69
Views
2
CrossRef citations to date
0
Altmetric
Original Articles

A model of finite-step random walk with absorbent boundaries

, &
Pages 1685-1696 | Received 22 Feb 2007, Accepted 23 Jun 2007, Published online: 07 Oct 2008
 

Abstract

This paper proposes a model of finite-step lattice random walk with absorbent boundaries. We address a problem of optimal stop for this model, which is defined as the absorbent boundary value with maximum profit. Compared with many existing optimal stop investigations in the random process, our study only considers the small-sample behaviour (i.e., small number of steps behaviour) and does not consider the limit behaviour of the walk. The optimal stop time is given based on classical probability computation. Since the small-sample is more practical and common than the large-sample in many real world problems, the result obtained in this paper may provide some useful guidelines for real applications associated with the finite-step random walk such as the stock market and gambling games.

2000 AMS Subject Classification:

Acknowledgements

This research is supported by the National Natural Science Foundation of China (60473045). Hebei Hi-tech project (04213533) and the plan of 100 excellent innovative scientists of the first group in the Education Department of Hebei Province.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 1,129.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.