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Systemic risk measures quantify the potential risk to an individual financial constituent arising from the distress of entire financial system. As a generalization of two widely applied risk measures, Value-at-Risk and Expected Shortfall,…

Methodology · Statistics 2025-11-24 Qingzhao Zhong , Yanxi Hou

Conditional value-at-risk (CoVaR) is one of the most important measures of systemic risk. It is defined as the high quantile conditional on a related variable being extreme, widely used in the field of quantitative risk management. In this…

Methodology · Statistics 2026-02-12 Zhaowen Wang , Yutao Liu , Deyuan Li

The global financial crisis of 2007-2009 highlighted the crucial role systemic risk plays in ensuring stability of financial markets. Accurate assessment of systemic risk would enable regulators to introduce suitable policies to mitigate…

Statistics Theory · Mathematics 2022-03-03 Natalia Nolde , Chen Zhou , Menglin Zhou

Risk sensitive decision making finds important applications in current day use cases. Existing risk measures consider a single or finite collection of random variables, which do not account for the asymptotic behaviour of underlying…

Risk Management · Quantitative Finance 2024-05-24 Shivam Patel , Vivek Borkar

This paper is dedicated to the consistency of systemic risk measures with respect to stochastic dependence. It compares two alternative notions of Conditional Value-at-Risk (CoVaR) available in the current literature. These notions are both…

Risk Management · Quantitative Finance 2012-08-30 Georg Mainik , Eric Schaanning

We develop an extreme value framework for CoVaR centered on $v(q \mid p ; C)$, the copula-adjusted probability level, or equivalently, the CoVaR on the uniform (0,1) scale. We characterize the possible tail regimes of $v(q \mid p ; C)$…

Methodology · Statistics 2026-03-31 Xiaoting Li , Harry Joe

In this paper, we investigate risk measures such as value at risk (VaR) and the conditional tail expectation (CTE) of the extreme (maximum and minimum) and the aggregate (total) of two dependent risks. In finance, insurance and the other…

Risk Management · Quantitative Finance 2021-02-01 Suman Thapa , Yiqiang Q. Zhao

CoVaR (conditional value-at-risk) is a crucial measure for assessing financial systemic risk, which is defined as a conditional quantile of a random variable, conditioned on other random variables reaching specific quantiles. It enables the…

Risk Management · Quantitative Finance 2023-10-31 Weihuan Huang

Systemic risk measures play a crucial role in analyzing individual losses conditional on extreme system-wide disasters. In this paper, we provide a unified asymptotic treatment for systemic risk measures. First, we classify them into two…

Risk Management · Quantitative Finance 2026-05-26 Bingzhen Geng , Yang Liu , Yimiao Zhao

We propose nonparametric estimators for conditional value-at-risk (CVaR) and conditional expected shortfall (CES) associated with conditional distributions of a series of returns on a financial asset. The return series and the conditioning…

Methodology · Statistics 2016-12-28 Carlos Martins-Filho , Feng Yao , Maximo Torero

We propose a non-asymptotic convergence analysis of a two-step approach to learn a conditional value-at-risk (VaR) and a conditional expected shortfall (ES) using Rademacher bounds, in a non-parametric setup allowing for heavy-tails on the…

Computational Finance · Quantitative Finance 2024-09-20 D Barrera , S Crépey , E Gobet , Hoang-Dung Nguyen , B Saadeddine

The popular systemic risk measure CoVaR (conditional Value-at-Risk) and its variants are widely used in economics and finance. In this article, we propose joint dynamic forecasting models for the Value-at-Risk (VaR) and CoVaR. The CoVaR…

Econometrics · Economics 2025-01-22 Timo Dimitriadis , Yannick Hoga

In a wide variety of sequential decision making problems, it can be important to estimate the impact of rare events in order to minimize risk exposure. A popular risk measure is the conditional value-at-risk (CVaR), which is commonly…

Machine Learning · Statistics 2020-12-11 Dylan Troop , Frédéric Godin , Jia Yuan Yu

Risk measure forecast and model have been developed in order to not only provide better forecast but also preserve its (empirical) property especially coherent property. Whilst the widely used risk measure of Value-at-Risk (VaR) has shown…

Risk Management · Quantitative Finance 2020-09-08 Bony Josaphat , Khreshna Syuhada

We propose a new class of extreme-value copulas which are extreme-value limits of conditional normal models. Conditional normal models are generalizations of conditional independence models, where the dependence among observed variables is…

Methodology · Statistics 2021-02-16 Pavel Krupskii , Marc G. Genton

The Pickands estimator for the extreme value index is beneficial due to its universal consistency, location, and scale invariance, which sets it apart from other types of estimators. However, similar to many extreme value index estimators,…

Statistics Theory · Mathematics 2024-07-29 Yizhou Li , Pawel Polak

This paper shows that the CoVaR,$\Delta$-CoVaR,CoES,$\Delta$-CoES and MES systemic risk measures can be represented in terms of the univariate risk measure evaluated at a quantile determined by the copula. The result is applied to derive…

Risk Management · Quantitative Finance 2023-04-27 Aleksy Leeuwenkamp

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

In financial risk management, Value at Risk (VaR) is widely used to estimate potential portfolio losses. VaR's limitation is its inability to account for the magnitude of losses beyond a certain threshold. Expected Shortfall (ES) addresses…

Risk Management · Quantitative Finance 2024-07-10 Federico Gatta , Fabrizio Lillo , Piero Mazzarisi

Recent financial disasters have emphasised the need to accurately predict extreme financial losses and their consequences for the institutions belonging to a given financial market. The ability of econometric models to predict extreme…

Methodology · Statistics 2016-01-22 Mauro Bernardi , Leopoldo Catania
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