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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

We consider the optimal mass transportation problem in $\RR^d$ with measurably parameterized marginals, for general cost functions and under conditions ensuring the existence of a unique optimal transport map. We prove a joint measurability…

Probability · Mathematics 2008-09-09 Joaquin Fontbona , Helene Guerin , Sylvie Meleard

Continuity of the value of the martingale optimal transport problem on the real line w.r.t. its marginals was recently established in Backhoff-Veraguas and Pammer [2] and Wiesel [21]. We present a new perspective of this result using the…

Probability · Mathematics 2021-04-23 Ariel Neufeld , Julian Sester

We formulate and study an optimal transportation problem with infinitely many marginals; this is a natural extension of the multi-marginal problem studied by Gangbo and Swiech (1998). We prove results on the existence, uniqueness and…

Analysis of PDEs · Mathematics 2012-06-26 Brendan Pass

This paper focuses on martingale optimal transport problems when the martingales are assumed to have bounded quadratic variation. First, we give a result that characterizes the existence of a probability measure satisfying some convex…

Probability · Mathematics 2020-03-18 Erhan Bayraktar , Xin Zhang , Zhou Zhou

We introduce and study a multi-marginal optimal partial transport problem. Under a natural and sharp condition on the dominating marginals, we establish uniqueness of the optimal plan. Our strategy of proof establishes and exploits a…

Analysis of PDEs · Mathematics 2015-08-10 Jun Kitagawa , Brendan Pass

A fundamental concept in optimal transport is c-cyclical monotonicity: it allows to link the optimality of transport plans to the geometry of their support sets. Recently, related concepts have been successfully applied in the…

Probability · Mathematics 2019-08-12 Mathias Beiglböck , Claus Griessler

We study the optimal transport between two probability measures on the real line, where the transport plans are laws of one-step martingales. A quasi-sure formulation of the dual problem is introduced and shown to yield a complete duality…

Probability · Mathematics 2016-06-14 Mathias Beiglböck , Marcel Nutz , Nizar Touzi

This note contains a short discussion on the sufficiency of finite optimality in martingale transport. It is shown that finitely minimal martingale measures are solutions of the martingale transport problem when the cost function is upper…

Probability · Mathematics 2016-06-13 Claus Griessler

This note establishes that a generalization of $c$-cyclical monotonicity from the Monge-Kantorovich problem with two marginals gives rise to a sufficient condition for optimality also in the multi-marginal version of that problem. To obtain…

Optimization and Control · Mathematics 2016-01-22 Claus Griessler

We study the stability of entropically regularized optimal transport with respect to the marginals. Lipschitz continuity of the value and H\"older continuity of the optimal coupling in $p$-Wasserstein distance are obtained under general…

Optimization and Control · Mathematics 2022-07-06 Stephan Eckstein , Marcel Nutz

Our main result is to establish stability of martingale couplings: suppose that $\pi$ is a martingale coupling with marginals $\mu, \nu$. Then, given approximating marginal measures $\tilde \mu \approx \mu, \tilde \nu\approx \nu$ in convex…

Probability · Mathematics 2023-08-28 Mathias Beiglböck , Benjamin Jourdain , William Margheriti , Gudmund Pammer

While many questions in robust finance can be posed in the martingale optimal transport framework or its weak extension, others like the subreplication price of VIX futures, the robust pricing of American options or the construction of…

Probability · Mathematics 2023-04-20 Benjamin Jourdain , Gudmund Pammer

Multi-marginal optimal transport (MOT) is a generalization of optimal transport to multiple marginals. Optimal transport has evolved into an important tool in many machine learning applications, and its multi-marginal extension opens up for…

Machine Learning · Computer Science 2021-12-07 Jiaojiao Fan , Isabel Haasler , Johan Karlsson , Yongxin Chen

Under mild regularity assumptions, the transport problem is stable in the following sense: if a sequence of optimal transport plans $\pi_1, \pi_2, \ldots$ converges weakly to a transport plan $\pi$, then $\pi$ is also optimal (between its…

Probability · Mathematics 2020-12-22 Julio Backhoff-Veraguas , Gudmund Pammer

We consider an extension of the Monge-Kantorovitch optimal transportation problem. The mass is transported along a continuous semimartingale, and the cost of transportation depends on the drift and the diffusion coefficients of the…

Probability · Mathematics 2013-10-04 Xiaolu Tan , Nizar Touzi

We investigate stability properties of weak supermartingale optimal transport (WSOT) problems on $\mathbb{R}$. For probability measures $\mu,\nu\in\mathcal{P}_r$ satisfying $\mu \leq_{cd} \nu$ (equivalently, $\Pi_S(\mu,\nu)\neq\emptyset$),…

Probability · Mathematics 2026-03-31 Shuoqing Deng , Gaoyue Guo , Dominykas Norgilas

We consider optimal transportation of measures on metric and topological spaces in the case where the cost function and marginal distributions depend on a parameter with values in a metric space. The Hausdorff distance between the sets of…

Functional Analysis · Mathematics 2021-11-29 Vladimir Bogachev , Svetlana Popova

While many questions in (robust) finance can be posed in the martingale optimal transport (MOT) framework, others require to consider also non-linear cost functionals. Following the terminology of Gozlan, Roberto, Samson and Tetali this…

Probability · Mathematics 2022-04-05 Mathias Beiglböck , Benjamin Jourdain , William Margheriti , Gudmund Pammer

Multi-marginal optimal transport enables one to compare multiple probability measures, which increasingly finds application in multi-task learning problems. One practical limitation of multi-marginal transport is computational scalability…

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