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We propose a multivariate extension of a well-known characterization by S. Kusuoka of regular and coherent risk measures as maximal correlation functionals. This involves an extension of the notion of comonotonicity to random vectors…

Theoretical Economics · Economics 2021-02-09 Ivar Ekeland , Alfred Galichon , Marc Henry

We introduce the concept of partial law invariance, generalizing the concepts of law invariance and probabilistic sophistication widely used in decision theory, as well as statistical and financial applications. This new concept is…

Risk Management · Quantitative Finance 2025-06-24 Yi Shen , Zachary Van Oosten , Ruodu Wang

This paper addresses law invariant coherent risk measures and their Kusuoka representations. By elaborating the existence of a minimal representation we show that every Kusuoka representation can be reduced to its minimal representation.…

Statistics Theory · Mathematics 2013-02-28 Alois Pichler , Alexander Shapiro

In this paper, we study convex risk measures with weak optimal transport penalties. In a first step, we show that these risk measures allow for an explicit representation via a nonlinear transform of the loss function. In a second step, we…

Mathematical Finance · Quantitative Finance 2023-12-12 Michael Kupper , Max Nendel , Alessandro Sgarabottolo

A classical result in risk measure theory states that every coherent risk measure has a dual representation as the supremum of certain expected value over a risk envelope. We study this topic in more detail. The related issues include: 1.…

Optimization and Control · Mathematics 2018-02-28 Marcus Ang , Jie Sun , Qiang Yao

Recently, literature on dynamic coherent risk measures has broadened the choices for risk-sensitive performance evaluation. A running example includes Cumulative prospect theory and Conditional variance at risk. Most of them can be can be…

Optimization and Control · Mathematics 2020-12-14 Weixin Wang

We study a class of dynamically consistent risk measures that robustify a time-homogeneous Markovian reference model by allowing for distributional uncertainty in its transition laws. We start from one-step convex risk evaluations in which…

Mathematical Finance · Quantitative Finance 2026-05-22 Sven Fuhrmann , Michael Kupper , Max Nendel

We develop a general theory of risk measures that determines the optimal amount of capital to raise and invest in a portfolio of reference traded securities in order to meet a pre-specified regulatory requirement. The distinguishing feature…

Mathematical Finance · Quantitative Finance 2021-11-17 Maria Arduca , Cosimo Munari

We study a static portfolio optimization problem with two risk measures: a principle risk measure in the objective function and a secondary risk measure whose value is controlled in the constraints. This problem is of interest when it is…

Portfolio Management · Quantitative Finance 2020-12-14 Çağın Ararat

We characterize when a convex risk measure associated to a law-invariant acceptance set in $L^\infty$ can be extended to $L^p$, $1\leq p<\infty$, preserving finiteness and continuity. This problem is strongly connected to the statistical…

Risk Management · Quantitative Finance 2014-01-15 Pablo Koch-Medina , Cosimo Munari

By means of the techniques of Boolean valued analysis, we provide a transfer principle between duality theory of classical convex risk measures and duality theory of conditional risk measures. Namely, a conditional risk measure can be…

Functional Analysis · Mathematics 2019-10-09 José Miguel Zapata

We study combinations of risk measures under no restrictive assumption on the set of alternatives. We develop and discuss results regarding the preservation of properties and acceptance sets for the combinations of risk measures. One of the…

Mathematical Finance · Quantitative Finance 2023-05-09 Marcelo Brutti Righi

In this note, we extend the regularity theory for monotone measure-preserving maps, also known as optimal transports for the quadratic cost optimal transport problem, to the case when the support of the target measure is an arbitrary convex…

Analysis of PDEs · Mathematics 2023-05-17 Alessio Figalli , Yash Jhaveri

In this paper we study optimal stopping problems with respect to distorted expectations of the form \begin{eqnarray*} \mathcal{E}(X)=\int_{-\infty}^{\infty} x\,dG(F_X(x)), \end{eqnarray*} where $F_X$ is the distribution function of $X$ and…

Optimization and Control · Mathematics 2015-06-16 Denis Belomestny , Volker Kraetschmer

In this work we consider optimal stopping problems with conditional convex risk measures called optimised certainty equivalents. Without assuming any kind of time-consistency for the underlying family of risk measures, we derive a novel…

Mathematical Finance · Quantitative Finance 2014-12-16 Denis Belomestny , Volker Kraetschmer

The inf-convolution of risk measures is directly related to risk sharing and general equilibrium, and it has attracted considerable attention in mathematical finance and insurance problems. However, the theory is restricted to finite sets…

Risk Management · Quantitative Finance 2022-03-22 Marcelo Brutti Righi , Marlon Ruoso Moresco

In this paper, we study general monetary risk measures (without any convexity or weak convexity). A monetary (respectively, positively homogeneous) risk measure can be characterized as the lower envelope of a family of convex (respectively,…

Mathematical Finance · Quantitative Finance 2020-12-15 Guangyan Jia , Jianming Xia , Rongjie Zhao

We expose a theoretical hedging optimization framework with variational preferences under convex risk measures. We explore a general dual representation for the composition between risk measures and utilities. We study the properties of the…

Mathematical Finance · Quantitative Finance 2024-10-11 Marcelo Righi

The classical problem of optimal transportation can be formulated as a linear optimization problem on a convex domain: among all joint measures with fixed marginals find the optimal one, where optimality is measured against a cost function.…

Optimization and Control · Mathematics 2012-11-29 Jonathan Korman , Robert J. McCann

This paper generalizes results concerning strong convexity of two-stage mean-risk models with linear recourse to distortion risk measures. Introducing the concept of (restricted) partial strong convexity, we conduct an in-depth analysis of…

Optimization and Control · Mathematics 2018-12-20 Matthias Claus , Kai Spürkel
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