Optimal stopping for partially observed piecewise-deterministic Markov processes

Adrien Brandejsky, Benoîte de Saporta and François Dufour

Stochastic Processes and their Applications, 2013, vol. 123, issue 8, 3201-3238

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 ϵ-optimal stopping time. We prove the convergence of the algorithms and bound the rates of convergence.

Keywords: Optimal stopping; Partial observation; Filtering; Piecewise deterministic Markov processes; Quantization; Numerical method (search for similar items in EconPapers)
Date: 2013
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Citations: View citations in EconPapers (2)

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Persistent link: https://EconPapers.repec.org/RePEc:eee:spapps:v:123:y:2013:i:8:p:3201-3238

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DOI: 10.1016/j.spa.2013.03.006

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