We study the problem of maximizing a spectral risk measure of a given output function which depends on several underlying variables, whose individual distributions are known but whose joint distribution is not. We establish and exploit an equivalence between this problem and a multi-marginal optimal transport problem. We use this reformulation to establish explicit, closed form solutions when the underlying variables are one dimensional, for a large class of output functions. For higher dimensional underlying variables, we identify conditions on the output function and marginal distributions under which solutions concentrate on graphs over the first variable and are unique
International audienceWe consider the optimal mass transportation problem in $\RR^d$ with measurably...
We consider the optimal mass transportation problem in Rd with measurably parameterized marginals u...
We study a class of optimal transport planning problems where the reference cost involves a non line...
We study the problem of maximizing a spectral risk measure of a given output function which depends ...
Motivated by applications in model-free finance and quantitative risk management, we consider Freche...
A spectral risk measure (SRM) is a weighted average of value at risk where the weighting function (a...
Relatively recently, there has been much activity on two particular generalizations of the classical...
Over the past five years, multi-marginal optimal transport, a generalization of the well k...
While many questions in robust finance can be posed in the martingale optimal transport framework or...
During recent decades, there has been a substantial development in optimal mass transport theory and...
This thesis deals with a class of multi-marginal optimal transport problems, which we call graph-str...
We study solutions to the multi-marginal Monge-Kantorovich problem which are concentrated on several...
The robust approach has been a prominent area of research within modern mathematical finance since t...
Abstract. We introduce and study a multi-marginal optimal partial transport problem. Under a natural...
A fundamental problem in risk management is the robust aggregation of different sources of risk in a...
International audienceWe consider the optimal mass transportation problem in $\RR^d$ with measurably...
We consider the optimal mass transportation problem in Rd with measurably parameterized marginals u...
We study a class of optimal transport planning problems where the reference cost involves a non line...
We study the problem of maximizing a spectral risk measure of a given output function which depends ...
Motivated by applications in model-free finance and quantitative risk management, we consider Freche...
A spectral risk measure (SRM) is a weighted average of value at risk where the weighting function (a...
Relatively recently, there has been much activity on two particular generalizations of the classical...
Over the past five years, multi-marginal optimal transport, a generalization of the well k...
While many questions in robust finance can be posed in the martingale optimal transport framework or...
During recent decades, there has been a substantial development in optimal mass transport theory and...
This thesis deals with a class of multi-marginal optimal transport problems, which we call graph-str...
We study solutions to the multi-marginal Monge-Kantorovich problem which are concentrated on several...
The robust approach has been a prominent area of research within modern mathematical finance since t...
Abstract. We introduce and study a multi-marginal optimal partial transport problem. Under a natural...
A fundamental problem in risk management is the robust aggregation of different sources of risk in a...
International audienceWe consider the optimal mass transportation problem in $\RR^d$ with measurably...
We consider the optimal mass transportation problem in Rd with measurably parameterized marginals u...
We study a class of optimal transport planning problems where the reference cost involves a non line...