Irreducible convex paving for decomposition of multi-dimensional martingale transport plans

Martingale transport plans on the line are known from Beiglbock & Juillet to have an irreducible decomposition on a (at most) countable union of intervals. We provide an extension of this decomposition for martingale transport plans in R^d, d larger than one. Our decomposition is a partition of R^d consisting of a possibly uncountable family of relatively open convex components, with the required measurability so that the disintegration is well-defined. We justify the relevance of our decomposition by proving the existence of a martingale transport plan filling these components. We also deduce from this decomposition a characterization of the structure of polar sets with respect to all martingale transport plans.Comment: 52 pages, 2 figure

Optimal trading using signals

In this paper we propose a mathematical framework to address the uncertainty emergingwhen the designer of a trading algorithm uses a threshold on a signal as a control. We rely ona theorem by Benveniste and Priouret to deduce our Inventory Asymptotic Behaviour (IAB)Theorem giving the full distribution of the inventory at any point in time for a well formulatedtime continuous version of the trading algorithm.Since this is the first time a paper proposes to address the uncertainty linked to the use of athreshold on a signal for trading, we give some structural elements about the kind of signals thatare using in execution. Then we show how to control this uncertainty for a given cost function.There is no closed form solution to this control, hence we propose several approximation schemesand compare their performances.Moreover, we explain how to apply the IAB Theorem to any trading algorithm drivenby a trading speed. It is not needed to control the uncertainty due to the thresholding of asignal to exploit the IAB Theorem; it can be applied ex-post to any traditional trading algorithm.Comment: 21 pages, 5 figur

Quasi-sure duality for multi-dimensional martingale optimal transport

43 pages, 3 figuresBased on the multidimensional irreducible paving of De March & Touzi, we provide a multi-dimensional version of the quasi sure duality for the martingale optimal transport problem, thus extending the result of Beiglb\"ock, Nutz & Touzi. Similar, we also prove a disintegration result which states a natural decomposition of the martingale optimal transport problem on the irreducible components, with pointwise duality verified on each component. As another contribution, we extend the martingale monotonicity principle to the present multi-dimensional setting. Our results hold in dimensions 1, 2, and 3 provided that the target measure is dominated by the Lebesgue measure. More generally, our results hold in any dimension under an assumption which is implied by the Continuum Hypothesis. Finally, in contrast with the one-dimensional setting of Beiglb\"ock, Lim & Obloj, we provide an example which illustrates that the smoothness of the coupling function does not imply that pointwise duality holds for compactly supported measures

Transport optimal de martingale multidimensionnel.

In this thesis, we study various aspects of martingale optimal transport in dimension greater than one, from duality to local structure, and finally we propose numerical approximation methods.We first prove the existence of irreducible intrinsic components to martingal transport between two given measurements, as well as the canonicity of these components. We have then proved a duality result for optimal martingale transport in any dimension, point by-point duality is no longer true but a form of quasi safe duality is demonstrated. This duality makes it possible to demonstrate the possibility of decomposing the quasi-safe optimal transport into a series of optimal transport subproblems point by point on each irreducible component. Finally, this duality is used to demonstrate a principle of martingale monotony, analogous to the famous monotonic principle of classical optimal transport. We then study the local structure of optimal transport, deduced from differential considerations. We thus obtain a characterization of this structure using tools of real algebraic geometry. We deduce the optimal martingal transport structure in the case of the power costs of the Euclidean norm, which makes it possible to solve a conjecture that dates from 2015. Finally, we compared the existingnumerical methods and proposed a new method which proves more efficient and allows to treat an intrinsic problem of the martingale constraint which is the defect of convex order. Techniques are also provided to manage digital problems in practice.Nous étudions dans cette thèse divers aspects du transport optimal martingale en dimension plus grande que un, de la dualité à la structure locale, puis nous proposons finalement des méthodes d’approximation numérique.On prouve d’abord l’existence de composantes irréductibles intrinsèques aux transports martingales entre deux mesures données, ainsi que la canonicité de ces composantes. Nous avons ensuite prouvé un résultat de dualité pour le transport optimal martingale en dimension quelconque, la dualité point par point n’est plus vraie mais une forme de dualité quasi-sûre est démontrée. Cette dualité permet de démontrer la possibilité de décomposer le transport optimal quasi-sûre en une série de sous-problèmes de transports optimaux point par point sur chaque composante irréductible. On utilise enfin cette dualité pour démontrer un principe de monotonie martingale, analogue au célèbre principe de monotonie du transport optimal classique. Nous étudions ensuite la structure locale des transports optimaux, déduite de considérations différentielles. On obtient ainsi une caractérisation de cette structure en utilisant des outils de géométrie algébrique réelle. On en déduit la structure des transports optimaux martingales dans le cas des coûts puissances de la norme euclidienne, ce qui permet de résoudre une conjecture qui date de 2015. Finalement, nous avons comparé les méthodes numériques existantes et proposé une nouvelle méthode qui s’avère plus efficace et permet de traiter un problème intrinsèque de la contrainte martingale qu’est le défaut d’ordre convexe. On donne également des techniques pour gérer en pratique les problèmes numériques

Local structure of multi-dimensional martingale optimal transport

36 pages, 6 figuresThis paper analyzes the support of the conditional distribution of optimal martingale transport plans in higher dimension. In the context of a distance coupling in dimension larger than 2, previous results established by Ghoussoub, Kim & Lim show that this conditional transport is concentrated on its own Choquet boundary. Moreover, when the target measure is atomic, they prove that the support is concentrated on d+1 points, and conjecture that this result is valid for arbitrary target measure. We provide a structure result of the support of the conditional optimal transport for general Lipschitz couplings. Using tools from algebraic geometry, we provide sufficient conditions for finiteness of this conditional support, together with (optimal) lower bounds on the maximal cardinality for a given coupling function. More results are obtained for specific examples of coupling functions based on distance functions. In particular, we show that the above conjecture of Ghoussoub, Kim & Lim is not valid beyond the context of atomic target distributions

Entropic approximation for multi-dimensional martingale optimal transport

48 pages, 4 figuresWe study the existing algorithms that solve the multidimensional martingale optimal transport. Then we provide a new algorithm based on entropic regularization and Newton's method. Then we provide theoretical convergence rate results and we check that this algorithm performs better through numerical experiments. We also give a simple way to deal with the absence of convex ordering among the marginals. Furthermore, we provide a new universal bound on the error linked to entropy

Multidimensional martingale optimal transport.

Nous étudions dans cette thèse divers aspects du transport optimal martingale en dimension plus grande que un, de la dualité à la structure locale, puis nous proposons finalement des méthodes d’approximation numérique.On prouve d’abord l’existence de composantes irréductibles intrinsèques aux transports martingales entre deux mesures données, ainsi que la canonicité de ces composantes. Nous avons ensuite prouvé un résultat de dualité pour le transport optimal martingale en dimension quelconque, la dualité point par point n’est plus vraie mais une forme de dualité quasi-sûre est démontrée. Cette dualité permet de démontrer la possibilité de décomposer le transport optimal quasi-sûre en une série de sous-problèmes de transports optimaux point par point sur chaque composante irréductible. On utilise enfin cette dualité pour démontrer un principe de monotonie martingale, analogue au célèbre principe de monotonie du transport optimal classique. Nous étudions ensuite la structure locale des transports optimaux, déduite de considérations différentielles. On obtient ainsi une caractérisation de cette structure en utilisant des outils de géométrie algébrique réelle. On en déduit la structure des transports optimaux martingales dans le cas des coûts puissances de la norme euclidienne, ce qui permet de résoudre une conjecture qui date de 2015. Finalement, nous avons comparé les méthodes numériques existantes et proposé une nouvelle méthode qui s’avère plus efficace et permet de traiter un problème intrinsèque de la contrainte martingale qu’est le défaut d’ordre convexe. On donne également des techniques pour gérer en pratique les problèmes numériques.In this thesis, we study various aspects of martingale optimal transport in dimension greater than one, from duality to local structure, and finally we propose numerical approximation methods.We first prove the existence of irreducible intrinsic components to martingal transport between two given measurements, as well as the canonicity of these components. We have then proved a duality result for optimal martingale transport in any dimension, point by-point duality is no longer true but a form of quasi safe duality is demonstrated. This duality makes it possible to demonstrate the possibility of decomposing the quasi-safe optimal transport into a series of optimal transport subproblems point by point on each irreducible component. Finally, this duality is used to demonstrate a principle of martingale monotony, analogous to the famous monotonic principle of classical optimal transport. We then study the local structure of optimal transport, deduced from differential considerations. We thus obtain a characterization of this structure using tools of real algebraic geometry. We deduce the optimal martingal transport structure in the case of the power costs of the Euclidean norm, which makes it possible to solve a conjecture that dates from 2015. Finally, we compared the existingnumerical methods and proposed a new method which proves more efficient and allows to treat an intrinsic problem of the martingale constraint which is the defect of convex order. Techniques are also provided to manage digital problems in practice

Optimal trading using signals

21 pages, 5 figureIn this paper we propose a mathematical framework to address the uncertainty emergingwhen the designer of a trading algorithm uses a threshold on a signal as a control. We rely ona theorem by Benveniste and Priouret to deduce our Inventory Asymptotic Behaviour (IAB)Theorem giving the full distribution of the inventory at any point in time for a well formulatedtime continuous version of the trading algorithm.Since this is the first time a paper proposes to address the uncertainty linked to the use of athreshold on a signal for trading, we give some structural elements about the kind of signals thatare using in execution. Then we show how to control this uncertainty for a given cost function.There is no closed form solution to this control, hence we propose several approximation schemesand compare their performances.Moreover, we explain how to apply the IAB Theorem to any trading algorithm drivenby a trading speed. It is not needed to control the uncertainty due to the thresholding of asignal to exploit the IAB Theorem; it can be applied ex-post to any traditional trading algorithm

BUILDING ARBITRAGE-FREE IMPLIED VOLATILITY: SINKHORN'S ALGORITHM AND VARIANTS

We consider the classical problem of building an arbitrage-free implied volatility surface from bid-ask quotes. We design a fast numerical procedure, for which we prove the convergence, based on the Sinkhorn algorithm that has been recently used to solve efficiently (martingale) optimal transport problems