The possibilities of the use of the coefficient of variation over a high threshold in tail modelling are discussed. The paper also considers multiple threshold tests for a generalized Pareto distribution, together with a threshold selection algorithm. One of the main contributions is to extend the methodology based on moments to all distributions, even without finite moments. These techniques are applied to euro/dollar daily exchange rates and to Danish fire insurance losses
In order to model the tail of a distribution, one has to define the threshold above or below which a...
We propose a dynamic semi-parametric framework to study time variation in tail parameters. The frame...
Extreme Value Theory is increasingly used in the modelling of financial time series. The non-normali...
The possibilities of the use of the coefficient of variation over a high threshold in tail modelling...
We define the extreme values of any random sample of size n from a distribution function F as the ob...
Tail data are often modelled by fitting a generalized Pareto distribution (GPD) to the exceedances o...
Tail data are often modelled by fitting a generalized Pareto distribution (GPD) to the exceedances o...
The objective of extreme value analysis is to quantify the probabilistic behavior of unusually large...
PEst-OE/MAT/UI0006/2011 PEst-OE/MAT/UI0297/2011In this paper, for heavy-tailed models and through th...
Most extreme events in real life can be faithfully modeled as random realizations from a Generalized...
The most popular approach in extreme value statistics is the modelling of threshold exceedances usin...
The statistical modelling of integer-valued extremes such as large avalanche counts has received les...
Extreme-value theory is the branch of statistics concerned with modelling the joint tail of a multiv...
The most popular approach in extreme value statistics is the modelling of threshold exceedances usin...
Good estimates for the tails of loss severity distributions are essential for pricing or positioning...
In order to model the tail of a distribution, one has to define the threshold above or below which a...
We propose a dynamic semi-parametric framework to study time variation in tail parameters. The frame...
Extreme Value Theory is increasingly used in the modelling of financial time series. The non-normali...
The possibilities of the use of the coefficient of variation over a high threshold in tail modelling...
We define the extreme values of any random sample of size n from a distribution function F as the ob...
Tail data are often modelled by fitting a generalized Pareto distribution (GPD) to the exceedances o...
Tail data are often modelled by fitting a generalized Pareto distribution (GPD) to the exceedances o...
The objective of extreme value analysis is to quantify the probabilistic behavior of unusually large...
PEst-OE/MAT/UI0006/2011 PEst-OE/MAT/UI0297/2011In this paper, for heavy-tailed models and through th...
Most extreme events in real life can be faithfully modeled as random realizations from a Generalized...
The most popular approach in extreme value statistics is the modelling of threshold exceedances usin...
The statistical modelling of integer-valued extremes such as large avalanche counts has received les...
Extreme-value theory is the branch of statistics concerned with modelling the joint tail of a multiv...
The most popular approach in extreme value statistics is the modelling of threshold exceedances usin...
Good estimates for the tails of loss severity distributions are essential for pricing or positioning...
In order to model the tail of a distribution, one has to define the threshold above or below which a...
We propose a dynamic semi-parametric framework to study time variation in tail parameters. The frame...
Extreme Value Theory is increasingly used in the modelling of financial time series. The non-normali...