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20112024
most citedOn a minimum distance procedure for threshold selection in tail analysis

23 citations · 48 across the 9 of their papers we have counts for

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math.PR2023

Multivariate Regular Variation of Preferential Attachment Models

Anja Janßen, Max Ziegenbalg

We use the framework of multivariate regular variation to analyse the extremal behaviour of preferential attachment models. To this end, we follow a directed linear preferential at…

math.PR2022

Invariance properties of limiting point processes and applications to clusters of extremes

Anja Janßen, Johan Segers

Motivated by examples from extreme value theory we introduce the general notion of a cluster process as a limiting point process of returns of a certain event in a time series. We…

math.PR2017

Spectral tail processes and max-stable approximations of multivariate regularly varying time series

Anja Janßen

A regularly varying time series as introduced in Basrak and Segers (2009) is a (multivariate) time series such that all finite dimensional distributions are multivariate regularly…

math.PR2016

Conditional Extreme Value Models: Fallacies and Pitfalls

Holger Drees, Anja Janßen

Conditional extreme value models have been introduced by Heffernan and Resnick (2007) to describe the asymptotic behavior of a random vector as one specific component becomes extre…

math.PR2016★ 3 cited

The eigenvalues of the sample covariance matrix of a multivariate heavy-tailed stochastic volatility model

Anja Janßen, Thomas Mikosch, Mohsen Rezapour +1

We consider a multivariate heavy-tailed stochastic volatility model and analyze the large-sample behavior of its sample covariance matrix. We study the limiting behavior of its ent…

math.PR2015

Joint exceedances of random products

Anja Janßen, Holger Drees

We analyze the joint extremal behavior of random products of the form for non-negative, independent regularly varying random vari…

math.PR2013★ 19 cited

A stochastic volatility model with flexible extremal dependence structure

Anja Janssen, Holger Drees

Stochastic volatility processes with heavy-tailed innovations are a well-known model for financial time series. In these models, the extremes of the log returns are mainly driven b…

math.PR2013★ 2 cited

Markov tail chains

Anja Janßen, Johan Segers

The extremes of a univariate Markov chain with regulary varying stationary marginal distribution and asymptotically linear behavior are known to exhibit a multiplicative random wal…

math.PR2011

Joint Extremal Behavior of Hidden and Observable Time Series with an Application to GARCH Processes

Andree Ehlert, Ulf-Rainer Fiebig, Anja Janßen +1

We study the behavior of a real-valued and unobservable process (Y_t) under an extreme event of a related process (X_t) that is observable. Our analysis is motivated by the well-kn…