Geometry of distribution-constrained optimal stopping problems

We adapt ideas and concepts developed in optimal transport (and its martingale variant) to give a geometric description of optimal stopping times τ of Brownian motion subject to the constraint that the distribution of τ is a given probability μ . The methods work for a large class of cost processes....

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Bibliographic Details
Published in:Probability theory and related fields 2018-10, Vol.172 (1-2), p.71-101
Main Authors: Beiglböck, Mathias, Eder, Manu, Elgert, Christiane, Schmock, Uwe
Format: Article
Language:English
Subjects:
Brownian motion
Economics
Finance
Insurance
Management
Martingales
Mathematical and Computational Biology
Mathematical and Computational Physics
Mathematics
Mathematics and Statistics
Operations Research/Decision Theory
Probabilistic methods
Probability
Probability Theory and Stochastic Processes
Quantitative Finance
Random walk theory
Statistics for Business
Theoretical
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Summary:We adapt ideas and concepts developed in optimal transport (and its martingale variant) to give a geometric description of optimal stopping times τ of Brownian motion subject to the constraint that the distribution of τ is a given probability μ . The methods work for a large class of cost processes. (At a minimum we need the cost process to be measurable and ( F t 0 ) t ≥ 0 -adapted. Continuity assumptions can be used to guarantee existence of solutions.) We find that for many of the cost processes one can come up with, the solution is given by the first hitting time of a barrier in a suitable phase space. As a by-product we recover classical solutions of the inverse first passage time problem/Shiryaev’s problem.
ISSN:0178-8051
1432-2064
DOI:10.1007/s00440-017-0805-x