  In stochastic control problems delicate issues arise when the controlled
system can jump due to both exogenous shocks and endogenous controls. Here one
has to specify what the controller knows when about the exogenous shocks and
how and when she can act on this information. We propose to use
Meyer-$\sigma$-fields as a flexible tool to model information flow in such
situations. The possibilities of this approach are illustrated first in a very
simple linear stochastic control problem and then in a fairly general
formulation for the singular stochastic control problem of irreversible
investment with inventory risk. For the latter, we illustrate in a first case
study how different signals on exogenous jumps lead to different optimal
controls, interpolating between the predictable and the optional case in a
systematic manner.
