Fluctuation identities for omega-killed Markov additive processes and dividend problem

Abstract: In this paper we solve the exit problems for an one-sided Markov additive process (MAP) which is exponentially killed with a bivariate killing intensity $\omega(\cdot,\cdot)$ dependent on the present level of the process and the present state of the environment. Moreover, we analyze respective resolvents. All identities are given in terms of new generalizations of classical scale matrices for the MAP. We also remark on a number of applications of the obtained identities to (controlled) insurance risk processes. In particular, we show that our results can be applied to the so-called Omega model, where bankruptcy occurs at rate $\omega(\cdot,\cdot)$ when the surplus process becomes negative. Finally, we consider the Markov modulated Brownian motion (MMBM) and present the results for the particular choice of piecewise intensity function $\omega(\cdot,\cdot)$.