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Related papers: On Multivariate Extensions of Value-at-Risk

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Value-at-Risk (VaR) is one of the main regulatory tools used for risk management purposes. However, it is difficult to compute optimal VaR portfolios; that is, an optimal risk-reward portfolio allocation using VaR as the risk measure. This…

Portfolio Management · Quantitative Finance 2021-07-16 Onur Babat , Juan C. Vera , Luis F. Zuluaga

This paper presents analytical solutions to the problem of how to calculate sensible VaR (Value-at-Risk) and ES (Expected Shortfall) contributions in the CreditRisk+ methodology. Via the ES contributions, ES itself can be exactly computed…

Condensed Matter · Physics 2011-08-09 Alexandre Kurth , Dirk Tasche

Determining contributions by sub-portfolios or single exposures to portfolio-wide economic capital for credit risk is an important risk measurement task. Often economic capital is measured as Value-at-Risk (VaR) of the portfolio loss…

Statistics Theory · Mathematics 2009-06-18 Dirk Tasche

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

Recent financial disasters emphasised the need to investigate the consequence associated with the tail co-movements among institutions; episodes of contagion are frequently observed and increase the probability of large losses affecting…

Methodology · Statistics 2013-11-05 Mauro Bernardi , Ghislaine Gayraud , Lea Petrella

The distribution functions of the matricvariate beta type I and II distributions are studied under real normed division algebras. The unified approach for real, complex, quaternions and octonions, also considers general properties and…

Statistics Theory · Mathematics 2024-09-27 José A. Díaz-García , Francisco J. Caro-Lopera

Multivariate Analysis (MVA) comprises a family of well-known methods for feature extraction that exploit correlations among input variables of the data representation. One important property that is enjoyed by most such methods is…

Machine Learning · Statistics 2016-09-21 Sergio Muñoz-Romero , Vanessa Gómez-Verdejo , Jerónimo Arenas-García

The two popular systemic risk measures CoVaR (Conditional Value-at-Risk) and CoES (Conditional Expected Shortfall) have recently been receiving growing attention on applications in economics and finance. In this paper, we study the…

Methodology · Statistics 2026-01-21 Qingzhao Zhong

This paper proposes a new integrated variance estimator based on order statistics within the framework of jump-diffusion models. Its ability to disentangle the integrated variance from the total process quadratic variation is confirmed by…

Risk Management · Quantitative Finance 2018-03-23 Luca Spadafora , Francesca Sivero , Nicola Picchiotti

In the multivariate setting, estimates of extremal risk measures are important in many contexts, such as environmental planning and structural engineering. In this paper, we propose new estimation methods for extremal bivariate return…

Methodology · Statistics 2022-10-11 C. J. R. Murphy-Barltrop , J. L. Wadsworth , E. F. Eastoe

Based on law of large numbers and central limit theorem under nonlinear expectation, we introduce a new method of using G-normal distribution to measure financial risks. Applying max-mean estimators and small windows method, we establish…

Mathematical Finance · Quantitative Finance 2021-07-28 Shige Peng , Shuzhen Yang

We study risk-sensitive planning under partial observability using the dynamic risk measure Iterated Conditional Value-at-Risk (ICVaR). A policy evaluation algorithm for ICVaR is developed with finite-time performance guarantees that do not…

Artificial Intelligence · Computer Science 2026-01-29 Yaacov Pariente , Vadim Indelman

We introduce a class of dependence structures, that we call the Multiple Risk Factor (MRF) dependence structures. On the one hand, the new constructions extend the popular CreditRisk+ approach, and as such they formally describe default…

Risk Management · Quantitative Finance 2016-07-19 Jianxi Su , Edward Furman

Vector autoregressive (VAR) models are widely used in practical studies, e.g., forecasting, modelling policy transmission mechanism, and measuring connection of economic agents. To better capture the dynamics, this paper introduces a new…

Econometrics · Economics 2021-11-02 Yayi Yan , Jiti Gao , Bin Peng

Given measurements from sensors and a set of standard forces, an optimization based approach to identify weakness in structures is introduced. The key novelty lies in letting the load and measurements to be random variables. Subsequently…

Optimization and Control · Mathematics 2023-11-22 Facundo N. Airaudo , Harbir Antil , Rainald Löhner , Umarkhon Rakhimov

This survey gives an introduction to monetary measures of risk as monotone and cash additive functions on spaces of univariate random variables. Primal and dual representation results as well as several examples are discussed. Principal…

Risk Management · Quantitative Finance 2018-12-12 Andreas H Hamel

Conditional Value-at-Risk (CoVaR) quantifies systemic financial risk by measuring the loss quantile of one asset, conditional on another asset experiencing distress. We develop a Transformer-based methodology that integrates financial news…

Econometrics · Economics 2026-02-16 Junyu Chen , Tom Boot , Lingwei Kong , Weining Wang

A new multivariate distribution possessing arbitrarily parametrized and positively dependent univariate Pareto margins is introduced. Unlike the probability law of Asimit et al. (2010) [Asimit, V., Furman, E. and Vernic, R. (2010) On a…

Risk Management · Quantitative Finance 2016-07-19 Jianxi Su , Edward Furman

We present a general framework for measuring the liquidity risk. The theoretical framework defines a class of risk measures that incorporate the liquidity risk into the standard risk measures. We consider a one-period risk measurement…

Mathematical Finance · Quantitative Finance 2016-10-31 Erindi Allaj

This paper focuses on vector-valued composite functionals, which may be nonlinear in probability. Our primary goal is to establish central limit theorems for these functionals when mixed estimators are employed. Our study is relevant to the…

Statistics Theory · Mathematics 2025-01-09 Huihui Chen , Darinka Dentcheva , Yang Lin , Gregory J. Stock