Indexing metadata

On predicting the ultimate maximum for exponential Lévy processes


 
Dublin Core PKP Metadata Items Metadata for this Document
 
1. Title Title of document On predicting the ultimate maximum for exponential Lévy processes
 
2. Creator Author's name, affiliation, country Katsunori Ano; Shibaura Institute of Technology, Tokyo; Japan
 
2. Creator Author's name, affiliation, country Roman Ivanov; Trapeznikov Institute of Control Sciences of RAS, Moscow; Russian Federation
 
3. Subject Discipline(s)
 
3. Subject Keyword(s) optimal stopping; exponential Lévy process; predicting; selling of asset; utility function
 
3. Subject Subject classification 60G25; 60G51; 60G70
 
4. Description Abstract

We consider a problem of predicting of the ultimate maximum  of the process over a finite interval of time. Mathematically, this problem relates to a particular optimal stopping problem. In this paper we discuss exponential Lévy processes. As the Lévy processes, we discuss $\alpha$-stable Lévy processes, $0<\alpha\leq 2$,  and generalized hyperbolic Lévy processes. The method of solution uses the representations of these processes as time-changed Brownian motions with drift. Our results generalize results of papers by Toit and Peskir and by Shiryaev and Xu, and Zhou.
 
5. Publisher Organizing agency, location
 
6. Contributor Sponsor(s)
 
7. Date (YYYY-MM-DD) 2012-10-07
 
8. Type Status & genre Peer-reviewed Article
 
8. Type Type
 
9. Format File format PDF
 
10. Identifier Uniform Resource Identifier http://ecp.ejpecp.org/article/view/1805
 
10. Identifier Digital Object Identifier 10.1214/ECP.v17-1805
 
11. Source Journal/conference title; vol., no. (year) Electronic Communications in Probability; Vol 17
 
12. Language English=en en
 
14. Coverage Geo-spatial location, chronological period, research sample (gender, age, etc.)
 
15. Rights Copyright and permissions The Electronic Journal of Probability applies the Creative Commons Attribution License (CCAL) to all articles we publish in this journal. Under the CCAL, authors retain ownership of the copyright for their article, but authors allow anyone to download, reuse, reprint, modify, distribute, and/or copy articles published in EJP, so long as the original authors and source are credited. This broad license was developed to facilitate open access to, and free use of, original works of all types. Applying this standard license to your work will ensure your right to make your work freely and openly available.

Summary of the Creative Commons Attribution License

You are free
  • to copy, distribute, display, and perform the work
  • to make derivative works
  • to make commercial use of the work
under the following condition of Attribution: others must attribute the work if displayed on the web or stored in any electronic archive by making a link back to the website of EJP via its Digital Object Identifier (DOI), or if published in other media by acknowledging prior publication in this Journal with a precise citation including the DOI. For any further reuse or distribution, the same terms apply. Any of these conditions can be waived by permission of the Corresponding Author.