The purpose of this chapter is to present an overview of recent results on stochastic control,
in particular, portfolio optimization, achieved via techniques of Malliavin calculus and …

This book provides the reader with the principal concepts and results related to differential
properties of measures on infinite dimensional spaces. In the finite dimensional case such …

Stochastic Calculus of Variations (or Malliavin Calculus) consists, in brief, in constructing
and exploiting natural differentiable structures on abstract probability spaces; in other words …

This monograph is an introduction to some aspects of stochastic analysis in the framework of
normal martingales, in both discrete and continuous time. The text is mostly self-contained …

We consider random variables of the form F= f (V 1,…, V n), where f is a smooth function and
V i, i∈ ℕ, are random variables with absolutely continuous law pi (y) dy. We assume that pi …

In the theory of portfolio selection, there are few methods that effectively address the
combined challenge of insider information and model uncertainty, despite numerous …

The goal of this paper is to obtain probabilistic representation formulas that are suitable for
the numerical computation of the (possibly non-continuous) density functions of infima of …

This article concerns continuous-time, continuous-space stochastic dynamical systems
described by stochastic differential equations (SDE). It presents a new approach to compute …

We use white noise calculus for Lévy processes to obtain a representation formula for the
functionals of a jump diffusion. Then we use this to find an explicit formula for the Donsker …

We develop an integration by parts technique for point processes, with application to the
computation of sensitivities via Monte Carlo simulations in stochastic models with jumps …