Abstract
Previous authors have considered optimal stopping problems driven by the running maximum of a spectrally negative Lévy process as well as of a one-dimensional diffusion; see e.g. Kyprianou and Ott (2014); Ott (2014); Ott (2013); Alvarez and Matomäki (2014); Guo and Shepp (2001); Pedersen (2000); Gapeev (2007). Many of the aforementioned results are either implicitly or explicitly dependent on Peskir's maximality principle, cf. (Peskir, 1998). In this article, we are interested in understanding how some of the main ideas from these previous works can be brought into the setting of problems driven by the maximum of a class of Markov additive processes (more precisely Markov modulated Lévy processes). Similarly to Ott (2013); Kyprianou and Ott (2014); Ott (2014), the optimal stopping boundary is characterised by a system of ordinary first-order differential equations, one for each state of the modulating component of the Markov additive process. Moreover, whereas scale functions played an important role in the previously mentioned work, we work instead with scale matrices for Markov additive processes here; as introduced by Kyprianou and Palmowski (2008); Ivanovs and Palmowski (2012). We exemplify our calculations in the setting of the Shepp–Shiryaev optimal stopping problem (Shepp and Shiryaev, 1993; Shepp and Shiryaev, 1995), as well as a family of capped maximum optimal stopping problems.
Original language | English |
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Pages (from-to) | 1109-1138 |
Journal | Stochastic Processes and their Applications |
Volume | 150 |
Early online date | 1 Jul 2021 |
DOIs | |
Publication status | Published - 31 Aug 2022 |
Bibliographical note
Funding Information:AEK and M? are grateful for reciprocal support they each received from their respective universities in order to explore Bath-Ko? collaborative research. All authors would like to thank three referees for their extensive remarks which brought about many improvements to the original document.
Keywords
- Excursion theory
- Markov additive processes
- Optimal stopping
- Scale matrices
ASJC Scopus subject areas
- Statistics and Probability
- Modelling and Simulation
- Applied Mathematics