Optimal hitting time and perpetual option in a non-Lévy model: application to real options

Pauline Barrieu and N. Bellamy

LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library

Abstract: We study the perpetual American option characteristics in the case where the underlying dynamics involve a Brownian motion and a point process with a stochastic intensity. No assumption on the distribution of the jump size is made and we work with an arbitrary positive or negative jump. After proving the existence of an optimal stopping time for the problem and characterizing it as the hitting time of an optimal boundary,we provide closed-form formulae for the option value, as well as for the Laplace transform of the optimal stopping time. These results are then applied to the analysis of a real option problem when considering the impact of a fundamental and brutal change in the investment project environment. The consequences of this impact, that can seriously modify, positively or negatively, the project’s future cash flows and therefore the investment decision, are illustrated numerically via the study of some examples.

JEL-codes: C1 (search for similar items in EconPapers)
Date: 2007
References: View references in EconPapers View complete reference list from CitEc
Citations:

Published in Advances in Applied Probability, 2007, 39(2), pp. 510-530. ISSN: 0001-8678

Downloads: (external link)
http://eprints.lse.ac.uk/5099/ Open access version. (application/pdf)

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:ehl:lserod:5099

Access Statistics for this paper

More papers in LSE Research Online Documents on Economics from London School of Economics and Political Science, LSE Library LSE Library Portugal Street London, WC2A 2HD, U.K.. Contact information at EDIRC.
Bibliographic data for series maintained by LSERO Manager (lseresearchonline@lse.ac.uk).