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Peaks over thresholds modelling with multivariate generalized Pareto distributions

Anna Kiriliouk ; Holger Rootzén (Institutionen för matematiska vetenskaper, matematisk statistik) ; Johan Segers ; Jennifer L. Wadsworth
(2017)
[Preprint]

The multivariate generalized Pareto distribution arises as the limit of a normal- ized vector conditioned upon at least one component of that vector being extreme. Statistical modelling using multivariate generalized Pareto distributions constitutes the multivariate analogue of univariate peaks over thresholds modelling. We exhibit a construction device which allows us to develop a variety of new and existing para- metric tail dependence models. A censored likelihood procedure is proposed to make inference on these models, together with a threshold selection procedure and several goodness-of-fit diagnostics. The models are fitted to returns of four UK-based banks and to rainfall data in the context of landslide risk estimation.

Nyckelord: extreme values, financial risk measurment, landslides



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Denna post skapades 2016-12-09. Senast ändrad 2017-08-25.
CPL Pubid: 246026

 

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Institutioner (Chalmers)

Institutionen för matematiska vetenskaper, matematisk statistik (2005-2016)

Ämnesområden

Building Futures
Energi
Matematik
Sannolikhetsteori och statistik

Chalmers infrastruktur