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Extreme-value copulas: A note on comparing models for tail-risk events

Aurora Gatto, Selene Perazzini, F. Marta L. Di Lascio   +2 more
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Operator-Valued QDS Risk Measures and Tail-Risk Forecasting with Coherence-Based Regime Diagnostics

Zeraoulia Rafik
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Asymptotic subadditivity/superadditivity of Value‐at‐Risk under tail dependence

Mathematical Finance, 2023
AbstractThis paper presents a new method for discussing the asymptotic subadditivity/superadditivity of Value‐at‐Risk (VaR) for multiple risks. We consider the asymptotic subadditivity and superadditivity properties of VaR for multiple risks whose copula admits a stable tail dependence function (STDF).
Wenhao Zhu, Lujun Li, Jingping Yang, Jiehua Xie, Liulei Sun   +4 more
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Conditional tail behaviour and Value at Risk

Quantitative Finance, 2007
In this paper we study the tail behaviour of eight major market indexes stratifying data according to the violation of a high threshold on the previous day. The distributional differences found can be exploited to improve VaR calculations in several settings, giving rise to what we call ‘MCVaR’.
Bellini F., FIGA' TALAMANCA, GIANNA
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Value-at-risk with heavy-tailed risk factors

Proceedings of the IEEE/IAFE/INFORMS 2000 Conference on Computational Intelligence for Financial Engineering (CIFEr) (Cat. No.00TH8520), 2002
This paper develops methods for computationally efficient calculation of value-at-risk (VAR) in the presence of heavy-tailed risk factors. The methods model market risk factors through a multivariate t-distribution, which has both heavy tails and empirical support.
Paul Glasserman, Philip Heidelberger, Perwez Shahabuddin   +2 more
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Tail value-at-risk in uncertain random environment

Soft Computing, 2018
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Yuhan Liu, Dan A. Ralescu, Chen Xiao, Waichon Lio   +3 more
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MULTIVARIATE GEOMETRIC TAIL- AND RANGE-VALUE-AT-RISK

ASTIN Bulletin, 2019
AbstractA generalization of range-value-at-risk (RVaR) and tail-value-at-risk (TVaR) for d-dimensional distribution functions is introduced. Properties of these new risk measures are studied and illustrated. We provide special cases, applications and a comparison with traditional univariate and multivariate versions of the TVaR and RVaR.
Klaus Herrmann, Marius Hofert, Mélina Mailhot   +2 more
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Vector-Valued Tail Value-at-Risk and Capital Allocation

Methodology and Computing in Applied Probability, 2015
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Cossette, Hélène, Mailhot, Mélina, Marceau, Étienne, Mesfioui, Mhamed   +3 more
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Portfolio Value‐at‐Risk with Heavy‐Tailed Risk Factors

Mathematical Finance, 2002
This paper develops efficient methods for computing portfolio value‐at‐risk (VAR) when the underlying risk factors have a heavy‐tailed distribution. In modeling heavy tails, we focus on multivariate t distributions and some extensions thereof. We develop two methods for VAR calculation that exploit a quadratic approximation to the portfolio loss, such ...
Glasserman, Paul, Heidelberger, Philip, Shahabuddin, Perwez   +2 more
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Efficient Simulation of Value at Risk with Heavy-Tailed Risk Factors

Operations Research, 2011
Simulation of small probabilities has important applications in many disciplines. The probabilities considered in value-at-risk (VaR) are moderately small. However, the variance reduction techniques developed in the literature for VaR computation are based on large-deviations methods, which are good for very small probabilities.
Cheng-Der Fuh, Inchi Hu, Ya-Hui Hsu, Ren-Her Wang   +3 more
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