We propose a partial replication strategy to construct risk-averse enhanced index funds. Our model takes into account the parameter estimation risk by defining the asset returns and the return covariance terms as random ...

We define a risk averse nonanticipative feasible policy for multistage stochastic programsand propose a methodology to implement it. The approach is based on dynamic programmingequations written for a risk averse formulation ...

We propose a new modeling and solution method for probabilistically constrained optimization problems.The methodology is based on the integration of the stochastic programming and combinatorialpattern recognition fields. ...

This paper proposes a general duality framework for the problem of minimizing a convex integral functional over a space of stochastic processes adapted to a given filtration. The framework unifies many well-known duality ...

In this paper we present stability and sensitivity analysis of a stochastic optimizationproblem with stochastic second order dominance constraints. We consider perturbation of theunderlying probability measure in the space ...

We explore reformulation of nonlinear stochastic programs with several joint chance constraints by stochastic programs with suitably chosenpenalty-type objectives. We show that the two problems are asymptotically equivalent. ...

In this paper, we compare the performance of two scenario-based numerical methods to solve stochastic optimal control problems: scenario trees and particles. The problem consists in finding strategies to control a dynamicalsystem ...

The paper deals with joint probabilistic constraints defined by a Gaussiancoefficient matrix. It is shown how to explicitly reduce the computation ofvalues and gradients of the underlying probability function to that of ...