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The standard theory of optimal stopping is based on the idealised assumption that the underlying process is essentially known. In this paper, we drop this restriction and study data-driven optimal stopping for a general diffusion process,…

Statistics Theory · Mathematics 2023-12-12 Sören Christensen , Niklas Dexheimer , Claudia Strauch

We study an optimal control problem in Bolza form and we consider the value function associated to this problem. We prove two verification theorems which ensure that, if a function $W$ satisfies some suitable weak continuity assumptions and…

Optimization and Control · Mathematics 2007-05-23 Mauro Garavello

We consider the theory of stopping bounded processes within the framework of Hudson--Parthasarathy quantum stochastic calculus, for both identity and vacuum adaptedness. This provides significant new insight into Coquio's method of stopping…

Operator Algebras · Mathematics 2018-08-01 Alexander C. R. Belton

In a classical optimal stopping problem the aim is to maximize the expected value of a functional of a diffusion evaluated at a stopping time. This note considers optimal stopping problems beyond this paradigm. We study problems in which…

Probability · Mathematics 2017-08-04 Vicky Henderson , David Hobson , Matthew Zeng

On a filtered probability space $(\Omega,\mathcal{F},P,\mathbb{F}=(\mathcal{F}_t)_{t=0,\dotso,T})$, we consider stopper-stopper games $\overline V:=\inf_{\Rho\in\bT^{ii}}\sup_{\tau\in\T}\E[U(\Rho(\tau),\tau)]$ and $\underline…

Probability · Mathematics 2017-03-29 Erhan Bayraktar , Zhou Zhou

We study the optimal stopping problem of maximizing the variance of an unkilled linear diffusion. Especially, we demonstrate how the problem can be solved as a convex two-player zero-sum game, and reveal quite surprising application of game…

Probability · Mathematics 2020-03-25 Kamille Sofie Tågholt Gad , Pekka Matomäki

In this paper we investigate a game of optimal stopping with incomplete information. There are two players of which only one is informed about the precise structure of the game. Observing the informed player the uninformed player is given…

Optimization and Control · Mathematics 2012-07-11 Christine Grün

In this paper, we study the $m$-states optimal switching problem in finite horizon, when the switching cost functions are arbitrary and can be positive or negative. This has an economic incentive in terms of central evaluation in cases…

Optimization and Control · Mathematics 2016-05-06 Brahim El Asri , Imade Fakhouri

A Dynkin game is considered for stochastic differential equations with random coefficients. We first apply Qiu and Tang's maximum principle for backward stochastic partial differential equations to generalize Krylov estimate for the…

Optimization and Control · Mathematics 2011-09-27 Shanjian Tang , Zhou Yang

In this paper we propose a new way of proving the value of a firm that is currently producing a certain product and faces the option to exit the market. The problem of optimal exiting is an optimal stopping problem, that can be solved using…

Optimization and Control · Mathematics 2013-09-23 Manuel Guerra , Cláudia Nunes , Carlos Oliveira

We characterise the value function of the optimal dividend problem with a finite time horizon as the unique classical solution of a suitable Hamilton-Jacobi-Bellman equation. The optimal dividend strategy is realised by a Skorokhod…

Probability · Mathematics 2017-11-27 Tiziano De Angelis , Erik Ekström

This study introduces the divergence-conforming discontinuous Galerkin finite element method (DGFEM) for numerically approximating optimal control problems with distributed constraints, specifically those governed by stationary generalized…

Numerical Analysis · Mathematics 2025-04-23 Harpal Singh , Arbaz Khan

We study the numerical solution of nonlinear partially observed optimal stopping problems. The system state is taken to be a multi-dimensional diffusion and drives the drift of the observation process, which is another multi-dimensional…

Optimization and Control · Mathematics 2010-01-20 Mike Ludkovski

In this Note we study optimal stopping problems for strong Markov processes and affine functions. We give a justification of the Snell envelope form using standard results of optimal stopping. We also justify the convexity of the value…

Probability · Mathematics 2008-12-18 Diana Dorobantu

We analyze an optimal stopping problem with a constraint on the expected cost. When the reward function and cost function are Lipschitz continuous in state variable, we show that the value of such an optimal stopping problem is a continuous…

Optimization and Control · Mathematics 2017-08-08 Erhan Bayraktar , Song Yao

This paper studies the problem of the deterministic version of the Verification Theorem for the optimal m-states switching in infinite horizon under Markovian framework with arbitrary switching cost functions. The problem is formulated as…

Probability · Mathematics 2013-11-15 Brahim El Asri

In a classical problem for the stopping of a diffusion process $(X_t)_{t \geq 0}$, where the goal is to maximise the expected discounted value of a function of the stopped process ${\mathbb E}^x[e^{-\beta \tau}g(X_\tau)]$, maximisation…

Probability · Mathematics 2020-04-27 David Hobson

In this paper we consider an energy storage optimization problem in finite time in a model with partial information that allows for a changing economic environment. The state process consists of the storage level controlled by the storage…

Mathematical Finance · Quantitative Finance 2016-06-21 Anton A. Shardin , Michaela Szölgyenyi

For an infinite-horizon continuous-time optimal stopping problem under non-exponential discounting, we look for an optimal equilibrium, which generates larger values than any other equilibrium does on the entire state space. When the…

Optimization and Control · Mathematics 2021-07-15 Yu-Jui Huang , Zhou Zhou

Score-based methods have recently seen increasing popularity in modeling and generation. Methods have been constructed to perform hypothesis testing and change-point detection with score functions, but these methods are in general not as…

Machine Learning · Statistics 2025-06-23 Sean Moushegian , Taposh Banerjee , Vahid Tarokh