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It is well known that Expected Shortfall (also called Average Value-at-Risk) is a convex risk measure, i. e. Expected Shortfall of a convex linear combination of arbitrary risk positions is not greater than a convex linear combination with…

Risk Management · Quantitative Finance 2019-10-03 Mikhail Tselishchev

In this paper, we propose a reduced-bias estimator of the EVI for Pareto-type tails (heavy-tailed) distributions. This is derived using the weighted least squares method. It is shown that the estimator is unbiased, consistent and…

Methodology · Statistics 2022-04-12 E. Ocran , R. Minkah , K. Doku-Amponsah

Conditional value-at-risk (CVaR) and value-at-risk (VaR) are popular tail-risk measures in finance and insurance industries as well as in highly reliable, safety-critical uncertain environments where often the underlying probability…

Machine Learning · Computer Science 2021-06-23 Shubhada Agrawal , Wouter M. Koolen , Sandeep Juneja

One of the main goal of extreme value analysis is to estimate the probability of rare events given a sample from an unknown distribution. The upper tail behavior of this distribution is described by the extreme value index. We present a new…

Probability · Mathematics 2007-05-23 Laurent Gardes , Stephane Girard

Inference over tails is usually performed by fitting an appropriate limiting distribution over observations that exceed a fixed threshold. However, the choice of such threshold is critical and can affect the inferential results. Extreme…

Statistical Finance · Quantitative Finance 2019-02-26 Chiara Lattanzi , Manuele Leonelli

We consider heavy-tailed distributions and compare the well-known estimators of the tail index, based on extreme value theory with a comparatively recent estimator based on a different idea.

Probability · Mathematics 2016-08-14 Vygantas Paulauskas , Marijus Vaičiulis

We study the optimal trade-off between expectation and tail risk for regret distribution in the stochastic multi-armed bandit model. We fully characterize the interplay among three desired properties for policy design: worst-case…

Machine Learning · Statistics 2025-10-27 David Simchi-Levi , Zeyu Zheng , Feng Zhu

This study introduces a new analytical framework for quantifying multivariate risk measures. Using the Wishart process, which is a stochastic process with values in the space of positive definite matrices, we derive several conditional tail…

Risk Management · Quantitative Finance 2026-02-09 Jose Da Fonseca , Patrick Wong

Recently some papers, such as Aban, Meerschaert and Panorska (2006), Nuyts (2010) and Clark (2013), have drawn attention to possible truncation in Pareto tail modelling. Sometimes natural upper bounds exist that truncate the probability…

Statistics Theory · Mathematics 2015-05-21 Jan Beirlant , Isabel Fraga Alves , Ivette Gomes

In structural credit risk models, default events and the ensuing losses are both derived from the asset values at maturity. Hence it is of utmost importance to choose a distribution for these asset values which is in accordance with…

Risk Management · Quantitative Finance 2016-01-13 Thilo A. Schmitt , Rudi Schäfer , Thomas Guhr

In this paper we are concerned with the analysis of heavy-tailed data when a portion of the extreme values is unavailable. This research was motivated by an analysis of the degree distributions in a large social network. The degree…

Statistics Theory · Mathematics 2018-12-20 Jingjing Zou , Richard A. Davis , Gennady Samorodnitsky

Likelihood-based procedures are a common way to estimate tail dependence parameters. They are not applicable, however, in non-differentiable models such as those arising from recent max-linear structural equation models. Moreover, they can…

Methodology · Statistics 2016-01-20 John H. J. Einmahl , Anna Kiriliouk , Johan Segers

We review recent progress in modeling credit risk for correlated assets. We start from the Merton model which default events and losses are derived from the asset values at maturity. To estimate the time development of the asset values, the…

Risk Management · Quantitative Finance 2018-03-02 Andreas Mühlbacher , Thomas Guhr

We introduce a new type of estimator for the spectral tail process of a regularly varying time series. The approach is based on a characterizing invariance property of the spectral tail process, which is incorporated into the new estimator…

Statistics Theory · Mathematics 2021-03-16 Holger Drees , Anja Janßen , Sebastian Neblung

As the increasing application of AI in finance, this paper will leverage AI algorithms to examine tail risk and develop a model to alter tail risk to promote the stability of US financial markets, and enhance the resilience of the US…

Risk Management · Quantitative Finance 2025-08-08 Zong Ke , Yuchen Yin

By introducing a weight function into the density power divergence, we develop a new class of robust and smooth estimators for the tail index of Pareto-type distributions, offering improved efficiency in the presence of outliers. These…

Statistics Theory · Mathematics 2025-07-25 Saida Mancer , Abdelhakim Necir , Djamel Meraghni

Tail dependence refers to clustering of extreme events. In the context of financial risk management, the clustering of high-severity risks has a devastating effect on the well-being of firms and is thus of pivotal importance in risk…

Applications · Statistics 2016-07-19 Edward Furman , Alexey Kuznetsov , Jianxi Su , Ricardas Zitikis

Risk contagion concerns any entity dealing with large scale risks. Suppose (X,Y) denotes a risk vector pertaining to two components in some system. A relevant measurement of risk contagion would be to quantify the amount of influence of…

Statistics Theory · Mathematics 2017-04-26 Bikramjit Das , Vicky Fasen

We consider a family of multivariate distributions with heavy-tailed margins and the type I elliptical dependence structure. This class of risks is common in finance, insurance, environmental and biostatistic applications. We obtain the…

Statistics Theory · Mathematics 2024-05-01 Kai Wang , Chengxiu Ling

The relationship between a response variable and its covariates can vary significantly, especially in scenarios where covariates take on extremely high or low values. This paper introduces a max-linear tail regression model specifically…

Methodology · Statistics 2025-02-24 Liujun Chen , Deyuan Li , Zhengjun Zhang
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