SELLING AT THE ULTIMATE MAXIMUM IN A REGIME-SWITCHING MODEL
Yue Liu () and
Nicolas Privault
Additional contact information
Yue Liu: School of Finance and Economics, Jiangsu University, Zhenjiang 212013, P. R. China
International Journal of Theoretical and Applied Finance (IJTAF), 2017, vol. 20, issue 03, 1-27
Abstract:
This paper deals with optimal prediction in a regime-switching model driven by a continuous-time Markov chain. We extend existing results for geometric Brownian motion by deriving optimal stopping strategies that depend on the current regime state and prove a number of continuity properties relating to optimal value and boundary functions. Our approach replaces the use of closed form expressions, which are not available in our setting, with PDE arguments that also simplify the approach of [du Toit & Peskir (2009) Selling a stock at the ultimate maximum, Annals of Applied Probability 19 (3), 983–1014.] in the classical Brownian case.
Keywords: Optimal stopping; ultimate maximum; regime-switching models; free boundary problems; diffusion processes (search for similar items in EconPapers)
Date: 2017
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (4)
Downloads: (external link)
http://www.worldscientific.com/doi/abs/10.1142/S0219024917500182
Access to full text is restricted to subscribers
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:wsi:ijtafx:v:20:y:2017:i:03:n:s0219024917500182
Ordering information: This journal article can be ordered from
DOI: 10.1142/S0219024917500182
Access Statistics for this article
International Journal of Theoretical and Applied Finance (IJTAF) is currently edited by L P Hughston
More articles in International Journal of Theoretical and Applied Finance (IJTAF) from World Scientific Publishing Co. Pte. Ltd.
Bibliographic data for series maintained by Tai Tone Lim ().