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Document type:
Zeitschriftenaufsatz 
Author(s):
Kley, Oliver; Klüppelberg, Claudia; Paterlini, Sandra 
Title:
Modelling extremal dependence for operational risk by a bipartite graph 
Abstract:
We introduce a statistical model for operational losses based on heavy-tailed distributions and bipartite graphs, which captures the event type and business line structure of operational risk data. The model explicitly takes into account the Pareto tails of losses and the heterogeneous dependence structures between them. We then derive estimators and provide estimation methods for individual as well as aggregated tail risk, measured in terms of Value-at-Risk and Conditional-Tail-Expectation for...    »
 
Keywords:
Bipartite graph Extremal dependence Operational risk Quantile risk measure Value-at-Risk Expected shortfall 
Dewey Decimal Classification:
510 Mathematik 
Journal title:
Journal of Banking & Finance 
Year:
2020 
Journal volume:
117 
Year / month:
2020-08 
Quarter:
3. Quartal 
Month:
Aug 
Pages contribution:
105855 
Publisher:
Elsevier BV 
E-ISSN:
0378-4266 
Notes:
Available online 16 May 2020 
Status:
Verlagsversion / published 
Accepted:
10.05.2020 
Date of publication:
01.08.2020 
Semester:
SS 20 
TUM Institution:
Lehrstuhl für Mathematische Statistik 
Format:
Text