7 papers
Statistical inference for extremal directions in high-dimensional spaces
Lucas Butsch, Vicky Fasen-Hartmann
In multivariate extreme value statistics, the first step in understanding the dependence structure of extremes is identifying the directions in which they occur. The novelty of thi…
Asymptotic independence in higher dimensions and its implications on risk management
Bikramjit Das, Vicky Fasen-Hartmann
In the study of extremes, the presence of asymptotic independence signifies that extreme events across multiple variables are probably less likely to occur together. Although well-…
Information criteria for the number of directions of extremes in high-dimensional data
Lucas Butsch, Vicky Fasen-Hartmann
In multivariate extreme value analysis, the estimation of the dependence structure in extremes is demanding, especially in the context of high-dimensional data. Therefore, a common…
Estimation of the number of principal components in high-dimensional multivariate extremes
Lucas Butsch, Vicky Fasen-Hartmann
For multivariate regularly random vectors of dimension , the dependence structure of the extremes is modeled by the so-called angular measure. When the dimension is high, es…
Measuring risk contagion in financial networks with CoVaR
Bikramjit Das, Vicky Fasen-Hartmann
The stability of a complex financial system may be assessed by measuring risk contagion between various financial institutions with relatively high exposure. We consider a financia…
Mixed orthogonality graphs for continuous-time state space models and orthogonal projections
Vicky Fasen-Hartmann, Lea Schenk
In this paper, we derive (local) orthogonality graphs for the popular continuous-time state space models, including in particular multivariate continuous-time ARMA (MCARMA) process…