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On Modeling Operational Risk using Extreme Value Theory

Kästner, Valentin (2016) MASM01 20161
Mathematical Statistics
Abstract (Swedish)
The main goal of this thesis is to show how operational risk can be measured if even the
use of standard extreme value theory fails to explain single catastrophic events in the tail
of the distribution. Against the background of regulatory requirements imposed by the
Basel Accords, an Advanced Measurement Approach (AMA) is developed for a dataset of
operational losses occurred in US businesses between 1985 and 2008.
Two alternative approaches are described for modeling the loss frequency when the
losses are reported by the month. A copula approach is applied to capture dependence
among dierent loss distributions corresponding to dierent event types. The resulting
99:9% Value-at-Risk, which determines the capital requirement, is... (More)
The main goal of this thesis is to show how operational risk can be measured if even the
use of standard extreme value theory fails to explain single catastrophic events in the tail
of the distribution. Against the background of regulatory requirements imposed by the
Basel Accords, an Advanced Measurement Approach (AMA) is developed for a dataset of
operational losses occurred in US businesses between 1985 and 2008.
Two alternative approaches are described for modeling the loss frequency when the
losses are reported by the month. A copula approach is applied to capture dependence
among dierent loss distributions corresponding to dierent event types. The resulting
99:9% Value-at-Risk, which determines the capital requirement, is compared to a model
assuming perfect dependence. (Less)
Please use this url to cite or link to this publication:
author
Kästner, Valentin
supervisor
organization
course
MASM01 20161
year
type
H2 - Master's Degree (Two Years)
subject
language
English
id
8877010
date added to LUP
2016-06-03 11:06:29
date last changed
2016-06-03 11:06:29
@misc{8877010,
  abstract     = {The main goal of this thesis is to show how operational risk can be measured if even the
use of standard extreme value theory fails to explain single catastrophic events in the tail
of the distribution. Against the background of regulatory requirements imposed by the
Basel Accords, an Advanced Measurement Approach (AMA) is developed for a dataset of
operational losses occurred in US businesses between 1985 and 2008.
Two alternative approaches are described for modeling the loss frequency when the
losses are reported by the month. A copula approach is applied to capture dependence
among dierent loss distributions corresponding to dierent event types. The resulting
99:9% Value-at-Risk, which determines the capital requirement, is compared to a model
assuming perfect dependence.},
  author       = {Kästner, Valentin},
  language     = {eng},
  note         = {Student Paper},
  title        = {On Modeling Operational Risk using Extreme Value Theory},
  year         = {2016},
}