Optimal stopping for partially observed piecewise-deterministic Markov processes

9Citations
Citations of this article
8Readers
Mendeley users who have this article in their library.

Abstract

This paper deals with the optimal stopping problem under partial observation for piecewise-deterministic Markov processes. We first obtain a recursive formulation of the optimal filter process and derive the dynamic programming equation of the partially observed optimal stopping problem. Then, we propose a numerical method, based on the quantization of the discrete-time filter process and the inter-jump times, to approximate the value function and to compute an Ïμ-optimal stopping time. We prove the convergence of the algorithms and bound the rates of convergence. © 2013 Elsevier B.V. All rights reserved.

Cite

CITATION STYLE

APA

Brandejsky, A., De Saporta, B., & Dufour, F. (2013). Optimal stopping for partially observed piecewise-deterministic Markov processes. Stochastic Processes and Their Applications, 123(8), 3201–3238. https://doi.org/10.1016/j.spa.2013.03.006

Register to see more suggestions

Mendeley helps you to discover research relevant for your work.

Already have an account?

Save time finding and organizing research with Mendeley

Sign up for free