On the impact of distributional assumptions for operational risk modelling
Result description
Operational risk modelling is one of the most challenging risk types due to its serious impact on the health of financial institutions as well as lack of data leading to modelling difficulties. It follows that it is quite hard to get reliable estimate of the probability distribution of risk events, as concerns both, the frequencies and the severity, and simultaneously, there is a need to estimate the risk levels in the tails. In this paper we focus on the case of one financial institution with rather insufficient databases of risk events and try to estimate the risk (in terms of VaR and cVaR) using various kinds of Lévy models. The results show that there can be quite significant differences among weekly- and monthly-aggregated data especially in the tails, though rather simplifying Gaussian distribution does not strongly differ from theoretically more appropriate gamma or Weibull distributions. (C) 2019 TeknoScienze. All rights reserved.
Keywords
The result's identifiers
Result code in IS VaVaI
Result on the web
DOI - Digital Object Identifier
—
Alternative languages
Result language
angličtina
Original language name
On the impact of distributional assumptions for operational risk modelling
Original language description
Operational risk modelling is one of the most challenging risk types due to its serious impact on the health of financial institutions as well as lack of data leading to modelling difficulties. It follows that it is quite hard to get reliable estimate of the probability distribution of risk events, as concerns both, the frequencies and the severity, and simultaneously, there is a need to estimate the risk levels in the tails. In this paper we focus on the case of one financial institution with rather insufficient databases of risk events and try to estimate the risk (in terms of VaR and cVaR) using various kinds of Lévy models. The results show that there can be quite significant differences among weekly- and monthly-aggregated data especially in the tails, though rather simplifying Gaussian distribution does not strongly differ from theoretically more appropriate gamma or Weibull distributions. (C) 2019 TeknoScienze. All rights reserved.
Czech name
—
Czech description
—
Classification
Type
JSC - Article in a specialist periodical, which is included in the SCOPUS database
CEP classification
—
OECD FORD branch
50200 - Economics and Business
Result continuities
Project
Continuities
P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)
Others
Publication year
2019
Confidentiality
S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů
Data specific for result type
Name of the periodical
Chimica Oggi
ISSN
0392-839X
e-ISSN
—
Volume of the periodical
37
Issue of the periodical within the volume
1
Country of publishing house
IT - ITALY
Number of pages
5
Pages from-to
39-43
UT code for WoS article
—
EID of the result in the Scopus database
2-s2.0-85072394742
Basic information
Result type
JSC - Article in a specialist periodical, which is included in the SCOPUS database
OECD FORD
Economics and Business
Year of implementation
2019