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This paper studies a class of optimal multiple stopping problems driven by L\'evy processes. Our model allows for a negative effective discount rate, which arises in a number of financial applications, including stock loans and real…

Mathematical Finance · Quantitative Finance 2016-03-11 Tim Leung , Kazutoshi Yamazaki , Hongzhong Zhang

For classical finite time horizon stopping problems driven by a Brownian motion \[V(t,x) = \sup_{t\leq\tau\leq0}E_{(t,x)}[g(\tau,W_{\tau})],\] we derive a new class of Fredholm type integral equations for the stopping set. For large problem…

Probability · Mathematics 2023-03-10 Sören Christensen , Simon Fischer

We propose a new method for solving optimal stopping problems (such as American option pricing in finance) under minimal assumptions on the underlying stochastic process $X$. We consider classic and randomized stopping times represented by…

Probability · Mathematics 2021-05-04 Christian Bayer , Paul Hager , Sebastian Riedel , John Schoenmakers

The objective of this work is to study continuous-time Markov decision processes on a general Borel state space with both impulsive and continuous controls for the infinite-time horizon discounted cost. The continuous-time controlled…

Optimization and Control · Mathematics 2019-08-17 François Dufour , Alexei Piunovskiy

We develop an approach for solving one-sided optimal stopping problems in discrete time for general underlying Markov processes on the real line. The main idea is to transform the problem into an auxiliary problem for the ladder height…

Probability · Mathematics 2018-10-29 Sören Christensen , Albrecht Irle

Consider the discounted optimal stopping problem for a real valued Markov process with only positive jumps. We provide a theorem to verify that the optimal stopping region has the form {x >= x^*} for some critical threshold x^*, and a…

Probability · Mathematics 2024-11-14 Fabian Crocce , Ernesto Mordecki

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

We consider the optimal stopping problem consisting in, given a strong Markov process, a reward function and a discount rate, finding the stopping time such that the expected reward at the stopping time is maximum. The approach we follow,…

Probability · Mathematics 2014-05-30 Fabián Crocce

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

We identify the integrable stopping time $\tau_*$ with minimal $L^1$-distance to the last-passage time $\gamma_z$ to a given level $z>0$, for an arbitrary non-negative time-homogeneous transient diffusion $X$. We demonstrate that $\tau_*$…

Probability · Mathematics 2013-12-31 Kristoffer Glover , Hardy Hulley

In this paper, we revisit the optimal periodic dividend problem, in which dividend payments can only be made at the jump times of an independent Poisson process. In the dual (spectrally positive L\'evy) model, recent results have shown the…

Optimization and Control · Mathematics 2018-02-27 Kei Noba , José-Luis Pérez , Kazutoshi Yamazaki , Kouji Yano

We present a methodology for obtaining explicit solutions to infinite time horizon optimal stopping problems involving general, one-dimensional, It\^o diffusions, payoff functions that need not be smooth and state-dependent discounting.…

Computational Finance · Quantitative Finance 2012-10-10 Timothy C. Johnson

We revisit the classical singular control problem of minimizing running and controlling costs. The problem arises in inventory control, as well as in healthcare management and mathematical finance. Existing studies have shown the optimality…

Probability · Mathematics 2022-07-18 Kei Noba , Kazutoshi Yamazaki

We address a general optimal switching problem over finite horizon for a stochastic system described by a differential equation driven by Brownian motion. The main novelty is the fact that we allow for infinitely many modes (or regimes,…

Optimization and Control · Mathematics 2019-08-07 Marco Fuhrman , Marie-Amélie Morlais

We consider the impulse control of Levy processes under the infinite horizon, discounted cost criterion. Our motivating example is the cash management problem in which a controller is charged a fixed plus proportional cost for adding to or…

Probability · Mathematics 2022-06-10 Peter Lakner , Josh Reed

In this paper, we investigate dynamic optimization problems featuring both stochastic control and optimal stopping in a finite time horizon. The paper aims to develop new methodologies, which are significantly different from those of mixed…

Portfolio Management · Quantitative Finance 2014-06-27 Xiongfei Jian , Xun Li , Fahuai Yi

An identity in law for the area of a spectrally positive L\'evy stable process stopped at zero is established. Extending that of Lefebvre for Brownian motion, it involves an inverse Beta random variable and the square of a positive stable…

Probability · Mathematics 2014-10-02 Julien Letemplier , Thomas Simon

We revisit an absolutely-continuous version of the stochastic control problem driven by a L\'evy process. A strategy must be absolutely continuous with respect to the Lebesgue measure and the running cost function is assumed to be convex.…

Probability · Mathematics 2023-08-17 Kei Noba , José Luis Pérez , Kazutoshi Yamazaki

We consider a wide class of increasing L\'evy processes perturbed by an independent Brownian motion as a degradation model. Such family contains almost all classical degradation models considered in the literature. Classically failure time…

Probability · Mathematics 2012-01-06 Christian Paroissin , Landy Rabehasaina

The core of the Model Predictive Control (MPC) method in every step of the algorithm consists in solving a time-dependent optimization problem on the prediction horizon of the MPC algorithm, and then to apply a portion of the optimal…

Optimization and Control · Mathematics 2021-01-15 Alessandro Alla , Carmen Gräßle , Michael Hinze