This PhD Thesis is composed of four working papers, each one with a respective chapter on this thesis, with contributions on risk averse stochastic programming models. In particular, it focuses on analyzing the practical consequences of certain theoretical concepts of decision theory, finance and optimization. The first working paper analyzes the practical consequences and the economic interpretation of time consistent optimal policies, in particular for well known portfolio selection problem. The second paper has also a contribution to the portfolio selection literature. Indeed, we develop leverage optimal strategy considering a single-period debt with a piecewise linear borrowing cost function, which represents the actual situation faced by investors, and show a significant gap in comparison to the suboptimal solutions obtained by the usual linear approximation. Moreover, we develop a multistage extension where our cost function indirectly penalizes the excess of leverage, which is closely related to the contribution of the next working paper. The contribution of the third working paper is to penalize excess of leverage in a debt issuance multistage model that optimizes over several types of bonds with fixed or floating rate, different maturities and amortization patterns. For the sake of dealing with the curse of dimensionality of a long term problem, we divide the planning horizon into a detailed part at the beginning followed by a policy rule approximation for the remainder. Indeed, our approximation mitigates the end effects of a truncated model which is closely related to the contributions of the forth working paper. The forth paper develops a multistage model that seeks to obtain the optimal cash holding policy of a firm. The main contributions are a methodology to end effect treatment for a multistage model with infinite horizon and the development of a policy rule as approximation of the optimal solution.