Solving optimal stopping problems of linear diffusions by applying convolution approximations
Luis Alvarez
Mathematical Methods of Operations Research, 2001, vol. 53, issue 1, 89-99
Abstract:
We study how the convolution approximation of continuous mappings can be applied in solving optimal stopping problems of linear diffusions whenever the underlying payoff is not differentiable and the smooth fit principle does not necessarily apply. We construct a sequence of smooth reward functions converging uniformly on compacts to the original reward and, consequently, we derive a sequence of continuously differentiable (i.e. satisfying the smooth fit principle) value functions converging to the value of the original stopping problem. Copyright Springer-Verlag Berlin Heidelberg 2001
Keywords: Key words: Optimal stopping; linear diffusions; convolution approximation; exponential distribution, AMS classification: 60G40, 49L25, 49J40, (search for similar items in EconPapers)
Date: 2001
References: Add references at CitEc
Citations: View citations in EconPapers (5)
Downloads: (external link)
http://hdl.handle.net/10.1007/s001860000098 (text/html)
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:spr:mathme:v:53:y:2001:i:1:p:89-99
Ordering information: This journal article can be ordered from
http://www.springer.com/economics/journal/00186
DOI: 10.1007/s001860000098
Access Statistics for this article
Mathematical Methods of Operations Research is currently edited by Oliver Stein
More articles in Mathematical Methods of Operations Research from Springer, Gesellschaft für Operations Research (GOR), Nederlands Genootschap voor Besliskunde (NGB)
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().