An elementary approach to optimal stopping problems for AR(1) sequences

Christensen, S; Irle, A; Novikov, A

An elementary approach to optimal stopping problems for AR(1) sequences

Christensen, S Irle, A Novikov, A

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Publication Type:: Journal Article
Citation:: Sequential Analysis, 2011, 30 (1), pp. 79 - 93
Issue Date:: 2011-01-01

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Field	Value	Language
dc.contributor.author	Christensen, S	en_US
dc.contributor.author	Irle, A	en_US
dc.contributor.author	Novikov, A https://orcid.org/0000-0001-8529-173X	en_US
dc.date.issued	2011-01-01	en_US
dc.identifier.citation	Sequential Analysis, 2011, 30 (1), pp. 79 - 93	en_US
dc.identifier.issn	0747-4946	en_US
dc.identifier.uri	http://hdl.handle.net/10453/17957
dc.description.abstract	Optimal stopping problems form a class of stochastic optimization problems that has a wide range of applications in sequential statistics and mathematical finance. Here we consider a general optimal stopping problem with discounting for autoregressive processes. Our strategy for a solution consists of two steps: First we give elementary conditions to ensure that an optimal stopping time is of threshold type. Then the resulting one-dimensional problem of finding the optimal threshold is to be solved explicitly. The second step is carried out for the case of exponentially distributed innovations. © Taylor & Francis Group, LLC.	en_US
dc.relation.ispartof	Sequential Analysis	en_US
dc.relation.isbasedon	10.1080/07474946.2011.539925	en_US
dc.subject.classification	Statistics & Probability	en_US
dc.title	An elementary approach to optimal stopping problems for AR(1) sequences	en_US
dc.type	Journal Article
utslib.citation.volume	1	en_US
utslib.citation.volume	30	en_US
utslib.for	010406 Stochastic Analysis and Modelling	en_US
utslib.for	0104 Statistics	en_US
pubs.embargo.period	Not known	en_US
pubs.organisational-group	/University of Technology Sydney
pubs.organisational-group	/University of Technology Sydney/Faculty of Science
pubs.organisational-group	/University of Technology Sydney/Faculty of Science/School of Mathematical and Physical Sciences
pubs.organisational-group	/University of Technology Sydney/Strength - QFRC - Quantitative Finance Research Centre
utslib.copyright.status	closed_access
pubs.issue	1	en_US
pubs.publication-status	Published	en_US
pubs.volume	30	en_US

Abstract:

Optimal stopping problems form a class of stochastic optimization problems that has a wide range of applications in sequential statistics and mathematical finance. Here we consider a general optimal stopping problem with discounting for autoregressive processes. Our strategy for a solution consists of two steps: First we give elementary conditions to ensure that an optimal stopping time is of threshold type. Then the resulting one-dimensional problem of finding the optimal threshold is to be solved explicitly. The second step is carried out for the case of exponentially distributed innovations. © Taylor & Francis Group, LLC.

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http://hdl.handle.net/10453/17957