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Related papers: Tail Risk Analysis for Financial Time Series

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Expectiles define the only law-invariant, coherent and elicitable risk measure apart from the expectation. The popularity of expectile-based risk measures is steadily growing and their properties have been studied for independent data, but…

Methodology · Statistics 2021-10-13 Anthony C. Davison , Simone A. Padoan , Gilles Stupfler

The quantitative analysis of financial time series often reveals two distinct features that standard Gaussian frameworks fail to capture: heavy-tailed marginal distributions and the phenomenon of extreme co-movements.While extreme value…

Statistics Theory · Mathematics 2026-05-14 Debanjana Datta , Diganta Mukherjee

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

We introduce a new stochastic order for the tail dependence between random variables. We then study different measures of tail dependence which are monotone in the proposed order, thereby extending various known tail dependence coefficients…

Risk Management · Quantitative Finance 2022-08-23 Karl Friedrich Siburg , Christopher Strothmann , Gregor Weiß

The tail index, indicating the degree of fatness of the tail distribution, is an important component of extreme value theory since it dominates the asymptotic distribution of extreme values such as the sample maximum. In this paper, we…

Statistics Theory · Mathematics 2009-06-12 Moosup Kim , Sangyeol Lee

Tail dependence plays an essential role in the characterization of joint extreme events in multivariate data. However, most standard tail dependence parameters assume continuous margins. This note presents a form of tail dependence suitable…

Statistics Theory · Mathematics 2025-02-04 Victory Idowu

Factor models have large potencial in the modeling of several natural and human phenomena. In this paper we consider a multivariate time series $\mb{Y}_n$, ${n\geq 1}$, rescaled through random factors $\mb{T}_n$, ${n\geq 1}$, extending some…

Probability · Mathematics 2013-06-18 Helena Ferreira , Marta Ferreira

To draw inference on serial extremal dependence within heavy-tailed Markov chains, Drees, Segers and Warcho{\l} [Extremes (2015) 18, 369--402] proposed nonparametric estimators of the spectral tail process. The methodology can be extended…

Methodology · Statistics 2018-01-30 R. A. Davis , H. Drees , J. Segers , M. Warchoł

Given a finite collection of stochastic alternatives, we study the problem of sequentially allocating a fixed sampling budget to identify the optimal alternative with a high probability, where the optimal alternative is defined as the one…

Methodology · Statistics 2025-03-11 Dohyun Ahn , Taeho Kim

This paper introduces a novel measure to quantify the directional dependence of extreme events between two variables. The proposed approach is designed to capture asymmetric tail dependence by studying conditional tail expectations of…

Methodology · Statistics 2026-04-06 Matthieu Garcin , Maxime L. D. Nicolas

Financial time series exhibit multiscale behavior, with interaction between multiple processes operating on different timescales. This paper introduces a method for separating these processes using variance and tail stationarity criteria,…

Portfolio Management · Quantitative Finance 2026-01-19 Jan Rosenzweig

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

This thesis evaluates most of the extreme mixture models and methods that have appended in the literature and implements them in the context of finance and insurance. The paper also reviews and studies extreme value theory, time series,…

General Economics · Economics 2024-07-09 Yujuan Qiu

Modelling multivariate tail dependence is one of the key challenges in extreme-value theory. Multivariate extremes are usually characterized using parametric models, some of which have simpler submodels at the boundary of their parameter…

Methodology · Statistics 2018-12-17 Anna Kiriliouk

On the occasion of Laurens de Haan's 70th birthday, we discuss two aspects of the statistical inference on the extreme value behavior of time series with a particular emphasis on his important contributions. First, the performance of a…

Statistics Theory · Mathematics 2007-11-01 Holger Drees

In risk theory, financial asset returns often follow heavy-tailed distributions. Investors and risk managers used to compare risk measures as the value at risk or tail value at risk in order over the whole confidence levels to avoid the…

Statistics Theory · Mathematics 2024-12-12 Alfonso J. Bello , Julio Mulero , Miguel A. Sordo , Alfonso Suárez-Llorens

In risk management, tail risks are of crucial importance. The assessment of risks should be carried out in accordance with the regulatory authority's requirement at high quantiles. In general, the underlying distribution function is…

Risk Management · Quantitative Finance 2020-07-15 Ingo Hoffmann , Christoph J. Börner

This paper investigates how two important sources of risk -- market tail risk and extreme market volatility risk -- are priced into the cross-section of asset returns across various investment horizons. To identify such risks, we propose a…

Pricing of Securities · Quantitative Finance 2021-12-13 Jozef Baruník , Matěj Nevrla

In this paper, we discuss the application of extreme value theory in the context of stationary $\beta$-mixing sequences that belong to the Fr\'echet domain of attraction. In particular, we propose a methodology to construct bias-corrected…

Statistics Theory · Mathematics 2017-08-24 Valérie Chavez-Demoulin , Armelle Guillou

We develop an efficient simulation algorithm for computing the tail probabilities of the infinite series $S = \sum_{n \geq 1} a_n X_n$ when random variables $X_n$ are heavy-tailed. As $S$ is the sum of infinitely many random variables, any…

Probability · Mathematics 2016-09-08 Henrik Hult , Sandeep Juneja , Karthyek Murthy