Fitting probability distributions to market risk and insurance risk

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F61989100%3A27510%2F15%3A86095921" target="_blank" >RIV/61989100:27510/15:86095921 - isvavai.cz</a>

Výsledek na webu

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DOI - Digital Object Identifier

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Jazyk výsledku

angličtina

Název v původním jazyce

Fitting probability distributions to market risk and insurance risk

Popis výsledku v původním jazyce

Determining the parametric VaR approach is very important in establishing the probability distribution of a risk factor. We assume that a normal distribution is symmetric; however, it has some limitations. This distribution is used for modelling asymmetric data or data that have only positive values, such as insurance claims. The aim of the paper is to find the best probability distribution for stock exchange index returns and for insurance claims. The paper is structured as follows. Firstly, we describe the typical probability distributions used in finance, namely normal, Student, logistic, gamma, exponential and lognormal distribution, and the methods of verification. Subsequently, parameters of the distribution types are estimated via the maximum likelihood method, and after that we calculate the value at risk. The VaR is calculated even though the time series do not correspond to the stated types of proba-bility distribution; nevertheless, we calculate the value at risk for all the

Název v anglickém jazyce

Fitting probability distributions to market risk and insurance risk

Popis výsledku anglicky

Determining the parametric VaR approach is very important in establishing the probability distribution of a risk factor. We assume that a normal distribution is symmetric; however, it has some limitations. This distribution is used for modelling asymmetric data or data that have only positive values, such as insurance claims. The aim of the paper is to find the best probability distribution for stock exchange index returns and for insurance claims. The paper is structured as follows. Firstly, we describe the typical probability distributions used in finance, namely normal, Student, logistic, gamma, exponential and lognormal distribution, and the methods of verification. Subsequently, parameters of the distribution types are estimated via the maximum likelihood method, and after that we calculate the value at risk. The VaR is calculated even though the time series do not correspond to the stated types of proba-bility distribution; nevertheless, we calculate the value at risk for all the

Druh

J_x - Nezařazeno - Článek v odborném periodiku (Jimp, Jsc a Jost)

CEP obor

AE - Řízení, správa a administrativa

OECD FORD obor

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Projekt

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Návaznosti

S - Specificky vyzkum na vysokych skolach

Rok uplatnění

2015

Kód důvěrnosti údajů

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

Název periodika

Ekonomická revue

ISSN

1212-3951

e-ISSN

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Svazek periodika

18

Číslo periodika v rámci svazku

4

Stát vydavatele periodika

CZ - Česká republika

Počet stran výsledku

7

Strana od-do

"167 - 173"

Kód UT WoS článku

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EID výsledku v databázi Scopus

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