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We provide a constructive way of defining new elicitable risk measures that are characterised by a multiplicative scoring function. We show that depending on the choice of the scoring function's components, the resulting risk measure…

Mathematical Finance · Quantitative Finance 2025-03-06 Akif Ince , Marlon Moresco , Ilaria Peri , Silvana M. Pesenti

In [16], a new family of vector-valued risk measures called multivariate expectiles is introduced. In this paper, we focus on the asymptotic behavior of these measures in a multivariate regular variations context. For models with equivalent…

Risk Management · Quantitative Finance 2018-01-22 Véronique Maume-Deschamps , Didier Rullière , Khalil Said

A generalization of expectiles for d-dimensional multivariate distribution functions is introduced. The resulting geometric expectiles are unique solutions to a convex risk minimization problem and are given by d-dimensional vectors. They…

Risk Management · Quantitative Finance 2018-01-19 Klaus Herrmann , Marius Hofert , Melina Mailhot

In this paper, we introduce two alternative extensions of the classical univariate Value-at-Risk (VaR) in a multivariate setting. The two proposed multivariate VaR are vector-valued measures with the same dimension as the underlying risk…

Risk Management · Quantitative Finance 2013-04-05 Areski Cousin , Elena Di Bernadino

We present a framework for constructing multivariate risk measures that is inspired from univariate Optimized Certainty Equivalent (OCE) risk measures. We show that this new class of risk measures verifies the desirable properties such as…

Optimization and Control · Mathematics 2022-12-07 Sarah Kaakai , Anis Matoussi , Achraf Tamtalini

The risk of a financial position is usually summarized by a risk measure. As this risk measure has to be estimated from historical data, it is important to be able to verify and compare competing estimation procedures. In statistical…

Risk Management · Quantitative Finance 2014-04-01 Johanna F. Ziegel

Expected Shortfall (ES) has been widely accepted as a risk measure that is conceptually superior to Value-at-Risk (VaR). At the same time, however, it has been criticised for issues relating to backtesting. In particular, ES has been found…

Risk Management · Quantitative Finance 2015-11-20 Susanne Emmer , Marie Kratz , Dirk Tasche

We discuss equivalent axiomatic characterizations of distortion risk measures, and give a novel and concise proof of the characterization of elicitable distortion risk measures. Elicitability has recently been discussed as a desirable…

Risk Management · Quantitative Finance 2014-05-27 Ruodu Wang , Johanna F. Ziegel

In this paper, we modify the Bayes risk for the expectile, the so-called variantile risk measure, to better capture extreme risks. The modified risk measure is called the adjusted standard-deviatile. First, we derive the asymptotic…

Statistics Theory · Mathematics 2024-11-12 Haoyu Chen , Tiantian Mao , Fan Yang

In this paper, we introduce a new class of set-valued risk measures, named set-valued star-shaped risk measures. Motivated by the results of scalar monetary and star-shaped risk measures, this paper investigates the representation theorems…

Risk Management · Quantitative Finance 2025-02-24 Bingchu Nie , Dejian Tian , Long Jiang

The notion of expectiles, originally introduced in the context of testing for homoscedasticity and conditional symmetry of the error distribution in linear regression, induces a law-invariant, coherent and elicitable risk measure that has…

Methodology · Statistics 2020-07-20 Simone A. Padoan , Gilles Stupfler

A new family of multivariate distributions, which shall be termed multivector variate distributions, based in the family of the multivariate contoured elliptically distribution is proposed. Several particular cases of multivector variate…

Statistics Theory · Mathematics 2018-06-26 Jose. A. Diaz-Garcia , Francisco J. Caro-Lopera , Fredy O. Perez Ramirez

In economics, insurance and finance, value at risk (VaR) is a widely used measure of the risk of loss on a specific portfolio of financial assets. For a given portfolio, time horizon, and probability $\alpha$, the $100\alpha\%$ VaR is…

Risk Management · Quantitative Finance 2018-03-15 Raúl Torres , Rosa E. Lillo , Henry Laniado

The purpose of this paper is to describe and extend the use of the newly-introduced measure, residual estimation risk. Following the seminal work of Bignozzi and Tsanakas, the quantification of residual estimation risk is proposed in a…

Risk Management · Quantitative Finance 2026-03-19 D. J. Manuge

In this study, we propose a new definition of multivariate conditional value-at-risk (MCVaR) as a set of vectors for discrete probability spaces. We explore the properties of the vector-valued MCVaR (VMCVaR) and show the advantages of…

Optimization and Control · Mathematics 2020-06-02 Merve Merakli , Simge Kucukyavuz

The aim of this paper is to introduce a risk measure that extends the Gini-type measures of risk and variability, the Extended Gini Shortfall, by taking risk aversion into consideration. Our risk measure is coherent and catches variability,…

Risk Management · Quantitative Finance 2018-03-21 Mohammed Berkhouch , Ghizlane Lakhnati , Marcelo Brutti Righi

Expectile, as the minimizer of an asymmetric quadratic loss function, is a coherent risk measure and is helpful to use more information about the distribution of the considered risk. In this paper, we propose a new risk measure by replacing…

Methodology · Statistics 2023-10-31 Qian Xiong , Zuoxiang Peng

We propose and study a novel collection of signed measures, which will be apply called Taylor measures. Stochastic versions of the new measures are also defined and studied. We illustrate, through examples, how the deterministic and…

Probability · Mathematics 2025-08-15 Athanasios Christou Micheas

Randomness in financial markets requires modern and robust multivariate models of risk measures. This paper proposes a new approach for modeling multivariate risk measures under Wasserstein barycenters of probability measures supported on…

Applications · Statistics 2020-08-14 M. Andrea Arias-Serna , Jean-Michel Loubes , Francisco J. Caro-Lopera

Several authors have recently developed risk-sensitive policy gradient methods that augment the standard expected cost minimization problem with a measure of variability in cost. These studies have focused on specific risk-measures, such as…

Artificial Intelligence · Computer Science 2015-06-09 Aviv Tamar , Yinlam Chow , Mohammad Ghavamzadeh , Shie Mannor
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