English

Rate of Strong Convergence to Markov-modulated Brownian motion

Probability 2019-08-30 v1

Abstract

In Latouche and Nguyen (2015), the authors constructed a sequence of stochastic fluid processes and showed that it converges weakly to a Markov-modulated Brownian motion (MMBM). Here, we construct a different sequence of stochastic fluid processes and show that it converges strongly to an MMBM. To the best of our knowledge, this is the first result on strong convergence to a Markov-modulated Brownian motion. We also prove that the rate of this almost sure convergence is o(n1/2logn)o(n^{-1/2} \log n). When reduced to the special case of standard Brownian motion, our convergence rate is an improvement over that obtained by a different approximation in \cite{gorostiza1980rate}, which is o(n1/2(logn)5/2)o(n^{-1/2}(\log n)^{5/2}).

Keywords

Cite

@article{arxiv.1908.11075,
  title  = {Rate of Strong Convergence to Markov-modulated Brownian motion},
  author = {Giang T. Nguyen and Oscar Peralta},
  journal= {arXiv preprint arXiv:1908.11075},
  year   = {2019}
}