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In this article, we study the classical finite-horizon optimal stopping problem for multidimensional diffusions through an approach that differs from what is typically found in the literature. More specifically, we first prove a key…

Optimization and Control · Mathematics 2025-03-05 Andrea Cosso , Laura Perelli

Many natural systems exhibit phase transition where external environmental conditions spark a shift to a new and sometimes quite different state. Therefore, detecting the behavior of a stochastic dynamic system such as the most probable…

Optimization and Control · Mathematics 2023-03-02 Jianyu Chen , Ting Gao , Yang Li , Jinqiao Duan

We consider an infinite horizon optimal control problem for a pure jump Markov process $X$, taking values in a complete and separable metric space $I$, with noise-free partial observation. The observation process is defined as $Y_t =…

Optimization and Control · Mathematics 2020-03-05 Alessandro Calvia

We study an optimal stopping problem when the state process is governed by a general Feller process. In particular, we examine viscosity properties of the associated value function with no a priori assumption on the stochastic differential…

Optimization and Control · Mathematics 2018-03-13 Suhang Dai , Olivier Menoukeu-Pamen

This paper presents a derivation of the explicit price for the perpetual American put option time-capped by the first drawdown epoch beyond a predefined level. We consider the market in which an asset price is described by geometric L\'evy…

Probability · Mathematics 2025-09-01 Zbigniew Palmowski , Paweł Stȩpniak

We consider a classical finite horizon optimal control problem for continuous-time pure jump Markov processes described by means of a rate transition measure depending on a control parameter and controlled by a feedback law. For this class…

Probability · Mathematics 2015-01-20 Elena Bandini , Marco Fuhrman

In this paper we assume the insurance wealth process is driven by the compound Poisson process. The discounting factor is modelled as a geometric Brownian motion at first and then as an exponential function of an integrated…

Mathematical Finance · Quantitative Finance 2018-07-24 Linlin Tian , Xiaoyi Zhang

We consider an interacting particle system modeled as a system of $N$ stochastic differential equations driven by Brownian motions. We prove that the (mollified) empirical process converges, uniformly in time and space variables, to the…

Probability · Mathematics 2020-10-19 Franco Flandoli , Christian Olivera , Marielle Simon

We consider the control problem with \textit{exit time}. Unlike the Bolza and Mayer problems, in this problem the terminal time of the trajectories is not fixed, but it is the first time at which they reach a given closed subset -…

Optimization and Control · Mathematics 2017-05-10 Luong V. Nguyen

We investigate the asymptotic properties of a finite-time horizon linear-quadratic optimal control problem driven by a multiscale stochastic process with multiplicative Brownian noise. We approach the problem by considering the associated…

Optimization and Control · Mathematics 2020-11-19 Beniamin Goldys , Gianmario Tessitore , James Yang , Zhou Zhou

We consider a kind of stochastic exit time optimal control problems, in which the cost function is defined through a nonlinear backward stochastic differential equation. We study the regularity of the value function for such a control…

Probability · Mathematics 2016-03-15 Rainer Buckdahn , Tianyang Nie

We study the asymptotic behavior of estimators of a two-valued, discontinuous diffusion coefficient in a Stochastic Differential Equation, called an Oscillating Brownian Motion. Using the relation of the latter process with the Skew…

Probability · Mathematics 2017-01-10 Antoine Lejay , Paolo Pigato

The Black-Scholes implied volatility skew at the money of SPX options is known to obey a power law with respect to the time-to-maturity. We construct a model of the underlying asset price process which is dynamically consistent to the power…

Mathematical Finance · Quantitative Finance 2015-01-29 Masaaki Fukasawa

In this paper we develop a deep learning method for optimal stopping problems which directly learns the optimal stopping rule from Monte Carlo samples. As such, it is broadly applicable in situations where the underlying randomness can…

Numerical Analysis · Mathematics 2021-11-02 Sebastian Becker , Patrick Cheridito , Arnulf Jentzen

In a classical optimal stopping problem in continuous time, the agent can choose any stopping time without constraint. Dupuis and Wang (Optimal stopping with random intervention times, Advances in Applied Probability, 34, 141--157, 2002)…

Probability · Mathematics 2019-01-23 David Hobson , Matthew Zeng

We model the price of a stock via a Lang\'{e}vin equation with multi-dimensional fluctuations coupled in the price and in time. We generalize previous models in that we assume that the fluctuations conditioned on the time step are compound…

Mathematical Physics · Physics 2008-12-10 Przemyslaw Repetowicz , Peter Richmond

We consider a stochastic flow driven by a finite dimensional Brownian motion. We show that almost every realization of such a flow exhibits strong statistical properties such as the exponential convergence of an initial measure to the…

Probability · Mathematics 2007-05-23 Dmitry Dolgopyat , Vadim Kaloshin , Leonid Koralov

The basic problem of optimal transportation consists in minimizing the expected costs $\mathbb {E}[c(X_1,X_2)]$ by varying the joint distribution $(X_1,X_2)$ where the marginal distributions of the random variables $X_1$ and $X_2$ are…

Probability · Mathematics 2016-08-14 Mathias Beiglböck , Nicolas Juillet

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

We study the stochastic control-stopping problem when the data are of polynomial growth. The approach is based on backward stochastic dierential equations (BSDEs for short). The problem turns into the study of a specic reected BSDE with a…

Optimization and Control · Mathematics 2020-05-15 Brahim Asri , Said Hamadène , Khalid Oufdil