Recently, Liang, Lyons and Qian developed a new
methodology for the study of backward stochastic differential equations (BSDEs)
on general filtered probability spaces. Their approach
is based on the analysis of a particular class of functional differential
equations, where the driver of the equation does not depend only on the
present, but also on the terminal value of the solution.
The purpose of this work is to study fully coupled
systems of forward functional differential equations, which are related to a
broad class of fully coupled forward-backward stochastic dynamics with respect
to general filtrations. In particular, these systems of functional differential
equations have a more homogeneous structure with respect to the underlying
forward-backward problems, allowing to partly avoid the conflicting nature
between the forward and backward components.
Another advantage of the approach is that its
generality allows to consider many other types of forward-backward equations
not treated in the classical literature: this is shown with the help of several
examples, which have interesting applications to mathematical finance and are
related to parabolic integro-partial differential equations. In the second part
of the talk, we introduce a numerical scheme for the approximation of decoupled
systems, based on a time discretization combined with a local iteration
approach.