existing portfolio choice models in continuous time typically reduce to finding optimal terminal cash flows which are random variables. While it works for expected 
 utility maximisation, it generally fails to work for models with non-expected utility criteria, such as the goal-achieving model, Yaari's dual model, Lopes' SP/A model, 
 behavioural model under prospect theory, models with coherent risk measures, as well as those explicitly involving VaR and CVaR in objectives and/or constraints. 
 This talk reviews the latest development in solving these non-classical models by changing decision variables - from random variables to their quantile functions.