Recursive Utility Maximization for Terminal Wealth under Partial Information

Utility Maximization under Uncertainty

Motivated by several search and optimization problems over uncertain datasets, we study the stochastic versions of a broad class of combinatorial problems where either the existences or the weights of the elements in the input dataset are uncertain. The class of problems that we study includes shortest paths, minimum weight spanning trees, and minimum weight matchings over probabilistic graphs;...

Recursive utility and preferences for information

This paper presents an axiomatic foundation for recursive utility that captures the role of the timing of resolution of uncertainty without relying on exogenously speci®ed objective beliefs. Two main representation results are proved. In the ®rst one, future utility enters the recursion through the type of general aggregators considered in Skiadas (1997a), and as a result the formulation is pur...

Blind deconvolution, information maximization and recursive filters

Starting from maximizing information ow through a nonlinear neuron Bell and Sejnowski derived adaptation equations for blind deconvolution using an FIR lter [1]. In this paper we will derive a simpler form of the adaptation and we will apply it to more complex lter structures, such as recursive lters. As an application, we study blind echo cancellation for speech signals. We will also present a...

On utility maximization under convex portfolio constraints

Utility Maximization Under Bounded Expected Loss

We consider the optimal selection of portfolios for utility maximizing investors under joint budget and shortfall risk constraints. The shortfall risk is measured in terms of the expected loss. Depending on the parameters of the risk constraint we show existence of an optimal solution and uniqueness of the corresponding Lagrange multipliers. Using Malliavin calculus we also provide the optimal ...