87 citations · 390 across the 29 of their papers we have counts for
35 papers
Estimating a Directed Tree for Extremes
Ngoc Mai Tran, Johannes Buck, Claudia Klüppelberg
We propose a new method to estimate a root-directed spanning tree from extreme data. A prominent example is a river network, to be discovered from extreme flow measured at a set of…
Conditional Independence in Max-linear Bayesian Networks
Carlos Améndola, Claudia Klüppelberg, Steffen Lauritzen +1
Motivated by extreme value theory, max-linear Bayesian networks have been recently introduced and studied as an alternative to linear structural equation models. However, for max-l…
Max-linear models in random environment
Claudia Klüppelberg, Ercan Sönmez
We extend previous work of max-linear models on finite directed acyclic graphs to infinite graphs as well as random graphs, and investigate their relations to classical percolation…
Indirect Inference for Lévy-driven continuous-time GARCH models
Thiago do Rêgo Sousa, Stephan Haug, Claudia Klüppelberg
We advocate the use of an Indirect Inference method to estimate the parameter of a COGARCH(1,1) process for equally spaced observations. This requires that the true model can be si…
Smoothing of transport plans with fixed marginals and rigorous semiclassical limit of the Hohenberg-Kohn functional
Codina Cotar, Gero Friesecke, Claudia Klüppelberg
We prove rigorously that the exact N-electron Hohenberg-Kohn density functional converges in the strongly interacting limit to the strictly correlated electrons (SCE) functional, a…
Generalised least squares estimation of regularly varying space-time processes based on flexible observation schemes
Sven Buhl, Claudia Klüppelberg
Regularly varying stochastic processes model extreme dependence between process values at different locations and/or time points. For such processes we propose a two-step parameter…
Contagion in financial systems: A Bayesian network approach
Carsten Chong, Claudia Klüppelberg
We develop a structural default model for interconnected financial institutions in a probabilistic framework. For all possible network structures we characterize the joint default…
Tail dependence of recursive max-linear models with regularly varying noise variables
Nadine Gissibl, Claudia Klüppelberg, Moritz Otto
Recursive max-linear structural equation models with regularly varying noise variables are considered. Their causal structure is represented by a directed acyclic graph (DAG). The…
Conditional loss probabilities for systems of economic agents sharing light-tailed claims with analysis of portfolio diversification benefits
Claudia Klüppelberg, Miriam Isabel Seifert
We analyze systems of agents sharing light-tailed risky claims issued by different financial objects. Assuming exponentially distributed claims, we obtain that both agents' and sys…
Semiparametric estimation for isotropic max-stable space-time processes
Sven Buhl, Richard A. Davis, Claudia Klüppelberg +1
Regularly varying space-time processes have proved useful to study extremal dependence in space-time data. We propose a semiparametric estimation procedure based on a closed form e…
Limit theory for the empirical extremogram of random fields
Sven Buhl, Claudia Klüppelberg
Regularly varying stochastic processes are able to model extremal dependence between process values at locations in random fields. We investigate the empirical extremogram as an es…
An Innovations Algorithm for the prediction of functional linear processes
Johannes Klepsch, Claudia Klüppelberg
When observations are curves over some natural time interval, the field of functional data analysis comes into play. Functional linear processes account for temporal dependence in…
Prediction of functional ARMA processes with an application to traffic data
J. Klepsch, C. Klüppelberg, T. Wei
This work is devoted to functional ARMA processes and approximating vector models based on functional PCA in the context of prediction. After deriving sufficient conditions…
Max-linear models on directed acyclic graphs
Nadine Gissibl, Claudia Klüppelberg
We consider a new recursive structural equation model where all variables can be written as max-linear function of their parental node variables and independent noise variables. Th…
Conditional risk measures in a bipartite market structure
Oliver Kley, Claudia Klüppelberg, Gesine Reinert
In this paper we study the effect of network structure between agents and objects on measures for systemic risk. We model the influence of sharing large exogeneous losses to the fi…
Partial mean field limits in heterogeneous networks
Carsten Chong, Claudia Klüppelberg
We investigate systems of interacting stochastic differential equations with two kinds of heterogeneity: one originating from different weights of the linkages, and one concerning…
Time-consistency of risk measures with GARCH volatilities and their estimation
Claudia Klüppelberg, Jianing Zhang
In this paper we study time-consistent risk measures for returns that are given by a GARCH(1,1) model. We present a construction of risk measures based on their static counterparts…
Anisotropic Brown-Resnick space-time processes: estimation and model assessment
Sven Buhl, Claudia Klüppelberg
Spatially isotropic max-stable processes have been used to model extreme spatial or space-time observations. One prominent model is the Brown-Resnick process, which has been succes…
Bounds for randomly shared risk of heavy-tailed loss factors
Oliver Kley, Claudia Kluppelberg
For a risk vector , whose components are shared among agents by some random mechanism, we obtain asymptotic lower and upper bounds for the individual agents' exposure risk and t…
Simulation of stochastic Volterra equations driven by space--time Lévy noise
Bohan Chen, Carsten Chong, Claudia Klüppelberg
In this paper we investigate two numerical schemes for the simulation of stochastic Volterra equations driven by space--time Lévy noise of pure-jump type. The first one is based on…
Fractionally integrated COGARCH processes
Stephan Haug, Claudia Klüppelberg, German Straub
We construct fractionally integrated continuous-time GARCH models, which capture the observed long range dependence of squared volatility in high-frequency data. Since the usual Mo…
Risk in a large claims insurance market with bipartite graph structure
Oliver Kley, Claudia Kluppelberg, Gesine Reinert
We model the influence of sharing large exogeneous losses to the reinsurance market by a bipartite graph. Using Pareto-tailed claims and multivariate regular variation we obtain as…
Systemic risk through contagion in a core-periphery structured banking network
Oliver Kley, Claudia Klüppelberg, Lukas Reichel
We contribute to the understanding of how systemic risk arises in a network of credit-interlinked agents. Motivated by empirical studies we formulate a network model which, despite…
Two-step estimation of a multivariate Lévy process
Habib Esmaeili, Claudia Klüppelberg
Based on the concept of a Lévy copula to describe the dependence structure of a multivariate Lévy process we present a new estimation procedure. We consider a parametric model for…