Sequential tracking of an unobservable two-state Markov process under Brownian noise
Probability
2019-08-06 v1 Statistics Theory
Statistics Theory
Abstract
We consider an optimal control problem, where a Brownian motion with drift is sequentially observed, and the sign of the drift coefficient changes at jump times of a symmetric two-state Markov process. The Markov process itself is not observable, and the problem consist in finding a {-1,1}-valued process that tracks the unobservable process as close as possible. We present an explicit construction of such a process.
Cite
@article{arxiv.1908.01162,
title = {Sequential tracking of an unobservable two-state Markov process under Brownian noise},
author = {Alexey Muravlev and Mikhail Urusov and Mikhail Zhitlukhin},
journal= {arXiv preprint arXiv:1908.01162},
year = {2019}
}
Comments
18 pages