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This article treats both discrete time and continuous time stopping problems for general Markov processes on the real line with general linear costs. Using an auxiliary function of maximum representation type, conditions are given to…

Probability · Mathematics 2020-01-28 Sören Christensen , Tobias Sohr

This paper is concerned with the solution of the optimal stopping problem associated to the valuation of Perpetual American options driven by continuous time Markov chains. We introduce a new dynamic approach for the numerical pricing of…

Probability · Mathematics 2019-04-25 Laurent Miclo , Stéphane Villeneuve

This paper deals with the optimal stopping problem under partial observation for piecewise-deterministic Markov processes. We first obtain a recursive formulation of the optimal filter process and derive the dynamic programming equation of…

Probability · Mathematics 2013-05-28 Adrien Brandejsky , Benoîte de Saporta , François Dufour

In the literature on optimal stopping, the problem of maximizing the expected discounted reward over all stopping times has been explicitly solved for some special reward functions (including $(x^+)^{\nu}$, $(e^x-K)^+$, $(K-e^{-x})^+$,…

Probability · Mathematics 2017-10-13 Yi-Shen Lin , Yi-Ching Yao

Standard Markovian optimal stopping problems are consistent in the sense that the first entrance time into the stopping set is optimal for each initial state of the process. Clearly, the usual concept of optimality cannot in a…

Optimization and Control · Mathematics 2018-12-05 Sören Christensen , Kristoffer Lindensjö

We investigate an optimal stopping problem for the expected value of a discounted payoff on a regime-switching geometric Brownian motion under two constraints on the possible stopping times: only at exogenous random times and only during a…

Probability · Mathematics 2024-11-20 Takuji Arai , Masahiko Takenaka

For a discrete time Markov chain and in line with Strotz' consistent planning we develop a framework for problems of optimal stopping that are time-inconsistent due to the consideration of a non-linear function of an expected reward. We…

Optimization and Control · Mathematics 2020-01-23 Sören Christensen , Kristoffer Lindensjö

We present a novel method for solving a class of time-inconsistent optimal stopping problems by reducing them to a family of standard stochastic optimal control problems. In particular, we convert an optimal stopping problem with a…

Optimization and Control · Mathematics 2016-11-15 Christopher W. Miller

Many discrete-time optimal stopping problems are known to have more tractable limit forms based on a planar Poisson process. Using this tool we find a solution to the optimal stopping problem for i.i.d. sequence of $n$ discrete uniform…

Probability · Mathematics 2026-01-09 Alexander Gnedin

This article treats long term average impulse control problems with running costs in the case that the underlying process is a L\'evy process. Under quite general conditions we characterize the value of the control problem as the value of a…

Probability · Mathematics 2020-05-15 Sören Christensen , Tobias Sohr

This paper is dedicated to the investigation of a new numerical method to approximate the optimal stopping problem for a discrete-time continuous state space Markov chain under partial observations. It is based on a two-step discretization…

Optimization and Control · Mathematics 2016-02-16 Benoîte de Saporta , François Dufour , Christophe Nivot

We consider optimal stopping problems for a Brownian motion and a geometric Brownian motion with a "disorder", assuming that the moment of a disorder is uniformly distributed on a finite interval. Optimal stopping rules are found as the…

Statistics Theory · Mathematics 2012-12-18 A. N. Shiryaev , M. V. Zhitlukhin

Our purpose is to study a particular class of optimal stopping problems for Markov processes. We justify the value function convexity and we deduce that there exists a boundary function such that the smallest optimal stopping time is the…

Probability · Mathematics 2013-07-22 Diana Dorobantu

We study a problem when a solution to optimal stopping problem for one-dimensional diffusion will generate by threshold strategy. Namely, we give necessary and sufficient conditions under which an optimal stopping time can be specified as…

Probability · Mathematics 2013-06-20 V. I. Arkin , A. D. Slastnikov

In this paper we consider stopping problems for continuous-time Markov chains under a general risk-sensitive optimization criterion for problems with finite and infinite time horizon. More precisely our aim is to maximize the certainty…

Probability · Mathematics 2019-07-05 Nicole Bäuerle , Anton Popp

We consider mean-field control problems in discrete time with discounted reward, infinite time horizon and compact state and action space. The existence of optimal policies is shown and the limiting mean-field problem is derived when the…

Optimization and Control · Mathematics 2025-10-16 Nicole Bäuerle

This paper deals with the long run average continuous control problem of piecewise deterministic Markov processes (PDMP's) taking values in a general Borel space and with compact action space depending on the state variable. The control…

Probability · Mathematics 2008-09-03 O. L. V. Costa , F. Dufour

In this paper, we present a novel method for computing the asymptotic values of both the optimal threshold, and the probability of success in sequences of optimal stopping problems. This method, based on the resolution of a first-order…

Probability · Mathematics 2022-05-18 L. Bayón , P. Fortuny , J. M. Grau , A. M. Oller-Marcén , M. M. Ruiz

For any quantity of interest in a system governed by ordinary differential equations, it is natural to seek the largest (or smallest) long-time average among solution trajectories, as well as the extremal trajectories themselves. Upper…

Dynamical Systems · Mathematics 2019-04-16 Ian Tobasco , David Goluskin , Charles R. Doering

We develop methods to solve general optimal stopping problems with opportunities to stop that arrive randomly. Such problems occur naturally in applications with market frictions. Pivotal to our approach is that our methods operate on…

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