The aim of the proposed grant project is the validation of decision models of dynamical economic and financial systems under uncertainty. For handling such tasks probabilistic approaches primarily based on multistage stochastic programming and stochasticdynamic programming are very often employed. As concerns model specification, the research will be primarily focused on various aspects on the model choice, choice of the objective function, and on modeling input scenarios. As concerns validation of results, the research will be focused on error bound analysis, contamination and stress testing, stability for empirical programs, the worst-case analysis, and stability of scenario generation methods. Special attention will be payed to computational aspects of the suggested approaches for solving large-scale problems arising in economic and financial analysis. The obtained mathematical results will be verified and tested on real economic data.The project also will enable to deepen and generalize