Two-sided reflected Markov-modulated Brownian motion with applications to fluid queues and dividend payouts

Mathematics – Probability

Scientific paper

Rate now

  [ 0.00 ] – not rated yet Voters 0   Comments 0

Details

22 pages, 1 figure

Scientific paper

In this paper we study a reflected Markov-modulated Brownian motion with a two sided reflection in which the drift, diffusion coefficient and the two boundaries are (jointly) modulated by a finite state space irreducible continuous time Markov chain. The goal is to compute the stationary distribution of this Markov process, which in addition to the complication of having a stochastic boundary can also include jumps at state change epochs of the underlying Markov chain because of the boundary changes. We give the general theory and then specialize to the case where the underlying Markov chain has two states. Moreover, motivated by an application of optimal dividend strategies, we consider the case where the lower barrier is zero and the upper barrier is subject to control. In this case we generalized earlier results from the case of a reflected Brownian motion to the Markov modulated case.

No associations

LandOfFree

Say what you really think

Search LandOfFree.com for scientists and scientific papers. Rate them and share your experience with other people.

Rating

Two-sided reflected Markov-modulated Brownian motion with applications to fluid queues and dividend payouts does not yet have a rating. At this time, there are no reviews or comments for this scientific paper.

If you have personal experience with Two-sided reflected Markov-modulated Brownian motion with applications to fluid queues and dividend payouts, we encourage you to share that experience with our LandOfFree.com community. Your opinion is very important and Two-sided reflected Markov-modulated Brownian motion with applications to fluid queues and dividend payouts will most certainly appreciate the feedback.

Rate now

     

Profile ID: LFWR-SCP-O-296365

  Search
All data on this website is collected from public sources. Our data reflects the most accurate information available at the time of publication.