We combine stochastic control methods, white noise analysis and Hida-Malliavin calculus applied to the Donsker delta functional to obtain explicit representations of semimartingale decompositions under enlargement of filtrations. Some of the expressions are more explicit than previously known. The results are illustrated by examples.Keywords: Enlargement of filtration, Semimartingale decomposition, Optimal inside information control, Hida-Malliavin calculus, Donsker delta functional.MSC (2010): 60H40, 60H07, 60H05, 60J75, 60G48, 91G80, 93E20
IntroductionThe purpose of this paper is twofold:• We introduce a new approach to enlargement of filtration problems, based on combining several optimal control methods.• We show that this approach can in some cases give more explicit results than known before.The system we consider, is described by a stochastic differential equation driven by a Brownian motion B(t) and an independent compensated Poisson random measureÑ(dt, dζ) = N(dt, dζ) − ν(dζ)dt, ν being the Lévy measure of the Poisson random measure N. The processes are jointly defined on a filtered probability space (Ω, F = {F t } t≥0 , P) satisfying the usual conditions where Ω = S ′ (R) and P is the Gaussian measure on S ′ (R). Here, and throughout the paper, F t denotes the sigma-algebra generated by {B(s)} s≤t and {N(s, ·)} s≤t . Throughout this paper we assume that the inside information is of initial enlargement type. Specifically, we assume that the inside filtration H has the form