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We consider the optimal risk transfer from an insurance company to a reinsurer. The problem formulation considered in this paper is closely connected to the optimal portfolio problem in finance, with some crucial distinctions. In…

Optimization and Control · Mathematics 2023-06-23 Benjamin Avanzi , Hayden Lau , Mogens Steffensen

Random shifting typically appears in credibility models whereas random scaling is often encountered in stochastic models for claim sizes reflecting the time-value property of money. In this article we discuss some aspects of random shifting…

Methodology · Statistics 2014-10-08 Enkelejd Hashorva , Lanpeng Ji

We consider the problem of finding Pareto-optimal allocations of risk among finitely many agents. The associated individual risk measures are law invariant, but with respect to agent-dependent and potentially heterogeneous reference…

Risk Management · Quantitative Finance 2022-05-05 Felix-Benedikt Liebrich

We present an exact algorithm for mean-risk optimization subject to a budget constraint, where decision variables may be continuous or integer. The risk is measured by the covariance matrix and weighted by an arbitrary monotone function,…

Optimization and Control · Mathematics 2017-05-08 Christoph Buchheim , Marianna De Santis , Francesco Rinaldi , Long Trieu

We provide analytical results for a static portfolio optimization problem with two coherent risk measures. The use of two risk measures is motivated by joint decision-making for portfolio selection where the risk perception of the portfolio…

Portfolio Management · Quantitative Finance 2021-01-19 Tahsin Deniz Aktürk , Çağın Ararat

This paper investigates risk measures derived from the expected maximum deficit in a continuous-time framework and develops optimal reserve allocation strategies across multiple lines of business. We formalize the expected maximum deficit…

Risk Management · Quantitative Finance 2026-05-19 Claude Lefevre , Pierre Zuyderhoff

Under appropriate integrability conditions the risk measure of the sample measures for a law invariant risk measure converge almost surely to the risk measure of the sampled random variable. The results follow from general convergence…

Probability · Mathematics 2021-09-23 Freddy Delbaen

Let $\rho$ be a general law--invariant convex risk measure, for instance the average value at risk, and let $X$ be a financial loss, that is, a real random variable. In practice, either the true distribution $\mu$ of $X$ is unknown, or the…

Risk Management · Quantitative Finance 2022-11-02 Daniel Bartl , Ludovic Tangpi

It is well known that a random vector with given marginal distributions is comonotonic if and only if it has the largest sum with respect to the convex order [ Kaas, Dhaene, Vyncke, Goovaerts, Denuit (2002), A simple geometric proof that…

Risk Management · Quantitative Finance 2016-05-10 Chuancun Yin , Dan Zhu

We study invariant sets and measures generated by iterated function systems defined on countable discrete spaces that are uniform grids of a finite dimension. The discrete spaces of this type can be considered as models of spaces in which…

Dynamical Systems · Mathematics 2024-10-22 Tomasz Martyn

Focusing on gains & losses relative to a risk-free benchmark instead of terminal wealth, we consider an asset allocation problem to maximize time-consistently a mean-risk reward function with a general risk measure which is i)…

Mathematical Finance · Quantitative Finance 2026-02-18 Felix Fießinger , Mitja Stadje

The basic principle of any version of insurance is the paradigm that exchanging risk by sharing it in a pool is beneficial for the participants. In case of independent risks with a finite mean this is the case for risk averse decision…

Risk Management · Quantitative Finance 2025-10-08 Alfred Müller

We propose an computational framework for real-time risk assessment and prioritizing for random outcomes without prior information on probability distributions. The basic model is built based on satisficing measure (SM) which yields a…

Optimization and Control · Mathematics 2018-07-03 Wenjie Huang

In this work the problem of optimal harvesting policy selection for natural resources management under model uncertainty is investigated. Under the framework of the neoclassical growth model dynamics, the associated optimal control problem…

Optimization and Control · Mathematics 2023-10-24 Georgios I. Papayiannis

Split conformal prediction has recently sparked great interest due to its ability to provide formally guaranteed uncertainty sets or intervals for predictions made by black-box neural models, ensuring a predefined probability of containing…

Machine Learning · Computer Science 2024-01-29 António Farinhas , Chrysoula Zerva , Dennis Ulmer , André F. T. Martins

A basic principle in the design of observational studies is to approximate the randomized experiment that would have been conducted under controlled circumstances. Now, linear regression models are commonly used to analyze observational…

Methodology · Statistics 2022-07-08 Ambarish Chattopadhyay , Jose R. Zubizarreta

Methods for measuring convexity defects of compacts in R^n abound. However, none of the those measures seems to take into account continuity. Continuity in convexity measure is essential for optimization, stability analysis, global…

Geometric Topology · Mathematics 2024-12-24 Abel Douzal , Ferdinand Jacobé de Naurois

One of the crucial problems in mathematical finance is to mitigate the risk of a financial position by setting up hedging positions of eligible financial securities. This leads to focusing on set-valued maps associating to any financial…

Mathematical Finance · Quantitative Finance 2017-11-02 Michel Baes , Cosimo Munari

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

Although there is growing interest in measuring integrated information in computational and cognitive systems, current methods for doing so in practice are computationally unfeasible. Existing and novel integration measures are investigated…

Neurons and Cognition · Quantitative Biology 2017-02-08 Max Tegmark