Logo: to the web site of Uppsala University

uu.sePublications from Uppsala University
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Stopping problems with an unknown state
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Probability Theory and Combinatorics.ORCID iD: 0000-0001-9604-9172
Uppsala University, Disciplinary Domain of Science and Technology, Mathematics and Computer Science, Department of Mathematics, Probability Theory and Combinatorics.
2024 (English)In: Journal of Applied Probability, ISSN 0021-9002, E-ISSN 1475-6072, Vol. 61, no 2, p. 515-528Article in journal (Refereed) Published
Abstract [en]

We extend the classical setting of an optimal stopping problem under full information to include problems with an unknown state. The framework allows the unknown state to influence (i) the drift of the underlying process, (ii) the payoff functions, and (iii) the distribution of the time horizon. Since the stopper is assumed to observe the underlying process and the random horizon, this is a two-source learning problem. Assigning a prior distribution for the unknown state, standard filtering theory can be employed to embed the problem in a Markovian framework with one additional state variable representing the posterior of the unknown state. We provide a convenient formulation of this Markovian problem, based on a measure change technique that decouples the underlying process from the new state variable. Moreover, we show by means of several novel examples that this reduced formulation can be used to solve problems explicitly.

Place, publisher, year, edition, pages
Cambridge University Press, 2024. Vol. 61, no 2, p. 515-528
National Category
Mathematics
Research subject
Mathematics
Identifiers
URN: urn:nbn:se:uu:diva-506838DOI: 10.1017/jpr.2023.52ISI: 001044052700001Scopus ID: 2-s2.0-85167916123OAI: oai:DiVA.org:uu-506838DiVA, id: diva2:1777685
Available from: 2023-06-29 Created: 2023-06-29 Last updated: 2025-02-13Bibliographically approved
In thesis
1. Optimal stopping, incomplete information, and stochastic games
Open this publication in new window or tab >>Optimal stopping, incomplete information, and stochastic games
2023 (English)Doctoral thesis, comprehensive summary (Other academic)
Abstract [en]

This thesis contains six papers on the topics of optimal stopping and stochastic games. 

Paper I extends the classical Bayesian sequential testing and detection problems for a Brownian motion to higher dimensions. We demonstrate unilateral concavity of the cost function and present its structural properties through various examples.

Paper II studies the problem of sequentially testing two composite hypotheses concerning an unknown parameter within the exponential family, incorporating observation costs within the Bayesian setting. In a Markovian framework, we show that the value function is concave, and non-decreasing in time under certain assumptions, consequently leading to the monotonicity of the stopping boundaries.

Paper III formulates an optimal stopping problem involving an unknown state that influences the diffusion process drift, the payoff functions, and the distribution of the time horizon. By performing a measure change, we reformulate it into a two-dimensional stopping problem with full information. We further provide several examples where explicit solutions are possible.

Paper IV introduces some non-linear, non-local parabolic operators related to a tug-of-war game where the random waiting time is coupled with space. Following that, we state and prove the asymptotic mean value formulas of the fractional heat operator and the aforementioned operators, and discuss their probabilistic interpretations. 

Paper V considers a Dynkin game with consolation where the players act under asymmetric and incomplete information. We prove a verification result that allows us to identify a Nash equilibrium. Building upon this, we examine certain classes of problems where the equilibrium value functions and strategies can be constructed.

Paper VI addresses the Bayesian sequential estimation problem of an unknown parameter within the exponential family, considering observations with associated costs. We offer sufficient conditions for space monotonicity of the value function, and explore their consequential impacts on the structural attributes of continuation and stopping regions.

Place, publisher, year, edition, pages
Uppsala: Department of Mathematics, 2023. p. 43
Series
Uppsala Dissertations in Mathematics, ISSN 1401-2049 ; 132
Keywords
Optimal stopping, sequential analysis, incomplete information, asymmetric information, stochastic filtering, Dynkin games, tug-of-war games
National Category
Probability Theory and Statistics
Research subject
Mathematics
Identifiers
urn:nbn:se:uu:diva-506845 (URN)978-91-506-3011-4 (ISBN)
Public defence
2023-09-22, Siegbahnsalen, Ångströmlaboratoriet, Lägerhyddsvägen 1, 13:15 (English)
Opponent
Supervisors
Available from: 2023-08-30 Created: 2023-06-29 Last updated: 2023-08-30

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full textScopus

Authority records

Ekström, ErikWang, Yuqiong

Search in DiVA

By author/editor
Ekström, ErikWang, Yuqiong
By organisation
Probability Theory and Combinatorics
In the same journal
Journal of Applied Probability
Mathematics

Search outside of DiVA

GoogleGoogle Scholar

doi
urn-nbn

Altmetric score

doi
urn-nbn
Total: 76 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf