On the impact of distributional assumptions for operational risk modelling

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F19%3A10242951" target="_blank" >RIV/61989100:27510/19:10242951 - isvavai.cz</a>

Výsledek na webu

<a href="https://www.teknoscienze.com/tks_article/on-the-impact-of-distributional-assumptions-for-operational-risk-modelling/" target="_blank" >https://www.teknoscienze.com/tks_article/on-the-impact-of-distributional-assumptions-for-operational-risk-modelling/</a>

DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

On the impact of distributional assumptions for operational risk modelling

Popis výsledku v původním jazyce

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.

Název v anglickém jazyce

On the impact of distributional assumptions for operational risk modelling

Popis výsledku anglicky

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.

Druh

J_SC - Článek v periodiku v databázi SCOPUS

CEP obor

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OECD FORD obor

50200 - Economics and Business

Projekt

<a href="/cs/project/GA13-13142S" target="_blank" >GA13-13142S: Ověření vhodnosti jednotlivých Lévyho modelů pro vybrané úlohy finanční modelování</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2019

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název periodika

Chimica Oggi

ISSN

0392-839X

e-ISSN

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Svazek periodika

37

Číslo periodika v rámci svazku

1

Stát vydavatele periodika

IT - Italská republika

Počet stran výsledku

5

Strana od-do

39-43

Kód UT WoS článku

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EID výsledku v databázi Scopus

2-s2.0-85072394742