  Shot-Noise processes constitute a useful tool in various areas, in particular
in finance. They allow to model abrupt changes in a more flexible way than
processes with jumps and hence are an ideal tool for modelling stock prices,
credit portfolio risk, systemic risk, or electricity markets. Here we consider
a general formulation of shot-noise processes, in particular time-inhomogeneous
shot-noise processes. This flexible class allows to obtain the Fourier
transforms in explicit form and is highly tractable. We prove that Markovianity
is equivalent to exponential decay of the noise function. Moreover, we study
the relation to semimartingales and equivalent measure changes which are
essential for the financial application. In particular we derive a drift
condition which guarantees absence of arbitrage. Examples include the minimal
martingale measure and the Esscher measure.
