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In this paper we consider an infinite time horizon risk-sensitive optimal stopping problem for a Feller--Markov process with an unbounded terminal cost function. We show that in the unbounded case an associated Bellman equation may have…

Optimization and Control · Mathematics 2022-11-01 Damian Jelito , Łukasz Stettner

In this paper, we develop an interior-point method for solving a class of convex optimization problems with time-varying objective and constraint functions. Using log-barrier penalty functions, we propose a continuous-time dynamical system…

Optimization and Control · Mathematics 2016-08-29 Mahyar Fazlyab , Santiago Paternain , Victor M. Preciado , Alejandro Ribeiro

In the classical optimal stopping problem, a player is given a sequence of random variables $X_1\ldots X_n$ with known distributions. After observing the realization of $X_i$, the player can either accept the observed reward from $X_i$ and…

Discrete Mathematics · Computer Science 2020-07-24 Shipra Agrawal , Jay Sethuraman , Xingyu Zhang

We consider an optimal stopping time problem related with many models found in real options problems. The main goal of this work is to bring for the field of real options, different and more realistic pay-off functions, and negative…

Optimization and Control · Mathematics 2017-01-10 Manuel Guerra , Cláudia Nunes , Carlos Oliveira

We study an optimal stopping problem with an unbounded, time-dependent and discontinuous reward function. This problem is motivated by the pricing of a variable annuity contract with guaranteed minimum maturity benefit, under the assumption…

Mathematical Finance · Quantitative Finance 2026-03-10 Anne Mackay , Marie-Claude Vachon

We consider a class of time-inhomogeneous optimal stopping problems and we provide sufficient conditions on the data of the problem that guarantee monotonicity of the optimal stopping boundary. In our setting, time-inhomogeneity stems not…

Optimization and Control · Mathematics 2023-01-16 Alessandro Milazzo

Pricing financial or real options with arbitrary payoffs in regime-switching models is an important problem in finance. Mathematically, it is to solve, under certain standard assumptions, a general form of optimal stopping problems in…

Mathematical Finance · Quantitative Finance 2018-09-11 Masahiko Egami , Rusudan Kevkhishvili

We propose a recursive algorithm for the numerical computation of the optimal value function $\inf_{t\le\tau\le T} E \Big[\sup_{0\le s\le T } Y_s / Y_{\tau} \big| {\cal F}_t\Big]$ over the stopping times $\tau$ with respect to the…

Probability · Mathematics 2017-02-09 Yue Liu , Nicolas Privault

We solve the non-discounted, finite-horizon optimal stopping problem of a Gauss-Markov bridge by using a time-space transformation approach. The associated optimal stopping boundary is proved to be Lipschitz continuous on any closed…

Probability · Mathematics 2024-07-08 Abel Azze , Bernardo D'Auria , Eduardo García-Portugués

This paper studies an optimal stochastic impulse control problem in a finite horizon with a decision lag, by which we mean that after an impulse is made, a fixed number units of time has to be elapsed before the next impulse is allowed to…

Optimization and Control · Mathematics 2021-02-09 Chang Li , Jiongmin Yong

We present a solution to an optimal stopping problem for a process with a wide-class of novel dynamics. The dynamics model the support/resistance line concept from financial technical analysis.

Mathematical Finance · Quantitative Finance 2020-03-30 Jun Maeda , Saul D. Jacka

We develop a method to solve, theoretically and numerically, general optimal stopping problems. Our general setting allows for multiple exercise rights, i.e., optimal multiple stopping, for a robust evaluation that accounts for model…

We address an optimal stopping problem over the set of Bermudan-type strategies $\Theta$ (which we understand in a more general sense than the stopping strategies for Bermudan options in finance) and with non-linear operators (non-linear…

Optimization and Control · Mathematics 2023-01-27 Miryana Grigorova , Marie-Claire Quenez , Peng Yuan

We study optimal stopping for diffusion processes with unknown model primitives within the continuous-time reinforcement learning (RL) framework developed by Wang et al. (2020), and present applications to option pricing and portfolio…

Optimization and Control · Mathematics 2025-08-12 Min Dai , Yu Sun , Zuo Quan Xu , Xun Yu Zhou

In this article we consider a toy example of an optimal stopping problem driven by fragmentation processes. We show that one can work with the concept of stopping lines to formulate the notion of an optimal stopping problem and moreover, to…

Probability · Mathematics 2011-01-27 Andreas E. Kyprianou , Juan Carlos Pardo

In this paper, we derive a new handy integral equation for the free-boundary of infinite time horizon, continuous time, stochastic, irreversible investment problems with uncertainty modeled as a one-dimensional, regular diffusion $X$. The…

Portfolio Management · Quantitative Finance 2015-01-21 Giorgio Ferrari

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

Let $X$ be a bounded c\`adl\`ag process with positive jumps defined on the canonical space of continuous paths. We consider the problem of optimal stopping the process $X$ under a nonlinear expectation operator $\cE$ defined as the supremum…

Probability · Mathematics 2013-02-12 Ibrahim Ekren , Nizar Touzi , Jianfeng Zhang

Inspired by recent work of P.-L. Lions on conditional optimal control, we introduce a problem of optimal stopping under bounded rationality: the objective is the expected payoff at the time of stopping, conditioned on another event. For…

Optimization and Control · Mathematics 2019-10-15 Marcel Nutz , Yuchong Zhang

We consider a discounted infinite horizon optimal stopping problem. If the underlying distribution is known a priori, the solution of this problem is obtained via dynamic programming (DP) and is given by a well known threshold rule. When…

Machine Learning · Computer Science 2021-02-23 Daniel Russo , Assaf Zeevi , Tianyi Zhang
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